\n\n[<< Day 1](../readme.md) | [Day 3 >>](../03_Day_Operators/03_operators.md)\n\n\n\n- [📘 Day 2](#-day-2)\n - [Built in functions](#built-in-functions)\n - [Variables](#variables)\n - [Declaring Multiple Variable in a Line](#declaring-multiple-variable-in-a-line)\n - [Data Types](#data-types)\n - [Checking Data types and Casting](#checking-data-types-and-casting)\n - [Numbers](#numbers)\n - [💻 Exercises - Day 2](#-exercises---day-2)\n - [Exercises: Level 1](#exercises-level-1)\n - [Exercises: Level 2](#exercises-level-2)\n\n# 📘 Day 2\n\n## Built in functions\n\nIn Python we have lots of built-in functions. Built-in functions are globally available for your use that mean you can make use of the built-in functions without importing or configuring. Some of the most commonly used Python built-in functions are the following: _print()_, _len()_, _type()_, _int()_, _float()_, _str()_, _input()_, _list()_, _dict()_, _min()_, _max()_, _sum()_, _sorted()_, _open()_, _file()_, _help()_, and _dir()_. In the following table you will see an exhaustive list of Python built-in functions taken from [python documentation](https://docs.python.org/3/library/functions.html).\n\n\n\nLet us open the Python shell and start using some of the most common built-in functions.\n\n\n\nLet us practice more by using different built-in functions\n\n\n\nAs you can see from the terminal above, Python has got reserved words. We do not use reserved words to declare variables or functions. We will cover variables in the next section.\n\nI believe, by now you are familiar with built-in functions. Let us do one more practice of built-in functions and we will move on to the next section.\n\n\n\n## Variables\n\nVariables store data in a computer memory. Mnemonic variables are recommended to use in many programming languages. A mnemonic variable is a variable name that can be easily remembered and associated. A variable refers to a memory address in which data is stored.\nNumber at the beginning, special character, hyphen are not allowed when naming a variable. A variable can have a short name (like x, y, z), but a more descriptive name (firstname, lastname, age, country) is highly recommended.\n\nPython Variable Name Rules\n\n- A variable name must start with a letter or the underscore character\n- A variable name cannot start with a number\n- A variable name can only contain alpha-numeric characters and underscores (A-z, 0-9, and \\_ )\n- Variable names are case-sensitive (firstname, Firstname, FirstName and FIRSTNAME) are different variables)\n\nHere are some example of valid variable names:\n\n```shell\nfirstname\nlastname\nage\ncountry\ncity\nfirst_name\nlast_name\ncapital_city\n_if # if we want to use reserved word as a variable\nyear_2021\nyear2021\ncurrent_year_2021\nbirth_year\nnum1\nnum2\n```\n\nInvalid variables names\n\n```shell\nfirst-name\nfirst@name\nfirst$name\nnum-1\n1num\n```\n\nWe will use standard Python variable naming style which has been adopted by many Python developers. Python developers use snake case(snake_case) variable naming convention. We use underscore character after each word for a variable containing more than one word(eg. first_name, last_name, engine_rotation_speed). The example below is an example of standard naming of variables, underscore is required when the variable name is more than one word.\n\nWhen we assign a certain data type to a variable, it is called variable declaration. For instance in the example below my first name is assigned to a variable first_name. The equal sign is an assignment operator. Assigning means storing data in the variable. The equal sign in Python is not equality as in Mathematics.\n\n_Example:_\n\n```py\n# Variables in Python\nfirst_name = 'Asabeneh'\nlast_name = 'Yetayeh'\ncountry = 'Finland'\ncity = 'Helsinki'\nage = 250\nis_married = True\nskills = ['HTML', 'CSS', 'JS', 'React', 'Python']\nperson_info = {\n 'firstname':'Asabeneh',\n 'lastname':'Yetayeh',\n 'country':'Finland',\n 'city':'Helsinki'\n }\n```\n\nLet us use the _print()_ and _len()_ built-in functions. Print function takes unlimited number of arguments. An argument is a value which we can be passed or put inside the function parenthesis, see the example below.\n\n**Example:**\n\n```py\nprint('Hello, World!') # The text Hello, World! is an argument\nprint('Hello',',', 'World','!') # it can take multiple arguments, four arguments have been passed\nprint(len('Hello, World!')) # it takes only one argument\n```\n\nLet us print and also find the length of the variables declared at the top:\n\n**Example:**\n\n```py\n# Printing the values stored in the variables\n\nprint('First name:', first_name)\nprint('First name length:', len(first_name))\nprint('Last name: ', last_name)\nprint('Last name length: ', len(last_name))\nprint('Country: ', country)\nprint('City: ', city)\nprint('Age: ', age)\nprint('Married: ', is_married)\nprint('Skills: ', skills)\nprint('Person information: ', person_info)\n```\n\n### Declaring Multiple Variable in a Line\n\nMultiple variables can also be declared in one line:\n\n**Example:**\n\n```py\nfirst_name, last_name, country, age, is_married = 'Asabeneh', 'Yetayeh', 'Helsink', 250, True\n\nprint(first_name, last_name, country, age, is_married)\nprint('First name:', first_name)\nprint('Last name: ', last_name)\nprint('Country: ', country)\nprint('Age: ', age)\nprint('Married: ', is_married)\n```\n\nGetting user input using the _input()_ built-in function. Let us assign the data we get from a user into first_name and age variables.\n**Example:**\n\n```py\nfirst_name = input('What is your name: ')\nage = input('How old are you? ')\n\nprint(first_name)\nprint(age)\n```\n\n## Data Types\n\nThere are several data types in Python. To identify the data type we use the _type_ built-in function. I would like to ask you to focus on understanding different data types very well. When it comes to programming, it is all about data types. I introduced data types at the very beginning and it comes again, because every topic is related to data types. We will cover data types in more detail in their respective sections.\n\n## Checking Data types and Casting\n\n- Check Data types: To check the data type of certain data/variable we use the _type_\n **Examples:**\n\n```py\n# Different python data types\n# Let's declare variables with various data types\n\nfirst_name = 'Asabeneh' # str\nlast_name = 'Yetayeh' # str\ncountry = 'Finland' # str\ncity= 'Helsinki' # str\nage = 250 # int, it is not my real age, don't worry about it\n\n# Printing out types\nprint(type('Asabeneh')) # str\nprint(type(first_name)) # str\nprint(type(10)) # int\nprint(type(3.14)) # float\nprint(type(1 + 1j)) # complex\nprint(type(True)) # bool\nprint(type([1, 2, 3, 4])) # list\nprint(type({'name':'Asabeneh'})) # dict\nprint(type((1,2))) # tuple\nprint(type(zip([1,2],[3,4]))) # zip\n```\n\n- Casting: Converting one data type to another data type. We use _int()_, _float()_, _str()_, _list_, _set_\n When we do arithmetic operations string numbers should be first converted to int or float otherwise it will return an error. If we concatenate a number with a string, the number should be first converted to a string. We will talk about concatenation in String section.\n\n **Examples:**\n\n```py\n# int to float\nnum_int = 10\nprint('num_int',num_int) # 10\nnum_float = float(num_int)\nprint('num_float:', num_float) # 10.0\n\n# float to int\ngravity = 9.81\nprint(int(gravity)) # 9\n\n# int to str\nnum_int = 10\nprint(num_int) # 10\nnum_str = str(num_int)\nprint(num_str) # '10'\n\n# str to int or float\nnum_str = '10.6'\nnum_float = float(num_str) # Convert the string to a float first\nnum_int = int(num_float) # Then convert the float to an integer\nprint('num_int', int(num_str)) # 10\nprint('num_float', float(num_str)) # 10.6\nnum_int = int(num_float)\nprint('num_int', int(num_int)) # 10\n\n# str to list\nfirst_name = 'Asabeneh'\nprint(first_name) # 'Asabeneh'\nfirst_name_to_list = list(first_name)\nprint(first_name_to_list) # ['A', 's', 'a', 'b', 'e', 'n', 'e', 'h']\n```\n\n## Numbers\n\nNumber data types in Python:\n\n1. Integers: Integer(negative, zero and positive) numbers\n Example:\n ... -3, -2, -1, 0, 1, 2, 3 ...\n\n2. Floating Point Numbers(Decimal numbers)\n Example:\n ... -3.5, -2.25, -1.0, 0.0, 1.1, 2.2, 3.5 ...\n\n3. Complex Numbers\n Example:\n 1 + j, 2 + 4j, 1 - 1j\n\n🌕 You are awesome. You have just completed day 2 challenges and you are two steps ahead on your way to greatness. Now do some exercises for your brain and muscles.\n\n## 💻 Exercises - Day 2\n\n### Exercises: Level 1\n\n1. Inside 30DaysOfPython create a folder called day_2. Inside this folder create a file named variables.py\n2. Write a python comment saying 'Day 2: 30 Days of python programming'\n3. Declare a first name variable and assign a value to it\n4. Declare a last name variable and assign a value to it\n5. Declare a full name variable and assign a value to it\n6. Declare a country variable and assign a value to it\n7. Declare a city variable and assign a value to it\n8. Declare an age variable and assign a value to it\n9. Declare a year variable and assign a value to it\n10. Declare a variable is_married and assign a value to it\n11. Declare a variable is_true and assign a value to it\n12. Declare a variable is_light_on and assign a value to it\n13. Declare multiple variable on one line\n\n### Exercises: Level 2\n\n1. Check the data type of all your variables using type() built-in function\n2. Using the _len()_ built-in function, find the length of your first name\n3. Compare the length of your first name and your last name\n4. Declare 5 as num_one and 4 as num_two\n5. Add num_one and num_two and assign the value to a variable total\n6. Subtract num_two from num_one and assign the value to a variable diff\n7. Multiply num_two and num_one and assign the value to a variable product\n8. Divide num_one by num_two and assign the value to a variable division\n9. Use modulus division to find num_two divided by num_one and assign the value to a variable remainder\n10. Calculate num_one to the power of num_two and assign the value to a variable exp\n11. Find floor division of num_one by num_two and assign the value to a variable floor_division\n12. The radius of a circle is 30 meters.\n 1. Calculate the area of a circle and assign the value to a variable name of _area_of_circle_\n 2. Calculate the circumference of a circle and assign the value to a variable name of _circum_of_circle_\n 3. Take radius as user input and calculate the area.\n13. Use the built-in input function to get first name, last name, country and age from a user and store the value to their corresponding variable names\n14. Run help('keywords') in Python shell or in your file to check for the Python reserved words or keywords\n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 1](../readme.md) | [Day 3 >>](../03_Day_Operators/03_operators.md)\n"
},
{
"path": "02_Day_Variables_builtin_functions/variables.py",
"content": "\n# Variables in Python\n\nfirst_name = 'Asabeneh'\nlast_name = 'Yetayeh'\ncountry = 'Finland'\ncity = 'Helsinki'\nage = 250\nis_married = True\nskills = ['HTML', 'CSS', 'JS', 'React', 'Python']\nperson_info = {\n 'firstname': 'Asabeneh',\n 'lastname': 'Yetayeh',\n 'country': 'Finland',\n 'city': 'Helsinki'\n}\n\n# Printing the values stored in the variables\n\nprint('First name:', first_name)\nprint('First name length:', len(first_name))\nprint('Last name: ', last_name)\nprint('Last name length: ', len(last_name))\nprint('Country: ', country)\nprint('City: ', city)\nprint('Age: ', age)\nprint('Married: ', is_married)\nprint('Skills: ', skills)\nprint('Person information: ', person_info)\n\n# Declaring multiple variables in one line\n\nfirst_name, last_name, country, age, is_married = 'Asabeneh', 'Yetayeh', 'Helsink', 250, True\n\nprint(first_name, last_name, country, age, is_married)\nprint('First name:', first_name)\nprint('Last name: ', last_name)\nprint('Country: ', country)\nprint('Age: ', age)\nprint('Married: ', is_married)\n"
},
{
"path": "03_Day_Operators/03_operators.md",
"content": "
\n\n[<< Day 2](../02_Day_Variables_builtin_functions/02_variables_builtin_functions.md) | [Day 4 >>](../04_Day_Strings/04_strings.md)\n\n\n\n- [📘 Day 3](#-day-3)\n - [Boolean](#boolean)\n - [Operators](#operators)\n - [Assignment Operators](#assignment-operators)\n - [Arithmetic Operators:](#arithmetic-operators)\n - [Comparison Operators](#comparison-operators)\n - [Logical Operators](#logical-operators)\n - [💻 Exercises - Day 3](#-exercises---day-3)\n\n# 📘 Day 3\n\n## Boolean\n\nA boolean data type represents one of the two values: _True_ or _False_. The use of these data types will be clear once we start using the comparison operator. The first letter **T** for True and **F** for False should be capital unlike JavaScript.\n**Example: Boolean Values**\n\n```py\nprint(True)\nprint(False)\n```\n\n## Operators\n\nPython language supports several types of operators. In this section, we will focus on few of them.\n\n### Assignment Operators\n\nAssignment operators are used to assign values to variables. Let us take = as an example. Equal sign in mathematics shows that two values are equal, however in Python it means we are storing a value in a certain variable and we call it assignment or a assigning value to a variable. The table below shows the different types of python assignment operators, taken from [w3school](https://www.w3schools.com/python/python_operators.asp).\n\n\n\n### Arithmetic Operators:\n\n- Addition(+): a + b\n- Subtraction(-): a - b\n- Multiplication(*): a * b\n- Division(/): a / b\n- Modulus(%): a % b\n- Floor division(//): a // b\n- Exponentiation(**): a ** b\n\n\n\n**Example:Integers**\n\n```py\n# Arithmetic Operations in Python\n# Integers\n\nprint('Addition: ', 1 + 2) # 3\nprint('Subtraction: ', 2 - 1) # 1\nprint('Multiplication: ', 2 * 3) # 6\nprint ('Division: ', 4 / 2) # 2.0 Division in Python gives floating number\nprint('Division: ', 6 / 2) # 3.0 \nprint('Division: ', 7 / 2) # 3.5\nprint('Division without the remainder: ', 7 // 2) # 3, gives without the floating number or without the remaining\nprint ('Division without the remainder: ',7 // 3) # 2\nprint('Modulus: ', 3 % 2) # 1, Gives the remainder\nprint('Exponentiation: ', 2 ** 3) # 8 it means 2 * 2 * 2\n```\n\n**Example:Floats**\n\n```py\n# Floating numbers\nprint('Floating Point Number, PI', 3.14)\nprint('Floating Point Number, gravity', 9.81)\n```\n\n**Example:Complex numbers**\n\n```py\n# Complex numbers\nprint('Complex number: ', 1 + 1j)\nprint('Multiplying complex numbers: ',(1 + 1j) * (1 - 1j))\n```\n\nLet's declare a variable and assign a number data type. I am going to use single character variable but remember do not develop a habit of declaring such types of variables. Variable names should be all the time mnemonic.\n\n**Example:**\n\n```python\n# Declaring the variable at the top first\n\na = 3 # a is a variable name and 3 is an integer data type\nb = 2 # b is a variable name and 3 is an integer data type\n\n# Arithmetic operations and assigning the result to a variable\ntotal = a + b\ndiff = a - b\nproduct = a * b\ndivision = a / b\nremainder = a % b\nfloor_division = a // b\nexponential = a ** b\n\n# I should have used sum instead of total but sum is a built-in function - try to avoid overriding built-in functions\nprint(total) # if you do not label your print with some string, you never know where the result is coming from\nprint('a + b = ', total)\nprint('a - b = ', diff)\nprint('a * b = ', product)\nprint('a / b = ', division)\nprint('a % b = ', remainder)\nprint('a // b = ', floor_division)\nprint('a ** b = ', exponential)\n```\n\n**Example:**\n\n```py\nprint('== Addition, Subtraction, Multiplication, Division, Modulus ==')\n\n# Declaring values and organizing them together\nnum_one = 3\nnum_two = 4\n\n# Arithmetic operations\ntotal = num_one + num_two\ndiff = num_two - num_one\nproduct = num_one * num_two\ndiv = num_two / num_one\nremainder = num_two % num_one\n\n# Printing values with label\nprint('total: ', total)\nprint('difference: ', diff)\nprint('product: ', product)\nprint('division: ', div)\nprint('remainder: ', remainder)\n```\n\nLet us start connecting the dots and start making use of what we already know to calculate (area, volume,density, weight, perimeter, distance, force).\n\n**Example:**\n\n```py\n# Calculating area of a circle\nradius = 10 # radius of a circle\narea_of_circle = 3.14 * radius ** 2 # two * sign means exponent or power\nprint('Area of a circle:', area_of_circle)\n\n# Calculating area of a rectangle\nlength = 10\nwidth = 20\narea_of_rectangle = length * width\nprint('Area of rectangle:', area_of_rectangle)\n\n# Calculating a weight of an object\nmass = 75\ngravity = 9.81\nweight = mass * gravity\nprint(weight, 'N') # Adding unit to the weight\n\n# Calculate the density of a liquid\nmass = 75 # in Kg\nvolume = 0.075 # in cubic meter\ndensity = mass / volume # 1000 Kg/m^3\nprint(density, 'Kg/m^3') # Adding unit to the density\n\n```\n\n### Comparison Operators\n\nIn programming we compare values, we use comparison operators to compare two values. We check if a value is greater or less or equal to other value. The following table shows Python comparison operators which was taken from [w3shool](https://www.w3schools.com/python/python_operators.asp).\n\n\n**Example: Comparison Operators**\n\n```py\nprint(3 > 2) # True, because 3 is greater than 2\nprint(3 >= 2) # True, because 3 is greater than 2\nprint(3 < 2) # False, because 3 is greater than 2\nprint(2 < 3) # True, because 2 is less than 3\nprint(2 <= 3) # True, because 2 is less than 3\nprint(3 == 2) # False, because 3 is not equal to 2\nprint(3 != 2) # True, because 3 is not equal to 2\nprint(len('mango') == len('avocado')) # False\nprint(len('mango') != len('avocado')) # True\nprint(len('mango') < len('avocado')) # True\nprint(len('milk') != len('meat')) # False\nprint(len('milk') == len('meat')) # True\nprint(len('tomato') == len('potato')) # True\nprint(len('python') > len('dragon')) # False\n\n\n# Comparing something gives either a True or False\n\nprint('True == True: ', True == True)\nprint('True == False: ', True == False)\nprint('False == False:', False == False)\n```\n\nIn addition to the above comparison operator Python uses:\n\n- _is_: Returns true if both variables are the same object(x is y)\n- _is not_: Returns true if both variables are not the same object(x is not y)\n- _in_: Returns True if the queried list contains a certain item(x in y)\n- _not in_: Returns True if the queried list doesn't have a certain item(x not in y)\n\n```py\nprint('1 is 1', 1 is 1) # True - because the data values are the same\nprint('1 is not 2', 1 is not 2) # True - because 1 is not 2\nprint('A in Asabeneh', 'A' in 'Asabeneh') # True - A found in the string\nprint('B not in Asabeneh', 'B' in 'Asabeneh') # False - there is no uppercase B\nprint('coding' in 'coding for all') # True - because coding for all has the word coding\nprint('a in an:', 'a' in 'an') # True\nprint('4 is 2 ** 2:', 4 is 2 ** 2) # True\n```\n\n### Logical Operators\n\nUnlike other programming languages python uses keywords _and_, _or_ and _not_ for logical operators. Logical operators are used to combine conditional statements:\n\n\n\n```py\nprint(3 > 2 and 4 > 3) # True - because both statements are true\nprint(3 > 2 and 4 < 3) # False - because the second statement is false\nprint(3 < 2 and 4 < 3) # False - because both statements are false\nprint('True and True: ', True and True)\nprint(3 > 2 or 4 > 3) # True - because both statements are true\nprint(3 > 2 or 4 < 3) # True - because one of the statements is true\nprint(3 < 2 or 4 < 3) # False - because both statements are false\nprint('True or False:', True or False)\nprint(not 3 > 2) # False - because 3 > 2 is true, then not True gives False\nprint(not True) # False - Negation, the not operator turns true to false\nprint(not False) # True\nprint(not not True) # True\nprint(not not False) # False\n\n```\n\n🌕 You have boundless energy. You have just completed day 3 challenges and you are three steps ahead on your way to greatness. Now do some exercises for your brain and your muscles.\n\n## 💻 Exercises - Day 3\n\n1. Declare your age as integer variable\n2. Declare your height as a float variable\n3. Declare a variable that store a complex number\n4. Write a script that prompts the user to enter base and height of the triangle and calculate an area of this triangle (area = 0.5 x b x h).\n\n```py\n Enter base: 20\n Enter height: 10\n The area of the triangle is 100\n```\n\n5. Write a script that prompts the user to enter side a, side b, and side c of the triangle. Calculate the perimeter of the triangle (perimeter = a + b + c).\n\n```py\nEnter side a: 5\nEnter side b: 4\nEnter side c: 3\nThe perimeter of the triangle is 12\n```\n\n6. Get length and width of a rectangle using prompt. Calculate its area (area = length x width) and perimeter (perimeter = 2 x (length + width))\n7. Get radius of a circle using prompt. Calculate the area (area = pi x r x r) and circumference (c = 2 x pi x r) where pi = 3.14.\n8. Calculate the slope, x-intercept and y-intercept of y = 2x -2\n9. Slope is (m = y2-y1/x2-x1). Find the slope and [Euclidean distance](https://en.wikipedia.org/wiki/Euclidean_distance#:~:text=In%20mathematics%2C%20the%20Euclidean%20distance,being%20called%20the%20Pythagorean%20distance.) between point (2, 2) and point (6,10) \n10. Compare the slopes in tasks 8 and 9.\n11. Calculate the value of y (y = x^2 + 6x + 9). Try to use different x values and figure out at what x value y is going to be 0.\n12. Find the length of 'python' and 'dragon' and make a falsy comparison statement.\n13. Use _and_ operator to check if 'on' is found in both 'python' and 'dragon'\n14. _I hope this course is not full of jargon_. Use _in_ operator to check if _jargon_ is in the sentence.\n15. There is no 'on' in both dragon and python\n16. Find the length of the text _python_ and convert the value to float and convert it to string\n17. Even numbers are divisible by 2 and the remainder is zero. How do you check if a number is even or not using python?\n18. Check if the floor division of 7 by 3 is equal to the int converted value of 2.7.\n19. Check if type of '10' is equal to type of 10\n20. Check if int('9.8') is equal to 10\n21. Write a script that prompts the user to enter hours and rate per hour. Calculate pay of the person?\n\n```py\nEnter hours: 40\nEnter rate per hour: 28\nYour weekly earning is 1120\n```\n\n22. Write a script that prompts the user to enter number of years. Calculate the number of seconds a person can live. Assume a person can live hundred years\n\n```py\nEnter number of years you have lived: 100\nYou have lived for 3153600000 seconds.\n```\n\n23. Write a Python script that displays the following table\n\n```py\n1 1 1 1 1\n2 1 2 4 8\n3 1 3 9 27\n4 1 4 16 64\n5 1 5 25 125\n```\n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 2](../02_Day_Variables_builtin_functions/02_variables_builtin_functions.md) | [Day 4 >>](../04_Day_Strings/04_strings.md)\n"
},
{
"path": "03_Day_Operators/day-3.py",
"content": "# Arithmetic Operations in Python\n# Integers\n\nprint('Addition: ', 1 + 2)\nprint('Subtraction: ', 2 - 1)\nprint('Multiplication: ', 2 * 3)\n# Division in python gives floating number\nprint('Division: ', 4 / 2)\nprint('Division: ', 6 / 2)\nprint('Division: ', 7 / 2)\n# gives without the floating number or without the remaining\nprint('Division without the remainder: ', 7 // 2)\nprint('Modulus: ', 3 % 2) # Gives the remainder\nprint('Division without the remainder: ', 7 // 3)\nprint('Exponential: ', 3 ** 2) # it means 3 * 3\n\n# Floating numbers\nprint('Floating Number,PI', 3.14)\nprint('Floating Number, gravity', 9.81)\n\n# Complex numbers\nprint('Complex number: ', 1+1j)\nprint('Multiplying complex number: ', (1+1j) * (1-1j))\n\n# Declaring the variable at the top first\n\na = 3 # a is a variable name and 3 is an integer data type\nb = 2 # b is a variable name and 3 is an integer data type\n\n# Arithmetic operations and assigning the result to a variable\ntotal = a + b\ndiff = a - b\nproduct = a * b\ndivision = a / b\nremainder = a % b\nfloor_division = a // b\nexponential = a ** b\n\n# I should have used sum instead of total but sum is a built-in function try to avoid overriding builtin functions\nprint(total) # if you don't label your print with some string, you never know from where is the result is coming\nprint('a + b = ', total)\nprint('a - b = ', diff)\nprint('a * b = ', product)\nprint('a / b = ', division)\nprint('a % b = ', remainder)\nprint('a // b = ', floor_division)\nprint('a ** b = ', exponential)\n\n# Declaring values and organizing them together\nnum_one = 3\nnum_two = 4\n\n# Arithmetic operations\ntotal = num_one + num_two\ndiff = num_two - num_one\nproduct = num_one * num_two\ndiv = num_two / num_two\nremainder = num_two % num_one\n\n# Printing values with label\nprint('total: ', total)\nprint('difference: ', diff)\nprint('product: ', product)\nprint('division: ', div)\nprint('remainder: ', remainder)\n\n\n# Calculating area of a circle\nradius = 10 # radius of a circle\n# two * sign means exponent or power\narea_of_circle = 3.14 * radius ** 2\nprint('Area of a circle:', area_of_circle)\n\n# Calculating area of a rectangle\nlength = 10\nwidth = 20\narea_of_rectangle = length * width\nprint('Area of rectangle:', area_of_rectangle)\n\n# Calculating a weight of an object\nmass = 75\ngravity = 9.81\nweight = mass * gravity\nprint(weight, 'N')\n\nprint(3 > 2) # True, because 3 is greater than 2\nprint(3 >= 2) # True, because 3 is greater than 2\nprint(3 < 2) # False, because 3 is greater than 2\nprint(2 < 3) # True, because 2 is less than 3\nprint(2 <= 3) # True, because 2 is less than 3\nprint(3 == 2) # False, because 3 is not equal to 2\nprint(3 != 2) # True, because 3 is not equal to 2\nprint(len('mango') == len('avocado')) # False\nprint(len('mango') != len('avocado')) # True\nprint(len('mango') < len('avocado')) # True\nprint(len('milk') != len('meat')) # False\nprint(len('milk') == len('meat')) # True\nprint(len('tomato') == len('potato')) # True\nprint(len('python') > len('dragon')) # False\n\n# Boolean comparison\nprint('True == True: ', True == True)\nprint('True == False: ', True == False)\nprint('False == False:', False == False)\nprint('True and True: ', True and True)\nprint('True or False:', True or False)\n\n# Another way comparison\n# True - because the data values are the same\nprint('1 is 1', 1 is 1)\nprint('1 is not 2', 1 is not 2) # True - because 1 is not 2\nprint('A in Asabeneh', 'A' in 'Asabeneh') # True - A found in the string\nprint('B in Asabeneh', 'B' in 'Asabeneh') # False -there is no uppercase B\n# True - because coding for all has the word coding\nprint('coding' in 'coding for all')\nprint('a in an:', 'a' in 'an') # True\nprint('4 is 2 ** 2:', 4 is 2 ** 2) # True\n\nprint(3 > 2 and 4 > 3) # True - because both statements are true\nprint(3 > 2 and 4 < 3) # False - because the second statement is false\nprint(3 < 2 and 4 < 3) # False - because both statements are false\nprint(3 > 2 or 4 > 3) # True - because both statements are true\nprint(3 > 2 or 4 < 3) # True - because one of the statement is true\nprint(3 < 2 or 4 < 3) # False - because both statements are false\nprint(not 3 > 2) # False - because 3 > 2 is true, then not True gives False\nprint(not True) # False - Negation, the not operator turns true to false\nprint(not False) # True\nprint(not not True) # True\nprint(not not False) # False\n"
},
{
"path": "04_Day_Strings/04_strings.md",
"content": "
\n\n[<< Day 3](../03_Day_Operators/03_operators.md) | [Day 5 >>](../05_Day_Lists/05_lists.md)\n\n\n\n- [Day 4](#day-4)\n - [Strings](#strings)\n - [Creating a String](#creating-a-string)\n - [String Concatenation](#string-concatenation)\n - [Escape Sequences in Strings](#escape-sequences-in-strings)\n - [String formatting](#string-formatting)\n - [Old Style String Formatting (% Operator)](#old-style-string-formatting--operator)\n - [New Style String Formatting (str.format)](#new-style-string-formatting-strformat)\n - [String Interpolation / f-Strings (Python 3.6+)](#string-interpolation--f-strings-python-36)\n - [Python Strings as Sequences of Characters](#python-strings-as-sequences-of-characters)\n - [Unpacking Characters](#unpacking-characters)\n - [Accessing Characters in Strings by Index](#accessing-characters-in-strings-by-index)\n - [Slicing Python Strings](#slicing-python-strings)\n - [Reversing a String](#reversing-a-string)\n - [Skipping Characters While Slicing](#skipping-characters-while-slicing)\n - [String Methods](#string-methods)\n - [💻 Exercises - Day 4](#-exercises---day-4)\n\n# Day 4\n\n## Strings\n\nText is a string data type. Any data type written as text is a string. Any data under single, double or triple quote are strings. There are different string methods and built-in functions to deal with string data types. To check the length of a string use the len() method.\n\n### Creating a String\n\n```py\nletter = 'P' # A string could be a single character or a bunch of texts\nprint(letter) # P\nprint(len(letter)) # 1\ngreeting = 'Hello, World!' # String could be made using a single or double quote,\"Hello, World!\"\nprint(greeting) # Hello, World!\nprint(len(greeting)) # 13\nsentence = \"I hope you are enjoying 30 days of Python Challenge\"\nprint(sentence)\n```\n\nMultiline string is created by using triple single (''') or triple double quotes (\"\"\"). See the example below.\n\n```py\nmultiline_string = '''I am a teacher and enjoy teaching.\nI didn't find anything as rewarding as empowering people.\nThat is why I created 30 days of python.'''\nprint(multiline_string)\n\n# Another way of doing the same thing\nmultiline_string = \"\"\"I am a teacher and enjoy teaching.\nI didn't find anything as rewarding as empowering people.\nThat is why I created 30 days of python.\"\"\"\nprint(multiline_string)\n```\n\n### String Concatenation\n\nWe can connect strings together. Merging or connecting strings is called concatenation. See the example below:\n\n```py\nfirst_name = 'Asabeneh'\nlast_name = 'Yetayeh'\nspace = ' '\nfull_name = first_name + space + last_name\nprint(full_name) # Asabeneh Yetayeh\n# Checking the length of a string using len() built-in function\nprint(len(first_name)) # 8\nprint(len(last_name)) # 7\nprint(len(first_name) > len(last_name)) # True\nprint(len(full_name)) # 16\n```\n\n### Escape Sequences in Strings\n\nIn Python and other programming languages \\ followed by a character is an escape sequence. Let us see the most common escape characters:\n\n- \\n: new line\n- \\t: Tab means(8 spaces) \n- \\\\\\\\: Back slash\n- \\\\': Single quote (')\n- \\\\\": Double quote (\")\n\nNow, let us see the use of the above escape sequences with examples.\n\n```py\nprint('I hope everyone is enjoying the Python Challenge.\\nAre you ?') # line break\nprint('Days\\tTopics\\tExercises') # adding tab space or 4 spaces\nprint('Day 1\\t5\\t5')\nprint('Day 2\\t6\\t20')\nprint('Day 3\\t5\\t23')\nprint('Day 4\\t1\\t35')\nprint('This is a backslash symbol (\\\\)') # To write a backslash\nprint('In every programming language it starts with \\\"Hello, World!\\\"') # to write a double quote inside a single quote\n\n# output\nI hope every one is enjoying the Python Challenge.\nAre you ?\nDays Topics Exercises\nDay 1\t5\t 5\nDay 2\t6\t 20\nDay 3\t5\t 23\nDay 4\t1\t 35\nThis is a backslash symbol (\\)\nIn every programming language it starts with \"Hello, World!\"\n```\n\n### String formatting\n\n#### Old Style String Formatting (% Operator)\n\nIn Python there are many ways of formatting strings. In this section, we will cover some of them.\nThe \"%\" operator is used to format a set of variables enclosed in a \"tuple\" (a fixed size list), together with a format string, which contains normal text together with \"argument specifiers\", special symbols like \"%s\", \"%d\", \"%f\", \"%.number of digitsf\".\n\n- %s - String (or any object with a string representation, like numbers)\n- %d - Integers\n- %f - Floating point numbers\n- \"%.number of digitsf\" - Floating point numbers with fixed precision\n\n```py\n# Strings only\nfirst_name = 'Asabeneh'\nlast_name = 'Yetayeh'\nlanguage = 'Python'\nformated_string = 'I am %s %s. I teach %s' %(first_name, last_name, language)\nprint(formated_string)\n\n# Strings and numbers\nradius = 10\npi = 3.14\narea = pi * radius ** 2\nformated_string = 'The area of circle with a radius %d is %.2f.' %(radius, area) # 2 refers the 2 significant digits after the point\n\npython_libraries = ['Django', 'Flask', 'NumPy', 'Matplotlib','Pandas']\nformated_string = 'The following are python libraries:%s' % (python_libraries)\nprint(formated_string) # \"The following are python libraries:['Django', 'Flask', 'NumPy', 'Matplotlib','Pandas']\"\n```\n\n#### New Style String Formatting (str.format)\n\nThis format was introduced in Python version 3.\n\n```py\n\nfirst_name = 'Asabeneh'\nlast_name = 'Yetayeh'\nlanguage = 'Python'\nformated_string = 'I am {} {}. I teach {}'.format(first_name, last_name, language)\nprint(formated_string)\na = 4\nb = 3\n\nprint('{} + {} = {}'.format(a, b, a + b))\nprint('{} - {} = {}'.format(a, b, a - b))\nprint('{} * {} = {}'.format(a, b, a * b))\nprint('{} / {} = {:.2f}'.format(a, b, a / b)) # limits it to two digits after decimal\nprint('{} % {} = {}'.format(a, b, a % b))\nprint('{} // {} = {}'.format(a, b, a // b))\nprint('{} ** {} = {}'.format(a, b, a ** b))\n\n# output\n4 + 3 = 7\n4 - 3 = 1\n4 * 3 = 12\n4 / 3 = 1.33\n4 % 3 = 1\n4 // 3 = 1\n4 ** 3 = 64\n\n# Strings and numbers\nradius = 10\npi = 3.14\narea = pi * radius ** 2\nformated_string = 'The area of a circle with a radius {} is {:.2f}.'.format(radius, area) # 2 digits after decimal\nprint(formated_string)\n\n```\n\n#### String Interpolation / f-Strings (Python 3.6+)\n\nAnother new string formatting is string interpolation, f-strings. Strings start with f and we can inject the data in their corresponding positions.\n\n```py\na = 4\nb = 3\nprint(f'{a} + {b} = {a +b}')\nprint(f'{a} - {b} = {a - b}')\nprint(f'{a} * {b} = {a * b}')\nprint(f'{a} / {b} = {a / b:.2f}')\nprint(f'{a} % {b} = {a % b}')\nprint(f'{a} // {b} = {a // b}')\nprint(f'{a} ** {b} = {a ** b}')\n```\n\n### Python Strings as Sequences of Characters\n\nPython strings are sequences of characters, and share their basic methods of access with other Python ordered sequences of objects – lists and tuples. The simplest way of extracting single characters from strings (and individual members from any sequence) is to unpack them into corresponding variables.\n\n#### Unpacking Characters\n\n```\nlanguage = 'Python'\na,b,c,d,e,f = language # unpacking sequence characters into variables\nprint(a) # P\nprint(b) # y\nprint(c) # t\nprint(d) # h\nprint(e) # o\nprint(f) # n\n```\n\n#### Accessing Characters in Strings by Index\n\nIn programming counting starts from zero. Therefore the first letter of a string is at zero index and the last letter of a string is the length of a string minus one.\n\n\n\n```py\nlanguage = 'Python'\nfirst_letter = language[0]\nprint(first_letter) # P\nsecond_letter = language[1]\nprint(second_letter) # y\nlast_index = len(language) - 1\nlast_letter = language[last_index]\nprint(last_letter) # n\n```\n\nIf we want to start from right end we can use negative indexing. -1 is the last index.\n\n```py\nlanguage = 'Python'\nlast_letter = language[-1]\nprint(last_letter) # n\nsecond_last = language[-2]\nprint(second_last) # o\n```\n\n#### Slicing Python Strings\n\nIn python we can slice strings into substrings.\n\n```py\nlanguage = 'Python'\nfirst_three = language[0:3] # starts at zero index and up to 3 but not include 3\nprint(first_three) #Pyt\nlast_three = language[3:6]\nprint(last_three) # hon\n# Another way\nlast_three = language[-3:]\nprint(last_three) # hon\nlast_three = language[3:]\nprint(last_three) # hon\n```\n\n#### Reversing a String\n\nWe can easily reverse strings in python.\n\n```py\ngreeting = 'Hello, World!'\nprint(greeting[::-1]) # !dlroW ,olleH\n```\n\n#### Skipping Characters While Slicing\n\nIt is possible to skip characters while slicing by passing step argument to slice method.\n\n```py\nlanguage = 'Python'\npto = language[0:6:2] #\nprint(pto) # Pto\n```\n\n### String Methods\n\nThere are many string methods which allow us to format strings. See some of the string methods in the following example:\n\n- capitalize(): Converts the first character of the string to capital letter\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.capitalize()) # 'Thirty days of python'\n```\n\n- count(): returns occurrences of substring in string, count(substring, start=.., end=..). The start is a starting indexing for counting and end is the last index to count.\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.count('y')) # 3\nprint(challenge.count('y', 7, 14)) # 1, \nprint(challenge.count('th')) # 2`\n```\n\n- endswith(): Checks if a string ends with a specified ending\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.endswith('on')) # True\nprint(challenge.endswith('tion')) # False\n```\n\n- expandtabs(): Replaces tab character with spaces, default tab size is 8. It takes tab size argument\n\n```py\nchallenge = 'thirty\\tdays\\tof\\tpython'\nprint(challenge.expandtabs()) # 'thirty days of python'\nprint(challenge.expandtabs(10)) # 'thirty days of python'\n```\n\n- find(): Returns the index of the first occurrence of a substring, if not found returns -1\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.find('y')) # 5\nprint(challenge.find('th')) # 0\n```\n\n- rfind(): Returns the index of the last occurrence of a substring, if not found returns -1\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.rfind('y')) # 16\nprint(challenge.rfind('th')) # 17\n```\n\n- format(): formats string into a nicer output \n More about string formatting check this [link](https://www.programiz.com/python-programming/methods/string/format)\n\n```py\nfirst_name = 'Asabeneh'\nlast_name = 'Yetayeh'\nage = 250\njob = 'teacher'\ncountry = 'Finland'\nsentence = 'I am {} {}. I am a {}. I am {} years old. I live in {}.'.format(first_name, last_name, job, age, country)\nprint(sentence) # I am Asabeneh Yetayeh. I am 250 years old. I am a teacher. I live in Finland.\n\nradius = 10\npi = 3.14\narea = pi * radius ** 2\nresult = 'The area of a circle with radius {} is {}'.format(str(radius), str(area))\nprint(result) # The area of a circle with radius 10 is 314\n```\n\n- index(): Returns the lowest index of a substring, additional arguments indicate starting and ending index (default 0 and string length - 1). If the substring is not found it raises a valueError. \n\n```py\nchallenge = 'thirty days of python'\nsub_string = 'da'\nprint(challenge.index(sub_string)) # 7\nprint(challenge.index(sub_string, 9)) # error\n```\n\n- rindex(): Returns the highest index of a substring, additional arguments indicate starting and ending index (default 0 and string length - 1)\n\n```py\nchallenge = 'thirty days of python'\nsub_string = 'da'\nprint(challenge.rindex(sub_string)) # 7\nprint(challenge.rindex(sub_string, 9)) # error\nprint(challenge.rindex('on', 8)) # 19\n```\n\n- isalnum(): Checks alphanumeric character\n\n```py\nchallenge = 'ThirtyDaysPython'\nprint(challenge.isalnum()) # True\n\nchallenge = '30DaysPython'\nprint(challenge.isalnum()) # True\n\nchallenge = 'thirty days of python'\nprint(challenge.isalnum()) # False, space is not an alphanumeric character\n\nchallenge = 'thirty days of python 2019'\nprint(challenge.isalnum()) # False\n```\n\n- isalpha(): Checks if all string elements are alphabet characters (a-z and A-Z)\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.isalpha()) # False, space is once again excluded\nchallenge = 'ThirtyDaysPython'\nprint(challenge.isalpha()) # True\nnum = '123'\nprint(num.isalpha()) # False\n```\n\n- isdecimal(): Checks if all characters in a string are decimal (0-9)\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.isdecimal()) # False\nchallenge = '123'\nprint(challenge.isdecimal()) # True\nchallenge = '\\u00B2'\nprint(challenge.isdigit()) # True \nchallenge = '12 3'\nprint(challenge.isdecimal()) # False, space not allowed\n```\n\n- isdigit(): Checks if all characters in a string are numbers (0-9 and some other unicode characters for numbers)\n\n```py\nchallenge = 'Thirty'\nprint(challenge.isdigit()) # False\nchallenge = '30'\nprint(challenge.isdigit()) # True\nchallenge = '\\u00B2'\nprint(challenge.isdigit()) # True\n```\n\n- isnumeric(): Checks if all characters in a string are numbers or number related (just like isdigit(), just accepts more symbols, like ½)\n\n```py\nnum = '10'\nprint(num.isnumeric()) # True\nnum = '\\u00BD' # ½\nprint(num.isnumeric()) # True\nnum = '10.5'\nprint(num.isnumeric()) # False\n```\n\n- isidentifier(): Checks for a valid identifier - it checks if a string is a valid variable name\n\n```py\nchallenge = '30DaysOfPython'\nprint(challenge.isidentifier()) # False, because it starts with a number\nchallenge = 'thirty_days_of_python'\nprint(challenge.isidentifier()) # True\n```\n\n- islower(): Checks if all alphabet characters in the string are lowercase\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.islower()) # True\nchallenge = 'Thirty days of python'\nprint(challenge.islower()) # False\n```\n\n- isupper(): Checks if all alphabet characters in the string are uppercase\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.isupper()) # False\nchallenge = 'THIRTY DAYS OF PYTHON'\nprint(challenge.isupper()) # True\n```\n\n- join(): Returns a concatenated string\n\n```py\nweb_tech = ['HTML', 'CSS', 'JavaScript', 'React']\nresult = ' '.join(web_tech)\nprint(result) # 'HTML CSS JavaScript React'\n```\n\n```py\nweb_tech = ['HTML', 'CSS', 'JavaScript', 'React']\nresult = '# '.join(web_tech)\nprint(result) # 'HTML# CSS# JavaScript# React'\n```\n\n- strip(): Removes all given characters starting from the beginning and end of the string\n\n```py\nchallenge = 'thirty days of pythoonnn'\nprint(challenge.strip('noth')) # 'irty days of py'\n```\n\n- replace(): Replaces substring with a given string\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.replace('python', 'coding')) # 'thirty days of coding'\n```\n\n- split(): Splits the string, using given string or space as a separator\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.split()) # ['thirty', 'days', 'of', 'python']\nchallenge = 'thirty, days, of, python'\nprint(challenge.split(', ')) # ['thirty', 'days', 'of', 'python']\n```\n\n- title(): Returns a title cased string\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.title()) # Thirty Days Of Python\n```\n\n- swapcase(): Converts all uppercase characters to lowercase and all lowercase characters to uppercase characters\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.swapcase()) # THIRTY DAYS OF PYTHON\nchallenge = 'Thirty Days Of Python'\nprint(challenge.swapcase()) # tHIRTY dAYS oF pYTHON\n```\n\n- startswith(): Checks if String Starts with the Specified String\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.startswith('thirty')) # True\n\nchallenge = '30 days of python'\nprint(challenge.startswith('thirty')) # False\n```\n\n🌕 You are an extraordinary person and you have a remarkable potential. You have just completed day 4 challenges and you are four steps a head in to your way to greatness. Now do some exercises for your brain and muscles.\n\n## 💻 Exercises - Day 4\n\n1. Concatenate the string 'Thirty', 'Days', 'Of', 'Python' to a single string, 'Thirty Days Of Python'.\n2. Concatenate the string 'Coding', 'For' , 'All' to a single string, 'Coding For All'.\n3. Declare a variable named company and assign it to an initial value \"Coding For All\".\n4. Print the variable company using _print()_.\n5. Print the length of the company string using _len()_ method and _print()_.\n6. Change all the characters to uppercase letters using _upper()_ method.\n7. Change all the characters to lowercase letters using _lower()_ method.\n8. Use capitalize(), title(), swapcase() methods to format the value of the string _Coding For All_.\n9. Cut(slice) out the first word of _Coding For All_ string.\n10. Check if _Coding For All_ string contains a word Coding using the method index, find or other methods.\n11. Replace the word coding in the string 'Coding For All' to Python.\n12. Change \"Python for Everyone\" to \"Python for All\" using the replace method or other methods. \n13. Split the string 'Coding For All' using space as the separator (split()) .\n14. \"Facebook, Google, Microsoft, Apple, IBM, Oracle, Amazon\" split the string at the comma.\n15. What is the character at index 0 in the string _Coding For All_.\n16. What is the last index of the string _Coding For All_.\n17. What character is at index 10 in \"Coding For All\" string.\n18. Create an acronym or an abbreviation for the name 'Python For Everyone'.\n19. Create an acronym or an abbreviation for the name 'Coding For All'.\n20. Use index to determine the position of the first occurrence of C in Coding For All.\n21. Use index to determine the position of the first occurrence of F in Coding For All.\n22. Use rfind to determine the position of the last occurrence of l in Coding For All People.\n23. Use index or find to find the position of the first occurrence of the word 'because' in the following sentence: 'You cannot end a sentence with because because because is a conjunction'\n24. Use rindex to find the position of the last occurrence of the word because in the following sentence: 'You cannot end a sentence with because because because is a conjunction'\n25. Slice out the phrase 'because because because' in the following sentence: 'You cannot end a sentence with because because because is a conjunction'\n26. Find the position of the first occurrence of the word 'because' in the following sentence: 'You cannot end a sentence with because because because is a conjunction'\n27. Slice out the phrase 'because because because' in the following sentence: 'You cannot end a sentence with because because because is a conjunction'\n28. Does 'Coding For All' start with a substring _Coding_?\n29. Does 'Coding For All' end with a substring _coding_?\n30. ' Coding For All ' , remove the left and right trailing spaces in the given string.\n31. Which one of the following variables return True when we use the method isidentifier():\n - 30DaysOfPython\n - thirty_days_of_python\n32. The following list contains the names of some of python libraries: ['Django', 'Flask', 'Bottle', 'Pyramid', 'Falcon']. Join the list with a hash with space string.\n33. Use the new line escape sequence to separate the following sentences.\n ```py\n I am enjoying this challenge.\n I just wonder what is next.\n ```\n34. Use a tab escape sequence to write the following lines.\n ```py\n Name Age Country City\n Asabeneh 250 Finland Helsinki\n ```\n35. Use the string formatting method to display the following:\n\n```sh\nradius = 10\narea = 3.14 * radius ** 2\nThe area of a circle with radius 10 is 314 meters square.\n```\n\n36. Make the following using string formatting methods:\n\n```sh\n8 + 6 = 14\n8 - 6 = 2\n8 * 6 = 48\n8 / 6 = 1.33\n8 % 6 = 2\n8 // 6 = 1\n8 ** 6 = 262144\n```\n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 3](../03_Day_Operators/03_operators.md) | [Day 5 >>](../05_Day_Lists/05_lists.md)\n\n\n"
},
{
"path": "04_Day_Strings/day_4.py",
"content": "\n# Single line comment\nletter = 'P' # A string could be a single character or a bunch of texts\nprint(letter) # P\nprint(len(letter)) # 1\ngreeting = 'Hello, World!' # String could be a single or double quote,\"Hello, World!\"\nprint(greeting) # Hello, World!\nprint(len(greeting)) # 13\nsentence = \"I hope you are enjoying 30 days of python challenge\"\nprint(sentence)\n\n# Multiline String\nmultiline_string = '''I am a teacher and enjoy teaching.\nI didn't find anything as rewarding as empowering people.\nThat is why I created 30 days of python.'''\nprint(multiline_string)\n# Another way of doing the same thing\nmultiline_string = \"\"\"I am a teacher and enjoy teaching.\nI didn't find anything as rewarding as empowering people.\nThat is why I created 30 days of python.\"\"\"\nprint(multiline_string)\n\n# String Concatenation\nfirst_name = 'Asabeneh'\nlast_name = 'Yetayeh'\nspace = ' '\nfull_name = first_name + space + last_name\nprint(full_name) # Asabeneh Yetayeh\n# Checking length of a string using len() builtin function\nprint(len(first_name)) # 8\nprint(len(last_name)) # 7\nprint(len(first_name) > len(last_name)) # True\nprint(len(full_name)) # 15\n\n# Unpacking characters\nlanguage = 'Python'\na, b, c, d, e, f = language # unpacking sequence characters into variables\nprint(a) # P\nprint(b) # y\nprint(c) # t\nprint(d) # h\nprint(e) # o\nprint(f) # n\n\n# Accessing characters in strings by index\nlanguage = 'Python'\nfirst_letter = language[0]\nprint(first_letter) # P\nsecond_letter = language[1]\nprint(second_letter) # y\nlast_index = len(language) - 1\nlast_letter = language[last_index]\nprint(last_letter) # n\n\n# If we want to start from right end we can use negative indexing. -1 is the last index\nlanguage = 'Python'\nlast_letter = language[-1]\nprint(last_letter) # n\nsecond_last = language[-2]\nprint(second_last) # o\n\n# Slicing\n\nlanguage = 'Python'\n# starts at zero index and up to 3 but not include 3\nfirst_three = language[0:3]\nlast_three = language[3:6]\nprint(last_three) # hon\n# Another way\nlast_three = language[-3:]\nprint(last_three) # hon\nlast_three = language[3:]\nprint(last_three) # hon\n\n# Skipping character while splitting Python strings\nlanguage = 'Python'\npto = language[0:6:2]\nprint(pto) # pto\n\n# Escape sequence\nprint('I hope every one enjoying the python challenge.\\nDo you ?') # line break\nprint('Days\\tTopics\\tExercises')\nprint('Day 1\\t3\\t5')\nprint('Day 2\\t3\\t5')\nprint('Day 3\\t3\\t5')\nprint('Day 4\\t3\\t5')\nprint('This is a back slash symbol (\\\\)') # To write a back slash\nprint('In every programming language it starts with \\\"Hello, World!\\\"')\n\n# String Methods\n# capitalize(): Converts the first character the string to Capital Letter\n\nchallenge = 'thirty days of python'\nprint(challenge.capitalize()) # 'Thirty days of python'\n\n# count(): returns occurrences of substring in string, count(substring, start=.., end=..)\n\nchallenge = 'thirty days of python'\nprint(challenge.count('y')) # 3\nprint(challenge.count('y', 7, 14)) # 1\nprint(challenge.count('th')) # 2`\n\n# endswith(): Checks if a string ends with a specified ending\n\nchallenge = 'thirty days of python'\nprint(challenge.endswith('on')) # True\nprint(challenge.endswith('tion')) # False\n\n# expandtabs(): Replaces tab character with spaces, default tab size is 8. It takes tab size argument\n\nchallenge = 'thirty\\tdays\\tof\\tpython'\nprint(challenge.expandtabs()) # 'thirty days of python'\nprint(challenge.expandtabs(10)) # 'thirty days of python'\n\n# find(): Returns the index of first occurrence of substring\n\nchallenge = 'thirty days of python'\nprint(challenge.find('y')) # 5\nprint(challenge.find('th')) # 0\n\n# format()\tformats string into nicer output\nfirst_name = 'Asabeneh'\nlast_name = 'Yetayeh'\njob = 'teacher'\ncountry = 'Finland'\nsentence = 'I am {} {}. I am a {}. I live in {}.'.format(\n first_name, last_name, job, country)\nprint(sentence) # I am Asabeneh Yetayeh. I am a teacher. I live in Finland.\n\nradius = 10\npi = 3.14\narea = pi # radius ## 2\nresult = 'The area of circle with {} is {}'.format(str(radius), str(area))\nprint(result) # The area of circle with 10 is 314.0\n\n# index(): Returns the index of substring\nchallenge = 'thirty days of python'\nprint(challenge.find('y')) # 5\nprint(challenge.find('th')) # 0\n\n# isalnum(): Checks alphanumeric character\n\nchallenge = 'ThirtyDaysPython'\nprint(challenge.isalnum()) # True\n\nchallenge = '30DaysPython'\nprint(challenge.isalnum()) # True\n\nchallenge = 'thirty days of python'\nprint(challenge.isalnum()) # False\n\nchallenge = 'thirty days of python 2019'\nprint(challenge.isalnum()) # False\n\n# isalpha(): Checks if all characters are alphabets\n\nchallenge = 'thirty days of python'\nprint(challenge.isalpha()) # True\nnum = '123'\nprint(num.isalpha()) # False\n\n# isdecimal(): Checks Decimal Characters\n\nchallenge = 'thirty days of python'\nprint(challenge.find('y')) # 5\nprint(challenge.find('th')) # 0\n\n# isdigit(): Checks Digit Characters\n\nchallenge = 'Thirty'\nprint(challenge.isdigit()) # False\nchallenge = '30'\nprint(challenge.isdigit()) # True\n\n# isdecimal():Checks decimal characters\n\nnum = '10'\nprint(num.isdecimal()) # True\nnum = '10.5'\nprint(num.isdecimal()) # False\n\n\n# isidentifier():Checks for valid identifier means it check if a string is a valid variable name\n\nchallenge = '30DaysOfPython'\nprint(challenge.isidentifier()) # False, because it starts with a number\nchallenge = 'thirty_days_of_python'\nprint(challenge.isidentifier()) # True\n\n\n# islower():Checks if all alphabets in a string are lowercase\n\nchallenge = 'thirty days of python'\nprint(challenge.islower()) # True\nchallenge = 'Thirty days of python'\nprint(challenge.islower()) # False\n\n# isupper(): returns if all characters are uppercase characters\n\nchallenge = 'thirty days of python'\nprint(challenge.isupper()) # False\nchallenge = 'THIRTY DAYS OF PYTHON'\nprint(challenge.isupper()) # True\n\n\n# isnumeric():Checks numeric characters\n\nnum = '10'\nprint(num.isnumeric()) # True\nprint('ten'.isnumeric()) # False\n\n# join(): Returns a concatenated string\n\nweb_tech = ['HTML', 'CSS', 'JavaScript', 'React']\nresult = '#, '.join(web_tech)\nprint(result) # 'HTML# CSS# JavaScript# React'\n\n# strip(): Removes both leading and trailing characters\n\nchallenge = ' thirty days of python '\nprint(challenge.strip('y')) # 5\n\n# replace(): Replaces substring inside\n\nchallenge = 'thirty days of python'\nprint(challenge.replace('python', 'coding')) # 'thirty days of coding'\n\n# split():Splits String from Left\n\nchallenge = 'thirty days of python'\nprint(challenge.split()) # ['thirty', 'days', 'of', 'python']\n\n# title(): Returns a Title Cased String\n\nchallenge = 'thirty days of python'\nprint(challenge.title()) # Thirty Days Of Python\n\n# swapcase(): Checks if String Starts with the Specified String\n\nchallenge = 'thirty days of python'\nprint(challenge.swapcase()) # THIRTY DAYS OF PYTHON\nchallenge = 'Thirty Days Of Python'\nprint(challenge.swapcase()) # tHIRTY dAYS oF pYTHON\n\n# startswith(): Checks if String Starts with the Specified String\n\nchallenge = 'thirty days of python'\nprint(challenge.startswith('thirty')) # True\nchallenge = '30 days of python'\nprint(challenge.startswith('thirty')) # False\n"
},
{
"path": "05_Day_Lists/05_lists.md",
"content": "
\n\n[<< Day 4](../04_Day_Strings/04_strings.md) | [Day 6 >>](../06_Day_Tuples/06_tuples.md)\n\n\n\n- [Day 5](#day-5)\n - [Lists](#lists)\n - [How to Create a List](#how-to-create-a-list)\n - [Accessing List Items Using Positive Indexing](#accessing-list-items-using-positive-indexing)\n - [Accessing List Items Using Negative Indexing](#accessing-list-items-using-negative-indexing)\n - [Unpacking List Items](#unpacking-list-items)\n - [Slicing Items from a List](#slicing-items-from-a-list)\n - [Modifying Lists](#modifying-lists)\n - [Checking Items in a List](#checking-items-in-a-list)\n - [Adding Items to a List](#adding-items-to-a-list)\n - [Inserting Items into a List](#inserting-items-into-a-list)\n - [Removing Items from a List](#removing-items-from-a-list)\n - [Removing Items Using Pop](#removing-items-using-pop)\n - [Removing Items Using Del](#removing-items-using-del)\n - [Clearing List Items](#clearing-list-items)\n - [Copying a List](#copying-a-list)\n - [Joining Lists](#joining-lists)\n - [Counting Items in a List](#counting-items-in-a-list)\n - [Finding Index of an Item](#finding-index-of-an-item)\n - [Reversing a List](#reversing-a-list)\n - [Sorting List Items](#sorting-list-items)\n - [💻 Exercises: Day 5](#-exercises-day-5)\n - [Exercises: Level 1](#exercises-level-1)\n - [Exercises: Level 2](#exercises-level-2)\n\n# Day 5\n\n## Lists\n\nThere are four collection data types in Python :\n\n- List: is a collection which is ordered and changeable(modifiable). Allows duplicate members.\n- Tuple: is a collection which is ordered and unchangeable or unmodifiable(immutable). Allows duplicate members.\n- Set: is a collection which is unordered, un-indexed and unmodifiable, but we can add new items to the set. Duplicate members are not allowed.\n- Dictionary: is a collection which is unordered, changeable(modifiable) and indexed. No duplicate members.\n\nA list is collection of different data types which is ordered and modifiable(mutable). A list can be empty or it may have different data type items.\n\n### How to Create a List\n\nIn Python we can create lists in two ways:\n\n- Using list built-in function\n\n```py\n# syntax\nlst = list()\n```\n\n```py\nempty_list = list() # this is an empty list, no item in the list\nprint(len(empty_list)) # 0\n```\n\n- Using square brackets, []\n\n```py\n# syntax\nlst = []\n```\n\n```py\nempty_list = [] # this is an empty list, no item in the list\nprint(len(empty_list)) # 0\n```\n\nLists with initial values. We use _len()_ to find the length of a list.\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon'] # list of fruits\nvegetables = ['Tomato', 'Potato', 'Cabbage','Onion', 'Carrot'] # list of vegetables\nanimal_products = ['milk', 'meat', 'butter', 'yoghurt'] # list of animal products\nweb_techs = ['HTML', 'CSS', 'JS', 'React','Redux', 'Node', 'MongDB'] # list of web technologies\ncountries = ['Finland', 'Estonia', 'Denmark', 'Sweden', 'Norway'] \n\n# Print the lists and its length\nprint('Fruits:', fruits)\nprint('Number of fruits:', len(fruits))\nprint('Vegetables:', vegetables)\nprint('Number of vegetables:', len(vegetables))\nprint('Animal products:',animal_products)\nprint('Number of animal products:', len(animal_products))\nprint('Web technologies:', web_techs)\nprint('Number of web technologies:', len(web_techs))\nprint('Countries:', countries)\nprint('Number of countries:', len(countries))\n```\n\n```sh\noutput\nFruits: ['banana', 'orange', 'mango', 'lemon']\nNumber of fruits: 4\nVegetables: ['Tomato', 'Potato', 'Cabbage', 'Onion', 'Carrot']\nNumber of vegetables: 5\nAnimal products: ['milk', 'meat', 'butter', 'yoghurt']\nNumber of animal products: 4\nWeb technologies: ['HTML', 'CSS', 'JS', 'React', 'Redux', 'Node', 'MongDB']\nNumber of web technologies: 7\nCountries: ['Finland', 'Estonia', 'Denmark', 'Sweden', 'Norway']\nNumber of countries: 5\n```\n\n- Lists can have items of different data types\n\n```py\n lst = ['Asabeneh', 250, True, {'country':'Finland', 'city':'Helsinki'}] # list containing different data types\n```\n\n### Accessing List Items Using Positive Indexing\n\nWe access each item in a list using their index. A list index starts from 0. The picture below shows clearly where the index starts\n\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfirst_fruit = fruits[0] # we are accessing the first item using its index\nprint(first_fruit) # banana\nsecond_fruit = fruits[1]\nprint(second_fruit) # orange\nlast_fruit = fruits[3]\nprint(last_fruit) # lemon\n# Last index\nlast_index = len(fruits) - 1\nlast_fruit = fruits[last_index]\n```\n\n### Accessing List Items Using Negative Indexing\n\nNegative indexing means beginning from the end, -1 refers to the last item, -2 refers to the second last item.\n\n\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfirst_fruit = fruits[-4]\nlast_fruit = fruits[-1]\nsecond_last = fruits[-2]\nprint(first_fruit) # banana\nprint(last_fruit) # lemon\nprint(second_last) # mango\n```\n\n### Unpacking List Items\n\n```py\nlst = ['item1','item2','item3', 'item4', 'item5']\nfirst_item, second_item, third_item, *rest = lst\nprint(first_item) # item1\nprint(second_item) # item2\nprint(third_item) # item3\nprint(rest) # ['item4', 'item5']\n\n```\n\n```py\n# First Example\nfruits = ['banana', 'orange', 'mango', 'lemon','lime','apple']\nfirst_fruit, second_fruit, third_fruit, *rest = fruits \nprint(first_fruit) # banana\nprint(second_fruit) # orange\nprint(third_fruit) # mango\nprint(rest) # ['lemon','lime','apple']\n# Second Example about unpacking list\nfirst, second, third,*rest, tenth = [1,2,3,4,5,6,7,8,9,10]\nprint(first) # 1\nprint(second) # 2\nprint(third) # 3\nprint(rest) # [4,5,6,7,8,9]\nprint(tenth) # 10\n# Third Example about unpacking list\ncountries = ['Germany', 'France','Belgium','Sweden','Denmark','Finland','Norway','Iceland','Estonia']\ngr, fr, bg, sw, *scandic, es = countries\nprint(gr) \nprint(fr)\nprint(bg)\nprint(sw)\nprint(scandic)\nprint(es)\n```\n\n### Slicing Items from a List\n\n- Positive Indexing: We can specify a range of positive indexes by specifying the start, end and step, the return value will be a new list. (default values for start = 0, end = len(lst) - 1 (last item), step = 1)\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nall_fruits = fruits[0:4] # it returns all the fruits\n# this will also give the same result as the one above\nall_fruits = fruits[0:] # if we don't set where to stop it takes all the rest\norange_and_mango = fruits[1:3] # it does not include the first index\norange_mango_lemon = fruits[1:]\norange_and_lemon = fruits[::2] # here we used a 3rd argument, step. It will take every 2cnd item - ['banana', 'mango']\n```\n\n- Negative Indexing: We can specify a range of negative indexes by specifying the start, end and step, the return value will be a new list.\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nall_fruits = fruits[-4:] # it returns all the fruits\norange_and_mango = fruits[-3:-1] # it does not include the last index,['orange', 'mango']\norange_mango_lemon = fruits[-3:] # this will give starting from -3 to the end,['orange', 'mango', 'lemon']\nreverse_fruits = fruits[::-1] # a negative step will take the list in reverse order,['lemon', 'mango', 'orange', 'banana']\n```\n\n### Modifying Lists\n\nList is a mutable or modifiable ordered collection of items. Lets modify the fruit list.\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits[0] = 'avocado'\nprint(fruits) # ['avocado', 'orange', 'mango', 'lemon']\nfruits[1] = 'apple'\nprint(fruits) # ['avocado', 'apple', 'mango', 'lemon']\nlast_index = len(fruits) - 1\nfruits[last_index] = 'lime'\nprint(fruits) # ['avocado', 'apple', 'mango', 'lime']\n```\n\n### Checking Items in a List\n\nChecking an item if it is a member of a list using *in* operator. See the example below.\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\ndoes_exist = 'banana' in fruits\nprint(does_exist) # True\ndoes_exist = 'lime' in fruits\nprint(does_exist) # False\n```\n\n### Adding Items to a List\n\nTo add item to the end of an existing list we use the method *append()*.\n\n```py\n# syntax\nlst = list()\nlst.append(item)\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits.append('apple')\nprint(fruits) # ['banana', 'orange', 'mango', 'lemon', 'apple']\nfruits.append('lime') # ['banana', 'orange', 'mango', 'lemon', 'apple', 'lime']\nprint(fruits)\n```\n\n### Inserting Items into a List\n\nWe can use *insert()* method to insert a single item at a specified index in a list. Note that other items are shifted to the right. The *insert()* methods takes two arguments:index and an item to insert.\n\n```py\n# syntax\nlst = ['item1', 'item2']\nlst.insert(index, item)\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits.insert(2, 'apple') # insert apple between orange and mango\nprint(fruits) # ['banana', 'orange', 'apple', 'mango', 'lemon']\nfruits.insert(3, 'lime') # ['banana', 'orange', 'apple', 'lime', 'mango', 'lemon']\nprint(fruits)\n```\n\n### Removing Items from a List\n\nThe remove method removes a specified item from a list\n\n```py\n# syntax\nlst = ['item1', 'item2']\nlst.remove(item)\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon', 'banana']\nfruits.remove('banana')\nprint(fruits) # ['orange', 'mango', 'lemon', 'banana'] - this method removes the first occurrence of the item in the list\nfruits.remove('lemon')\nprint(fruits) # ['orange', 'mango', 'banana']\n```\n\n### Removing Items Using Pop\n\nThe *pop()* method removes the specified index, (or the last item if index is not specified):\n\n```py\n# syntax\nlst = ['item1', 'item2']\nlst.pop() # last item\nlst.pop(index)\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits.pop()\nprint(fruits) # ['banana', 'orange', 'mango']\n\nfruits.pop(0)\nprint(fruits) # ['orange', 'mango']\n```\n\n### Removing Items Using Del\n\nThe *del* keyword removes the specified index and it can also be used to delete items within index range. It can also delete the list completely\n\n```py\n# syntax\nlst = ['item1', 'item2']\ndel lst[index] # only a single item\ndel lst # to delete the list completely\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon', 'kiwi', 'lime']\ndel fruits[0]\nprint(fruits) # ['orange', 'mango', 'lemon', 'kiwi', 'lime']\ndel fruits[1]\nprint(fruits) # ['orange', 'lemon', 'kiwi', 'lime']\ndel fruits[1:3] # this deletes items between given indexes, so it does not delete the item with index 3!\nprint(fruits) # ['orange', 'lime']\ndel fruits\nprint(fruits) # This should give: NameError: name 'fruits' is not defined\n```\n\n### Clearing List Items\n\nThe *clear()* method empties the list:\n\n```py\n# syntax\nlst = ['item1', 'item2']\nlst.clear()\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits.clear()\nprint(fruits) # []\n```\n\n### Copying a List\n\nIt is possible to copy a list by reassigning it to a new variable in the following way: list2 = list1. Now, list2 is a reference of list1, any changes we make in list2 will also modify the original, list1. But there are lots of case in which we do not like to modify the original instead we like to have a different copy. One of way of avoiding the problem above is using _copy()_.\n\n```py\n# syntax\nlst = ['item1', 'item2']\nlst_copy = lst.copy()\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits_copy = fruits.copy()\nprint(fruits_copy) # ['banana', 'orange', 'mango', 'lemon']\n```\n\n### Joining Lists\n\nThere are several ways to join, or concatenate, two or more lists in Python.\n\n- Plus Operator (+)\n\n```py\n# syntax\nlist3 = list1 + list2\n```\n\n```py\npositive_numbers = [1, 2, 3, 4, 5]\nzero = [0]\nnegative_numbers = [-5,-4,-3,-2,-1]\nintegers = negative_numbers + zero + positive_numbers\nprint(integers) # [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5]\nfruits = ['banana', 'orange', 'mango', 'lemon']\nvegetables = ['Tomato', 'Potato', 'Cabbage', 'Onion', 'Carrot']\nfruits_and_vegetables = fruits + vegetables\nprint(fruits_and_vegetables ) # ['banana', 'orange', 'mango', 'lemon', 'Tomato', 'Potato', 'Cabbage', 'Onion', 'Carrot']\n```\n\n- Joining using extend() method\n The *extend()* method allows to append list in a list. See the example below.\n\n```py\n# syntax\nlist1 = ['item1', 'item2']\nlist2 = ['item3', 'item4', 'item5']\nlist1.extend(list2) # ['item1', 'item2', 'item3', 'item4', 'item5']\n```\n\n```py\nnum1 = [0, 1, 2, 3]\nnum2= [4, 5, 6]\nnum1.extend(num2)\nprint('Numbers:', num1) # Numbers: [0, 1, 2, 3, 4, 5, 6]\nnegative_numbers = [-5,-4,-3,-2,-1]\npositive_numbers = [1, 2, 3,4,5]\nzero = [0]\n\nnegative_numbers.extend(zero)\nnegative_numbers.extend(positive_numbers)\nprint('Integers:', negative_numbers) # Integers: [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5]\nfruits = ['banana', 'orange', 'mango', 'lemon']\nvegetables = ['Tomato', 'Potato', 'Cabbage', 'Onion', 'Carrot']\nfruits.extend(vegetables)\nprint('Fruits and vegetables:', fruits ) # Fruits and vegetables: ['banana', 'orange', 'mango', 'lemon', 'Tomato', 'Potato', 'Cabbage', 'Onion', 'Carrot']\n```\n\n### Counting Items in a List\n\nThe *count()* method returns the number of times an item appears in a list:\n\n```py\n# syntax\nlst = ['item1', 'item2']\nlst.count(item)\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nprint(fruits.count('orange')) # 1\nages = [22, 19, 24, 25, 26, 24, 25, 24]\nprint(ages.count(24)) # 3\n```\n\n### Finding Index of an Item\n\nThe *index()* method returns the index of an item in the list:\n\n```py\n# syntax\nlst = ['item1', 'item2']\nlst.index(item)\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nprint(fruits.index('orange')) # 1\nages = [22, 19, 24, 25, 26, 24, 25, 24]\nprint(ages.index(24)) # 2, the first occurrence\n```\n\n### Reversing a List\n\nThe *reverse()* method reverses the order of a list.\n\n```py\n# syntax\nlst = ['item1', 'item2']\nlst.reverse()\n\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits.reverse()\nprint(fruits) # ['lemon', 'mango', 'orange', 'banana']\nages = [22, 19, 24, 25, 26, 24, 25, 24]\nages.reverse()\nprint(ages) # [24, 25, 24, 26, 25, 24, 19, 22]\n```\n\n### Sorting List Items\n\nTo sort lists we can use _sort()_ method or _sorted()_ built-in functions. The _sort()_ method reorders the list items in ascending order and modifies the original list. If an argument of _sort()_ method reverse is equal to true, it will arrange the list in descending order.\n\n- sort(): this method modifies the original list\n\n ```py\n # syntax\n lst = ['item1', 'item2']\n lst.sort() # ascending\n lst.sort(reverse=True) # descending\n ```\n\n **Example:**\n\n ```py\n fruits = ['banana', 'orange', 'mango', 'lemon']\n fruits.sort()\n print(fruits) # sorted in alphabetical order, ['banana', 'lemon', 'mango', 'orange']\n fruits.sort(reverse=True)\n print(fruits) # ['orange', 'mango', 'lemon', 'banana']\n ages = [22, 19, 24, 25, 26, 24, 25, 24]\n ages.sort()\n print(ages) # [19, 22, 24, 24, 24, 25, 25, 26]\n \n ages.sort(reverse=True)\n print(ages) # [26, 25, 25, 24, 24, 24, 22, 19]\n ```\n\n sorted(): returns the ordered list without modifying the original list\n **Example:**\n\n ```py\n fruits = ['banana', 'orange', 'mango', 'lemon']\n print(sorted(fruits)) # ['banana', 'lemon', 'mango', 'orange']\n # Reverse order\n fruits = ['banana', 'orange', 'mango', 'lemon']\n fruits = sorted(fruits,reverse=True)\n print(fruits) # ['orange', 'mango', 'lemon', 'banana']\n ```\n\n🌕 You are diligent and you have already achieved quite a lot. You have just completed day 5 challenges and you are 5 steps a head in to your way to greatness. Now do some exercises for your brain and muscles.\n\n## 💻 Exercises: Day 5\n\n### Exercises: Level 1\n\n1. Declare an empty list\n2. Declare a list with more than 5 items\n3. Find the length of your list\n4. Get the first item, the middle item and the last item of the list\n5. Declare a list called mixed_data_types, put your(name, age, height, marital status, address)\n6. Declare a list variable named it_companies and assign initial values Facebook, Google, Microsoft, Apple, IBM, Oracle and Amazon.\n7. Print the list using _print()_\n8. Print the number of companies in the list\n9. Print the first, middle and last company\n10. Print the list after modifying one of the companies\n11. Add an IT company to it_companies\n12. Insert an IT company in the middle of the companies list\n13. Change one of the it_companies names to uppercase (IBM excluded!)\n14. Join the it_companies with a string '#; '\n15. Check if a certain company exists in the it_companies list.\n16. Sort the list using sort() method\n17. Reverse the list in descending order using reverse() method\n18. Slice out the first 3 companies from the list\n19. Slice out the last 3 companies from the list\n20. Slice out the middle IT company or companies from the list\n21. Remove the first IT company from the list\n22. Remove the middle IT company or companies from the list\n23. Remove the last IT company from the list\n24. Remove all IT companies from the list\n25. Destroy the IT companies list\n26. Join the following lists:\n\n ```py\n front_end = ['HTML', 'CSS', 'JS', 'React', 'Redux']\n back_end = ['Node','Express', 'MongoDB']\n ```\n\n27. After joining the lists in question 26. Copy the joined list and assign it to a variable full_stack, then insert Python and SQL after Redux.\n\n### Exercises: Level 2\n\n1. The following is a list of 10 students ages:\n\n```sh\nages = [19, 22, 19, 24, 20, 25, 26, 24, 25, 24]\n```\n\n- Sort the list and find the min and max age\n- Add the min age and the max age again to the list\n- Find the median age (one middle item or two middle items divided by two)\n- Find the average age (sum of all items divided by their number )\n- Find the range of the ages (max minus min)\n- Compare the value of (min - average) and (max - average), use _abs()_ method\n\n1. Find the middle country(ies) in the [countries list](https://github.com/Asabeneh/30-Days-Of-Python/tree/master/data/countries.py)\n1. Divide the countries list into two equal lists if it is even if not one more country for the first half.\n1. ['China', 'Russia', 'USA', 'Finland', 'Sweden', 'Norway', 'Denmark']. Unpack the first three countries and the rest as scandic countries.\n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 4](../04_Day_Strings/04_strings.md) | [Day 6 >>](../06_Day_Tuples/06_tuples.md)\n"
},
{
"path": "05_Day_Lists/day_5.py",
"content": "empty_list = list() # this is an empty list, no item in the list\nprint(len(empty_list)) # 0\n\n# list of fruits\nfruits = ['banana', 'orange', 'mango', 'lemon']\nvegetables = ['Tomato', 'Potato', 'Cabbage',\n 'Onion', 'Carrot'] # list of vegetables\nanimal_products = ['milk', 'meat', 'butter',\n 'yoghurt'] # list of animal products\nweb_techs = ['HTML', 'CSS', 'JS', 'React', 'Redux',\n 'Node', 'MongDB'] # list of web technologies\ncountries = ['Finland', 'Estonia', 'Denmark', 'Sweden', 'Norway']\n\n# Print the lists and it length\nprint('Fruits:', fruits)\nprint('Number of fruits:', len(fruits))\nprint('Vegetables:', vegetables)\nprint('Number of vegetables:', len(vegetables))\nprint('Animal products:', animal_products)\nprint('Number of animal products:', len(animal_products))\nprint('Web technologies:', web_techs)\nprint('Number of web technologies:', len(web_techs))\nprint('Number of countries:', len(countries))\n\n# Modifying list\n\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfirst_fruit = fruits[0] # we are accessing the first item using its index\nprint(first_fruit) # banana\nsecond_fruit = fruits[1]\nprint(second_fruit) # orange\nlast_fruit = fruits[3]\nprint(last_fruit) # lemon\n# Last index\nlast_index = len(fruits) - 1\nlast_fruit = fruits[last_index]\n\n# Accessing itmes\nfruits = ['banana', 'orange', 'mango', 'lemon']\nlast_fruit = fruits[-1]\nsecond_last = fruits[-2]\nprint(last_fruit) # lemon\nprint(second_last) # mango\n\n# Slicing items\nfruits = ['banana', 'orange', 'mango', 'lemon']\nall_fruits = fruits[0:4] # it returns all the fruits\n# this is also give the same result as the above\nall_fruits = fruits[0:] # if we don't set where to stop it takes all the rest\norange_and_mango = fruits[1:3] # it does not include the end index\norange_mango_lemon = fruits[1:]\n\nfruits = ['banana', 'orange', 'mango', 'lemon']\nall_fruits = fruits[-4:] # it returns all the fruits\n# this is also give the same result as the above\norange_and_mango = fruits[-3:-1] # it does not include the end index\norange_mango_lemon = fruits[-3:]\n\n\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits[0] = 'Avocado'\nprint(fruits) # ['avocado', 'orange', 'mango', 'lemon']\nfruits[1] = 'apple'\nprint(fruits) # ['avocado', 'apple', 'mango', 'lemon']\nlast_index = len(fruits)\nfruits[last_index] = 'lime'\nprint(fruits) # ['avocado', 'apple', 'mango', 'lime']\n\n# checking items\nfruits = ['banana', 'orange', 'mango', 'lemon']\ndoes_exist = 'banana' in fruits\nprint(does_exist) # True\ndoes_exist = 'lime' in fruits\nprint(does_exist) # False\n\n# Append\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits.append('apple')\nprint(fruits) # ['banana', 'orange', 'mango', 'lemon', 'apple']\n# ['banana', 'orange', 'mango', 'lemon', 'apple', 'lime]\nfruits.append('lime')\nprint(fruits)\n\n# insert\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits.insert(2, 'apple') # insert apple between orange and mango\nprint(fruits) # ['banana', 'orange', 'apple', 'mango', 'lemon']\n# ['banana', 'orange', 'apple', 'mango', 'lime','lemon',]\nfruits.list(3, 'lime')\nprint(fruits)\n\n# remove\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits.remove('banana')\nprint(fruits) # ['orange', 'mango', 'lemon']\nfruits.remove('lemon')\nprint(fruits) # ['orange', 'mango']\n\n# pop\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits.remove()\nprint(fruits) # ['banana', 'orange', 'mango']\n\nfruits.remove(0)\nprint(fruits) # ['orange', 'mango']\n\n# del\nfruits = ['banana', 'orange', 'mango', 'lemon']\ndel fruits[0]\nprint(fruits) # ['orange', 'mango', 'lemon']\n\ndel fruits[1]\nprint(fruits) # ['orange', 'lemon']\ndel fruits\nprint(fruits) # This should give: NameError: name 'fruits' is not defined\n\n# clear\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits.clear()\nprint(fruits) # []\n\n# copying a lits\n\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits_copy = fruits.copy()\nprint(fruits_copy) # ['banana', 'orange', 'mango', 'lemon']\n\n# join\npositive_numbers = [1, 2, 3, 4, 5]\nzero = [0]\nnegative_numbers = [-5, -4, -3, -2, -1]\nintegers = negative_numbers + zero + positive_numbers\nprint(integers)\nfruits = ['banana', 'orange', 'mango', 'lemon']\nvegetables = ['Tomato', 'Potato', 'Cabbage', 'Onion', 'Carrot']\nfruits_and_vegetables = fruits + vegetables\nprint(fruits_and_vegetables)\n\n# join with extend\nnum1 = [0, 1, 2, 3]\nnum2 = [4, 5, 6]\nnum1.extend(num2)\nprint('Numbers:', num1)\nnegative_numbers = [-5, -4, -3, -2, -1]\npositive_numbers = [1, 2, 3, 4, 5]\nzero = [0]\n\nnegative_numbers.extend(zero)\nnegative_numbers.extend(positive_numbers)\nprint('Integers:', negative_numbers)\nfruits = ['banana', 'orange', 'mango', 'lemon']\nvegetables = ['Tomato', 'Potato', 'Cabbage', 'Onion', 'Carrot']\nfruits.extend(vegetables)\nprint('Fruits and vegetables:', fruits)\n\n# count\nfruits = ['banana', 'orange', 'mango', 'lemon']\nprint(fruits.count('orange')) # 1\nages = [22, 19, 24, 25, 26, 24, 25, 24]\nprint(ages.count(24)) # 3\n\n# index\nfruits = ['banana', 'orange', 'mango', 'lemon']\nprint(fruits.index('orange')) # 1\nages = [22, 19, 24, 25, 26, 24, 25, 24]\nprint(ages.index(24))\n# Reverse\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits.reverse()\nprint(fruits.reverse())\nages = [22, 19, 24, 25, 26, 24, 25, 24]\nages.reverse()\nprint(ages.reverse())\n\n# sort\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits.sort()\nprint(fruits)\nfruits.sort(reverse=True)\nprint(fruits)\nages = [22, 19, 24, 25, 26, 24, 25, 24]\nages.sort()\nprint(ages)\nages.sort(reverse=True)\nprint(ages)\n"
},
{
"path": "06_Day_Tuples/06_tuples.md",
"content": "
\n\n[<< Day 5](../05_Day_Lists/05_lists.md) | [Day 7 >>](../07_Day_Sets/07_sets.md)\n\n\n\n- [Day 6:](#day-6)\n - [Tuples](#tuples)\n - [Creating a Tuple](#creating-a-tuple)\n - [Tuple length](#tuple-length)\n - [Accessing Tuple Items](#accessing-tuple-items)\n - [Slicing tuples](#slicing-tuples)\n - [Changing Tuples to Lists](#changing-tuples-to-lists)\n - [Checking an Item in a Tuple](#checking-an-item-in-a-tuple)\n - [Joining Tuples](#joining-tuples)\n - [Deleting Tuples](#deleting-tuples)\n - [💻 Exercises: Day 6](#-exercises-day-6)\n - [Exercises: Level 1](#exercises-level-1)\n - [Exercises: Level 2](#exercises-level-2)\n\n# Day 6:\n\n## Tuples\n\nA tuple is a collection of different data types which is ordered and unchangeable (immutable). Tuples are written with round brackets, (). Once a tuple is created, we cannot change its values. We cannot use add, insert, remove methods in a tuple because it is not modifiable (mutable). Unlike list, tuple has few methods. Methods related to tuples:\n\n- tuple(): to create an empty tuple\n- count(): to count the number of a specified item in a tuple\n- index(): to find the index of a specified item in a tuple\n- `+` operator: to join two or more tuples and to create a new tuple\n\n### Creating a Tuple\n\n- Empty tuple: Creating an empty tuple\n \n ```py\n # syntax\n empty_tuple = ()\n # or using the tuple constructor\n empty_tuple = tuple()\n ```\n\n- Tuple with initial values\n \n ```py\n # syntax\n tpl = ('item1', 'item2','item3')\n ```\n\n ```py\n fruits = ('banana', 'orange', 'mango', 'lemon')\n ```\n\n### Tuple length\n\nWe use the _len()_ method to get the length of a tuple.\n\n```py\n# syntax\ntpl = ('item1', 'item2', 'item3')\nlen(tpl)\n```\n\n### Accessing Tuple Items\n\n- Positive Indexing\n Similar to the list data type we use positive or negative indexing to access tuple items.\n \n\n ```py\n # Syntax\n tpl = ('item1', 'item2', 'item3')\n first_item = tpl[0]\n second_item = tpl[1]\n ```\n\n ```py\n fruits = ('banana', 'orange', 'mango', 'lemon')\n first_fruit = fruits[0]\n second_fruit = fruits[1]\n last_index =len(fruits) - 1\n last_fruit = fruits[last_index]\n ```\n\n- Negative indexing\n Negative indexing means beginning from the end, -1 refers to the last item, -2 refers to the second last and the negative of the list/tuple length refers to the first item.\n \n\n ```py\n # Syntax\n tpl = ('item1', 'item2', 'item3','item4')\n first_item = tpl[-4]\n second_item = tpl[-3]\n ```\n\n ```py\n fruits = ('banana', 'orange', 'mango', 'lemon')\n first_fruit = fruits[-4]\n second_fruit = fruits[-3]\n last_fruit = fruits[-1]\n ```\n\n### Slicing tuples\n\nWe can slice out a sub-tuple by specifying a range of indexes where to start and where to end in the tuple, the return value will be a new tuple with the specified items.\n\n- Range of Positive Indexes\n\n ```py\n # Syntax\n tpl = ('item1', 'item2', 'item3','item4')\n all_items = tpl[0:4] # all items\n all_items = tpl[0:] # all items\n middle_two_items = tpl[1:3] # does not include item at index 3\n ```\n\n ```py\n fruits = ('banana', 'orange', 'mango', 'lemon')\n all_fruits = fruits[0:4] # all items\n all_fruits= fruits[0:] # all items\n orange_mango = fruits[1:3] # doesn't include item at index 3\n orange_to_the_rest = fruits[1:]\n ```\n\n- Range of Negative Indexes\n\n ```py\n # Syntax\n tpl = ('item1', 'item2', 'item3','item4')\n all_items = tpl[-4:] # all items\n middle_two_items = tpl[-3:-1] # does not include item at index 3 (-1)\n ```\n\n ```py\n fruits = ('banana', 'orange', 'mango', 'lemon')\n all_fruits = fruits[-4:] # all items\n orange_mango = fruits[-3:-1] # doesn't include item at index 3\n orange_to_the_rest = fruits[-3:]\n ```\n\n### Changing Tuples to Lists\n\nWe can change tuples to lists and lists to tuples. Tuple is immutable if we want to modify a tuple we should change it to a list.\n\n```py\n# Syntax\ntpl = ('item1', 'item2', 'item3','item4')\nlst = list(tpl)\n```\n\n```py\nfruits = ('banana', 'orange', 'mango', 'lemon')\nfruits = list(fruits)\nfruits[0] = 'apple'\nprint(fruits) # ['apple', 'orange', 'mango', 'lemon']\nfruits = tuple(fruits)\nprint(fruits) # ('apple', 'orange', 'mango', 'lemon')\n```\n\n### Checking an Item in a Tuple\n\nWe can check if an item exists or not in a tuple using _in_, it returns a boolean.\n\n```py\n# Syntax\ntpl = ('item1', 'item2', 'item3','item4')\n'item2' in tpl # True\n```\n\n```py\nfruits = ('banana', 'orange', 'mango', 'lemon')\nprint('orange' in fruits) # True\nprint('apple' in fruits) # False\nfruits[0] = 'apple' # TypeError: 'tuple' object does not support item assignment\n```\n\n### Joining Tuples\n\nWe can join two or more tuples using + operator\n\n```py\n# syntax\ntpl1 = ('item1', 'item2', 'item3')\ntpl2 = ('item4', 'item5','item6')\ntpl3 = tpl1 + tpl2\n```\n\n```py\nfruits = ('banana', 'orange', 'mango', 'lemon')\nvegetables = ('Tomato', 'Potato', 'Cabbage','Onion', 'Carrot')\nfruits_and_vegetables = fruits + vegetables\n```\n\n### Deleting Tuples\n\nIt is not possible to remove a single item in a tuple but it is possible to delete the tuple itself using _del_.\n\n```py\n# syntax\ntpl1 = ('item1', 'item2', 'item3')\ndel tpl1\n\n```\n\n```py\nfruits = ('banana', 'orange', 'mango', 'lemon')\ndel fruits\n```\n\n🌕 You are so brave, you made it to this far. You have just completed day 6 challenges and you are 6 steps a head in to your way to greatness. Now do some exercises for your brain and for your muscle.\n\n## 💻 Exercises: Day 6\n\n### Exercises: Level 1\n\n1. Create an empty tuple\n2. Create a tuple containing names of your sisters and your brothers (imaginary siblings are fine)\n3. Join brothers and sisters tuples and assign it to siblings\n4. How many siblings do you have?\n5. Modify the siblings tuple and add the name of your father and mother and assign it to family_members\n\n### Exercises: Level 2\n\n1. Unpack siblings and parents from family_members\n1. Create fruits, vegetables and animal products tuples. Join the three tuples and assign it to a variable called food_stuff_tp.\n1. Change the about food_stuff_tp tuple to a food_stuff_lt list\n1. Slice out the middle item or items from the food_stuff_tp tuple or food_stuff_lt list.\n1. Slice out the first three items and the last three items from food_stuff_lt list\n1. Delete the food_stuff_tp tuple completely\n1. Check if an item exists in tuple:\n\n- Check if 'Estonia' is a nordic country\n- Check if 'Iceland' is a nordic country\n\n ```py\n nordic_countries = ('Denmark', 'Finland','Iceland', 'Norway', 'Sweden')\n ```\n\n\n[<< Day 5](../05_Day_Lists/05_lists.md) | [Day 7 >>](../07_Day_Sets/07_sets.md)\n"
},
{
"path": "07_Day_Sets/07_sets.md",
"content": "
\n\n[<< Day 6](../06_Day_Tuples/06_tuples.md) | [Day 8 >>](../08_Day_Dictionaries/08_dictionaries.md)\n\n\n\n- [📘 Day 7](#-day-7)\n - [Sets](#sets)\n - [Creating a Set](#creating-a-set)\n - [Getting Set's Length](#getting-sets-length)\n - [Accessing Items in a Set](#accessing-items-in-a-set)\n - [Checking an Item](#checking-an-item)\n - [Adding Items to a Set](#adding-items-to-a-set)\n - [Removing Items from a Set](#removing-items-from-a-set)\n - [Clearing Items in a Set](#clearing-items-in-a-set)\n - [Deleting a Set](#deleting-a-set)\n - [Converting List to Set](#converting-list-to-set)\n - [Joining Sets](#joining-sets)\n - [Finding Intersection Items](#finding-intersection-items)\n - [Checking Subset and Super Set](#checking-subset-and-super-set)\n - [Checking the Difference Between Two Sets](#checking-the-difference-between-two-sets)\n - [Finding Symmetric Difference Between Two Sets](#finding-symmetric-difference-between-two-sets)\n - [Joining Sets](#joining-sets-1)\n - [💻 Exercises: Day 7](#-exercises-day-7)\n - [Exercises: Level 1](#exercises-level-1)\n - [Exercises: Level 2](#exercises-level-2)\n - [Exercises: Level 3](#exercises-level-3)\n\n# 📘 Day 7\n\n## Sets\n\nSet is a collection of items. Let me take you back to your elementary or high school Mathematics lesson. The Mathematics definition of a set can be applied also in Python. Set is a collection of unordered and un-indexed distinct elements. In Python set is used to store unique items, and it is possible to find the _union_, _intersection_, _difference_, _symmetric difference_, _subset_, _super set_ and _disjoint set_ among sets.\n\n### Creating a Set\n\nTo create an empty set, we use the set() function. Empty curly brackets {} will create a dictionary. \n\n- Creating an empty set\n\n```py\n# syntax\nst = set()\n```\n\n- Creating a set with initial items\n\n```py\n# syntax\nst = {'item1', 'item2', 'item3', 'item4'}\n```\n\n**Example:**\n\n```py\n# syntax\nfruits = {'banana', 'orange', 'mango', 'lemon'}\n```\n\n### Getting Set's Length\n\nWe use **len()** method to find the length of a set.\n\n```py\n# syntax\nst = {'item1', 'item2', 'item3', 'item4'}\nlen(st)\n```\n\n**Example:**\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\nlen(fruits)\n```\n\n### Accessing Items in a Set\n\nWe use loops to access items. We will see this in loop section\n\n### Checking an Item\n\nTo check if an item exist in a list we use _in_ membership operator.\n\n```py\n# syntax\nst = {'item1', 'item2', 'item3', 'item4'}\nprint(\"Does set st contain item3? \", 'item3' in st) # Does set st contain item3? True\n```\n\n**Example:**\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\nprint('mango' in fruits ) # True\n```\n\n### Adding Items to a Set\n\nOnce a set is created we cannot change any items and we can also add additional items.\n\n- Add one item using _add()_\n\n```py\n# syntax\nst = {'item1', 'item2', 'item3', 'item4'}\nst.add('item5')\n```\n\n**Example:**\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\nfruits.add('lime')\n```\n\n- Add multiple items using _update()_\n The _update()_ allows to add multiple items to a set. The _update()_ takes a list argument.\n\n```py\n# syntax\nst = {'item1', 'item2', 'item3', 'item4'}\nst.update(['item5','item6','item7'])\n```\n\n**Example:**\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\nvegetables = ('tomato', 'potato', 'cabbage','onion', 'carrot')\nfruits.update(vegetables)\n```\n\n### Removing Items from a Set\n\nWe can remove an item from a set using _remove()_ method. If the item is not found _remove()_ method will raise errors, so it is good to check if the item exist in the given set. However, _discard()_ method doesn't raise any errors.\n\n```py\n# syntax\nst = {'item1', 'item2', 'item3', 'item4'}\nst.remove('item2')\n```\n\nThe pop() methods remove a random item from a list and it returns the removed item.\n\n**Example:**\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\nfruits.pop() # removes a random item from the set\n\n```\n\nIf we are interested in the removed item.\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\nremoved_item = fruits.pop() \n```\n\n### Clearing Items in a Set\n\nIf we want to clear or empty the set we use _clear_ method.\n\n```py\n# syntax\nst = {'item1', 'item2', 'item3', 'item4'}\nst.clear()\n```\n\n**Example:**\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\nfruits.clear()\nprint(fruits) # set()\n```\n\n### Deleting a Set\n\nIf we want to delete the set itself we use _del_ operator.\n\n```py\n# syntax\nst = {'item1', 'item2', 'item3', 'item4'}\ndel st\n```\n\n**Example:**\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\ndel fruits\n```\n\n### Converting List to Set\n\nWe can convert list to set and set to list. Converting list to set removes duplicates and only unique items will be reserved.\n\n```py\n# syntax\nlst = ['item1', 'item2', 'item3', 'item4', 'item1']\nst = set(lst) # {'item2', 'item4', 'item1', 'item3'} - the order is random, because sets in general are unordered\n```\n\n**Example:**\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon','orange', 'banana']\nfruits = set(fruits) # {'mango', 'lemon', 'banana', 'orange'}\n```\n\n### Joining Sets\n\nWe can join two sets using the _union()_ or _update()_ method or _|_ symbol .\n\n- Union\n This method returns a new set\n\n```py\n# syntax\nst1 = {'item1', 'item2', 'item3', 'item4'}\nst2 = {'item5', 'item6', 'item7', 'item8'}\nst3 = st1.union(st2) #st3 = st1 | st2\n```\n\n**Example:**\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\nvegetables = {'tomato', 'potato', 'cabbage','onion', 'carrot'}\nprint(fruits.union(vegetables)) # {'lemon', 'carrot', 'tomato', 'banana', 'mango', 'orange', 'cabbage', 'potato', 'onion'}\n# or using this : print(fruits | vegetables)\n```\n\n- Update\n This method inserts a set into a given set\n\n```py\n# syntax\nst1 = {'item1', 'item2', 'item3', 'item4'}\nst2 = {'item5', 'item6', 'item7', 'item8'}\nst1.update(st2) # st2 contents are added to st1\n```\n\n**Example:**\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\nvegetables = {'tomato', 'potato', 'cabbage','onion', 'carrot'}\nfruits.update(vegetables)\nprint(fruits) # {'lemon', 'carrot', 'tomato', 'banana', 'mango', 'orange', 'cabbage', 'potato', 'onion'}\n```\n\n### Finding Intersection Items\n\nIntersection returns a set of items which are in both the sets or using _&_ symbol. See the example\n\n```py\n# syntax\nst1 = {'item1', 'item2', 'item3', 'item4'}\nst2 = {'item3', 'item2'}\nst1.intersection(st2) # {'item3', 'item2'}\n# or using thia : st1 & st2\n```\n\n**Example:**\n\n```py\nwhole_numbers = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10}\neven_numbers = {0, 2, 4, 6, 8, 10}\nwhole_numbers.intersection(even_numbers) # {0, 2, 4, 6, 8, 10}\n\npython = {'p', 'y', 't', 'h', 'o','n'}\ndragon = {'d', 'r', 'a', 'g', 'o','n'}\npython.intersection(dragon) # {'o', 'n'}\n# python & dragon\n```\n\n### Checking Subset and Super Set\n\nA set can be a subset or super set of other sets:\n\n- Subset: _issubset()_\n- Super set: _issuperset_\n\n```py\n# syntax\nst1 = {'item1', 'item2', 'item3', 'item4'}\nst2 = {'item2', 'item3'}\nst2.issubset(st1) # True\nst1.issuperset(st2) # True\n```\n\n**Example:**\n\n```py\nwhole_numbers = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10}\neven_numbers = {0, 2, 4, 6, 8, 10}\nwhole_numbers.issubset(even_numbers) # False, because it is a super set\nwhole_numbers.issuperset(even_numbers) # True\n\npython = {'p', 'y', 't', 'h', 'o','n'}\ndragon = {'d', 'r', 'a', 'g', 'o','n'}\npython.issubset(dragon) # False\n```\n\n### Checking the Difference Between Two Sets\n\nIt returns the difference between two sets or using _-_ symbol .\n\n```py\n# syntax\nst1 = {'item1', 'item2', 'item3', 'item4'}\nst2 = {'item2', 'item3'}\nst2.difference(st1) # set() : st2 - st1\nst1.difference(st2) # {'item1', 'item4'} => st1\\st2 : st2 - st1\n```\n\n**Example:**\n\n```py\nwhole_numbers = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10}\neven_numbers = {0, 2, 4, 6, 8, 10}\nwhole_numbers.difference(even_numbers) # {1, 3, 5, 7, 9}\n\npython = {'p', 'y', 't', 'o','n'}\ndragon = {'d', 'r', 'a', 'g', 'o','n'}\npython.difference(dragon) # {'p', 'y', 't'} - the result is unordered (characteristic of sets)\n# python - dragon\ndragon.difference(python) # {'d', 'r', 'a', 'g'}\n# dragon - python\n```\n\n### Finding Symmetric Difference Between Two Sets\n\nIt returns the symmetric difference between two sets. It means that it returns a set that contains all items from both sets, except items that are present in both sets, mathematically: (A\\B) ∪ (B\\A)\n\n```py\n# syntax\nst1 = {'item1', 'item2', 'item3', 'item4'}\nst2 = {'item2', 'item3'}\n# it means (A\\B)∪(B\\A)\nst2.symmetric_difference(st1) # {'item1', 'item4'} : st2 ^ st1\n```\n\n**Example:**\n\n```py\nwhole_numbers = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10}\nsome_numbers = {1, 2, 3, 4, 5}\nwhole_numbers.symmetric_difference(some_numbers) # {0, 6, 7, 8, 9, 10}\n\npython = {'p', 'y', 't', 'h', 'o','n'}\ndragon = {'d', 'r', 'a', 'g', 'o','n'}\npython.symmetric_difference(dragon) # {'r', 't', 'p', 'y', 'g', 'a', 'd', 'h'}\n# python ^ dragon\n```\n\n### Joining Sets\n\nIf two sets do not have a common item or items we call them disjoint sets. We can check if two sets are joint or disjoint using _isdisjoint()_ method.\n\n```py\n# syntax\nst1 = {'item1', 'item2', 'item3', 'item4'}\nst2 = {'item2', 'item3'}\nst2.isdisjoint(st1) # False\n```\n\n**Example:**\n\n```py\neven_numbers = {0, 2, 4 ,6, 8}\nodd_numbers = {1, 3, 5, 7, 9}\neven_numbers.isdisjoint(odd_numbers) # True, because no common item\n\npython = {'p', 'y', 't', 'h', 'o','n'}\ndragon = {'d', 'r', 'a', 'g', 'o','n'}\npython.isdisjoint(dragon) # False, there are common items {'o', 'n'}\n```\n\n🌕 You are a rising star . You have just completed day 7 challenges and you are 7 steps ahead in to your way to greatness. Now do some exercises for your brain and muscles.\n\n## 💻 Exercises: Day 7\n\n```py\n# sets\nit_companies = {'Facebook', 'Google', 'Microsoft', 'Apple', 'IBM', 'Oracle', 'Amazon'}\nA = {19, 22, 24, 20, 25, 26}\nB = {19, 22, 20, 25, 26, 24, 28, 27}\nage = [22, 19, 24, 25, 26, 24, 25, 24]\n```\n\n### Exercises: Level 1\n\n1. Find the length of the set it_companies\n2. Add 'Twitter' to it_companies\n3. Insert multiple IT companies at once to the set it_companies\n4. Remove one of the companies from the set it_companies\n5. What is the difference between remove and discard\n\n### Exercises: Level 2\n\n1. Join A and B\n2. Find A intersection B\n3. Is A subset of B\n4. Are A and B disjoint sets\n5. Join A with B and B with A\n6. What is the symmetric difference between A and B\n7. Delete the sets completely\n\n### Exercises: Level 3\n\n1. Convert the ages to a set and compare the length of the list and the set, which one is bigger?\n2. Explain the difference between the following data types: string, list, tuple and set\n3. _I am a teacher and I love to inspire and teach people._ How many unique words have been used in the sentence? Use the split methods and set to get the unique words.\n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 6](../06_Day_Tuples/06_tuples.md) | [Day 8 >>](../08_Day_Dictionaries/08_dictionaries.md)\n"
},
{
"path": "08_Day_Dictionaries/08_dictionaries.md",
"content": "
\n\n[<< Day 7 ](../07_Day_Sets/07_sets.md) | [Day 9 >>](../09_Day_Conditionals/09_conditionals.md)\n\n\n\n- [📘 Day 8](#-day-8)\n - [Dictionaries](#dictionaries)\n - [Creating a Dictionary](#creating-a-dictionary)\n - [Dictionary Length](#dictionary-length)\n - [Accessing Dictionary Items](#accessing-dictionary-items)\n - [Adding Items to a Dictionary](#adding-items-to-a-dictionary)\n - [Modifying Items in a Dictionary](#modifying-items-in-a-dictionary)\n - [Checking Keys in a Dictionary](#checking-keys-in-a-dictionary)\n - [Removing Key and Value Pairs from a Dictionary](#removing-key-and-value-pairs-from-a-dictionary)\n - [Changing Dictionary to a List of Items](#changing-dictionary-to-a-list-of-items)\n - [Clearing a Dictionary](#clearing-a-dictionary)\n - [Deleting a Dictionary](#deleting-a-dictionary)\n - [Copy a Dictionary](#copy-a-dictionary)\n - [Getting Dictionary Keys as a List](#getting-dictionary-keys-as-a-list)\n - [Getting Dictionary Values as a List](#getting-dictionary-values-as-a-list)\n - [💻 Exercises: Day 8](#-exercises-day-8)\n\n# 📘 Day 8\n\n## Dictionaries\n\nA dictionary is a collection of unordered, modifiable(mutable) paired (key: value) data type.\n\n### Creating a Dictionary\n\nTo create a dictionary we use curly brackets, {} or the *dict()* built-in function.\n\n```py\n# syntax\nempty_dict = {}\n# Dictionary with data values\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\n```\n\n**Example:**\n\n```py\nperson = {\n 'first_name':'Asabeneh',\n 'last_name':'Yetayeh',\n 'age':250,\n 'country':'Finland',\n 'is_marred':True,\n 'skills':['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address':{\n 'street':'Space street',\n 'zipcode':'02210'\n }\n }\n```\n\nThe dictionary above shows that a value could be any data types:string, boolean, list, tuple, set or a dictionary.\n\n### Dictionary Length\n\nIt checks the number of 'key: value' pairs in the dictionary.\n\n```py\n# syntax\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\nprint(len(dct)) # 4\n```\n\n**Example:**\n\n```py\nperson = {\n 'first_name':'Asabeneh',\n 'last_name':'Yetayeh',\n 'age':250,\n 'country':'Finland',\n 'is_married':True,\n 'skills':['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address':{\n 'street':'Space street',\n 'zipcode':'02210'\n }\n }\nprint(len(person)) # 7\n\n```\n\n### Accessing Dictionary Items\n\nWe can access Dictionary items by referring to its key name.\n\n```py\n# syntax\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\nprint(dct['key1']) # value1\nprint(dct['key4']) # value4\n```\n\n**Example:**\n\n```py\nperson = {\n 'first_name':'Asabeneh',\n 'last_name':'Yetayeh',\n 'age':250,\n 'country':'Finland',\n 'is_marred':True,\n 'skills':['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address':{\n 'street':'Space street',\n 'zipcode':'02210'\n }\n }\nprint(person['first_name']) # Asabeneh\nprint(person['country']) # Finland\nprint(person['skills']) # ['JavaScript', 'React', 'Node', 'MongoDB', 'Python']\nprint(person['skills'][0]) # JavaScript\nprint(person['address']['street']) # Space street\nprint(person['city']) # Error\n```\n\nAccessing an item by key name raises an error if the key does not exist. To avoid this error first we have to check if a key exist or we can use the _get_ method. The get method returns None, which is a NoneType object data type, if the key does not exist.\n```py\nperson = {\n 'first_name':'Asabeneh',\n 'last_name':'Yetayeh',\n 'age':250,\n 'country':'Finland',\n 'is_marred':True,\n 'skills':['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address':{\n 'street':'Space street',\n 'zipcode':'02210'\n }\n }\nprint(person.get('first_name')) # Asabeneh\nprint(person.get('country')) # Finland\nprint(person.get('skills')) #['JavaScript', 'React', 'Node', 'MongoDB', 'Python']\nprint(person.get('city')) # None\n```\n\n### Adding Items to a Dictionary\n\nWe can add new key and value pairs to a dictionary\n\n```py\n# syntax\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\ndct['key5'] = 'value5'\n```\n\n**Example:**\n\n```py\nperson = {\n 'first_name':'Asabeneh',\n 'last_name':'Yetayeh',\n 'age':250,\n 'country':'Finland',\n 'is_marred':True,\n 'skills':['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address':{\n 'street':'Space street',\n 'zipcode':'02210'\n }\n}\nperson['job_title'] = 'Instructor'\nperson['skills'].append('HTML')\nprint(person)\n```\n\n### Modifying Items in a Dictionary\n\nWe can modify items in a dictionary\n\n```py\n# syntax\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\ndct['key1'] = 'value-one'\n```\n\n**Example:**\n\n```py\nperson = {\n 'first_name':'Asabeneh',\n 'last_name':'Yetayeh',\n 'age':250,\n 'country':'Finland',\n 'is_marred':True,\n 'skills':['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address':{\n 'street':'Space street',\n 'zipcode':'02210'\n }\n }\nperson['first_name'] = 'Eyob'\nperson['age'] = 252\n```\n\n### Checking Keys in a Dictionary\n\nWe use the _in_ operator to check if a key exist in a dictionary\n\n```py\n# syntax\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\nprint('key2' in dct) # True\nprint('key5' in dct) # False\n```\n\n### Removing Key and Value Pairs from a Dictionary\n\n- _pop(key)_: removes the item with the specified key name:\n- _popitem()_: removes the last item\n- _del_: removes an item with specified key name\n\n```py\n# syntax\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\ndct.pop('key1') # removes key1 item\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\ndct.popitem() # removes the last item\ndel dct['key2'] # removes key2 item\n```\n\n**Example:**\n\n```py\nperson = {\n 'first_name':'Asabeneh',\n 'last_name':'Yetayeh',\n 'age':250,\n 'country':'Finland',\n 'is_marred':True,\n 'skills':['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address':{\n 'street':'Space street',\n 'zipcode':'02210'\n }\n }\nperson.pop('first_name') # Removes the firstname item\nperson.popitem() # Removes the address item\ndel person['is_married'] # Removes the is_married item\n```\n\n### Changing Dictionary to a List of Items\n\nThe _items()_ method changes dictionary to a list of tuples.\n\n```py\n# syntax\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\nprint(dct.items()) # dict_items([('key1', 'value1'), ('key2', 'value2'), ('key3', 'value3'), ('key4', 'value4')])\n```\n\n### Clearing a Dictionary\n\nIf we don't want the items in a dictionary we can clear them using _clear()_ method\n\n```py\n# syntax\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\nprint(dct.clear()) # None\n```\n\n### Deleting a Dictionary\n\nIf we do not use the dictionary we can delete it completely\n\n```py\n# syntax\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\ndel dct\n```\n\n### Copy a Dictionary\n\nWe can copy a dictionary using a _copy()_ method. Using copy we can avoid mutation of the original dictionary.\n\n```py\n# syntax\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\ndct_copy = dct.copy() # {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\n```\n\n### Getting Dictionary Keys as a List\n\nThe _keys()_ method gives us all the keys of a a dictionary as a list.\n\n```py\n# syntax\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\nkeys = dct.keys()\nprint(keys) # dict_keys(['key1', 'key2', 'key3', 'key4'])\n```\n\n### Getting Dictionary Values as a List\n\nThe _values_ method gives us all the values of a a dictionary as a list.\n\n```py\n# syntax\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\nvalues = dct.values()\nprint(values) # dict_values(['value1', 'value2', 'value3', 'value4'])\n```\n\n🌕 You are astonishing. Now, you are super charged with the power of dictionaries. You have just completed day 8 challenges and you are 8 steps a head in to your way to greatness. Now do some exercises for your brain and muscles.\n\n## 💻 Exercises: Day 8\n\n1. Create an empty dictionary called dog\n2. Add name, color, breed, legs, age to the dog dictionary\n3. Create a student dictionary and add first_name, last_name, gender, age, marital status, skills, country, city and address as keys for the dictionary\n4. Get the length of the student dictionary\n5. Get the value of skills and check the data type, it should be a list\n6. Modify the skills values by adding one or two skills\n7. Get the dictionary keys as a list\n8. Get the dictionary values as a list\n9. Change the dictionary to a list of tuples using _items()_ method\n10. Delete one of the items in the dictionary\n11. Delete one of the dictionaries\n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 7 ](../07_Day_Sets/07_sets.md) | [Day 9 >>](../09_Day_Conditionals/09_conditionals.md)\n"
},
{
"path": "09_Day_Conditionals/09_conditionals.md",
"content": "
\n\n[<< Day 8](../08_Day_Dictionaries/08_dictionaries.md) | [Day 10 >>](../10_Day_Loops/10_loops.md)\n\n\n\n- [📘 Day 9](#-day-9)\n - [Conditionals](#conditionals)\n - [If Condition](#if-condition)\n - [If Else](#if-else)\n - [If Elif Else](#if-elif-else)\n - [Short Hand](#short-hand)\n - [Nested Conditions](#nested-conditions)\n - [If Condition and Logical Operators](#if-condition-and-logical-operators)\n - [If and Or Logical Operators](#if-and-or-logical-operators)\n - [💻 Exercises: Day 9](#-exercises-day-9)\n - [Exercises: Level 1](#exercises-level-1)\n - [Exercises: Level 2](#exercises-level-2)\n - [Exercises: Level 3](#exercises-level-3)\n\n# 📘 Day 9\n\n## Conditionals\n\nBy default, statements in Python script are executed sequentially from top to bottom. If the processing logic require so, the sequential flow of execution can be altered in two way:\n\n- Conditional execution: a block of one or more statements will be executed if a certain expression is true\n- Repetitive execution: a block of one or more statements will be repetitively executed as long as a certain expression is true. In this section, we will cover _if_, _else_, _elif_ statements. The comparison and logical operators we learned in previous sections will be useful here.\n\n### If Condition\n\nIn python and other programming languages the key word _if_ is used to check if a condition is true and to execute the block code. Remember the indentation after the colon.\n\n```py\n# syntax\nif condition:\n this part of code runs for truthy conditions\n```\n\n**Example: 1**\n\n```py\na = 3\nif a > 0:\n print('A is a positive number')\n# A is a positive number\n```\n\nAs you can see in the example above, 3 is greater than 0. The condition was true and the block code was executed. However, if the condition is false, we do not see the result. In order to see the result of the falsy condition, we should have another block, which is going to be _else_.\n\n### If Else\n\nIf condition is true the first block will be executed, if not the else condition will run.\n\n```py\n# syntax\nif condition:\n this part of code runs for truthy conditions\nelse:\n this part of code runs for false conditions\n```\n\n**Example:**\n\n```py\na = 3\nif a < 0:\n print('A is a negative number')\nelse:\n print('A is a positive number')\n```\n\nThe condition above proves false, therefore the else block was executed. How about if our condition is more than two? We could use _elif_.\n\n### If Elif Else\n\nIn our daily life, we make decisions on daily basis. We make decisions not by checking one or two conditions but multiple conditions. As similar to life, programming is also full of conditions. We use _elif_ when we have multiple conditions.\n\n```py\n# syntax\nif condition:\n code\nelif condition:\n code\nelse:\n code\n\n```\n\n**Example:**\n\n```py\na = 0\nif a > 0:\n print('A is a positive number')\nelif a < 0:\n print('A is a negative number')\nelse:\n print('A is zero')\n```\n\n### Short Hand\n\n```py\n# syntax\ncode if condition else code\n```\n\n**Example:**\n\n```py\na = 3\nprint('A is positive') if a > 0 else print('A is negative') # first condition met, 'A is positive' will be printed\n```\n\n### Nested Conditions\n\nConditions can be nested\n\n```py\n# syntax\nif condition:\n code\n if condition:\n code\n```\n\n**Example:**\n\n```py\na = 0\nif a > 0:\n if a % 2 == 0:\n print('A is a positive and even integer')\n else:\n print('A is a positive number')\nelif a == 0:\n print('A is zero')\nelse:\n print('A is a negative number')\n\n```\n\nWe can avoid writing nested condition by using logical operator _and_.\n\n### If Condition and Logical Operators\n\n```py\n# syntax\nif condition and condition:\n code\n```\n\n**Example:**\n\n```py\na = 0\nif a > 0 and a % 2 == 0:\n print('A is an even and positive integer')\nelif a > 0 and a % 2 != 0:\n print('A is a positive integer')\nelif a == 0:\n print('A is zero')\nelse:\n print('A is negative')\n```\n\n### If and Or Logical Operators\n\n```py\n# syntax\nif condition or condition:\n code\n```\n\n**Example:**\n\n```py\nuser = 'James'\naccess_level = 3\nif user == 'admin' or access_level >= 4:\n print('Access granted!')\nelse:\n print('Access denied!')\n```\n\n🌕 You are doing great.Never give up because great things take time. You have just completed day 9 challenges and you are 9 steps a head in to your way to greatness. Now do some exercises for your brain and muscles.\n\n## 💻 Exercises: Day 9\n\n### Exercises: Level 1\n\n1. Get user input using input(“Enter your age: ”). If user is 18 or older, give feedback: You are old enough to drive. If below 18 give feedback to wait for the missing amount of years. Output:\n\n ```sh\n Enter your age: 30\n You are old enough to learn to drive.\n Output:\n Enter your age: 15\n You need 3 more years to learn to drive.\n ```\n\n2. Compare the values of my_age and your_age using if … else. Who is older (me or you)? Use input(“Enter your age: ”) to get the age as input. You can use a nested condition to print 'year' for 1 year difference in age, 'years' for bigger differences, and a custom text if my_age = your_age. Output:\n\n ```sh\n Enter your age: 30\n You are 5 years older than me.\n ```\n\n3. Get two numbers from the user using input prompt. If a is greater than b return a is greater than b, if a is less b return a is smaller than b, else a is equal to b. Output:\n\n```sh\nEnter number one: 4\nEnter number two: 3\n4 is greater than 3\n```\n\n### Exercises: Level 2\n\n 1. Write a code which gives grade to students according to theirs scores:\n\n ```sh\n 90-100, A\n 80-89, B\n 70-79, C\n 60-69, D\n 0-59, F\n ```\n\n 2. Get the month from user input then check if the season is Autumn, Winter, Spring or Summer. If the user input is:\n September, October or November, the season is Autumn.\n December, January or February, the season is Winter.\n March, April or May, the season is Spring\n June, July or August, the season is Summer\n 3. The following list contains some fruits:\n\n ```sh\n fruits = ['banana', 'orange', 'mango', 'lemon']\n ```\n\n If a fruit doesn't exist in the list add the fruit to the list and print the modified list. If the fruit exists print('That fruit already exist in the list')\n\n### Exercises: Level 3\n\n 1. Here we have a person dictionary. Feel free to modify it!\n\n```py\n person={\n 'first_name': 'Asabeneh',\n 'last_name': 'Yetayeh',\n 'age': 250,\n 'country': 'Finland',\n 'is_married': True,\n 'skills': ['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address': {\n 'street': 'Space street',\n 'zipcode': '02210'\n }\n }\n```\n\n * Check if the person dictionary has skills key, if so print out the middle skill in the skills list.\n * Check if the person dictionary has skills key, if so check if the person has 'Python' skill and print out the result.\n * If a person skills has only JavaScript and React, print('He is a front end developer'), if the person skills has Node, Python, MongoDB, print('He is a backend developer'), if the person skills has React, Node and MongoDB, Print('He is a fullstack developer'), else print('unknown title') - for more accurate results more conditions can be nested!\n * If the person is married and if he lives in Finland, print the information in the following format:\n\n```py\n Asabeneh Yetayeh lives in Finland. He is married.\n```\n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 8](../08_Day_Dictionaries/08_dictionaries.md) | [Day 10 >>](../10_Day_Loops/10_loops.md)\n"
},
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"path": "10_Day_Loops/10_loops.md",
"content": "
\n\n[<< Day 9](../09_Day_Conditionals/09_conditionals.md) | [Day 11 >>](../11_Day_Functions/11_functions.md)\n\n\n\n- [📘 Day 10](#-day-10)\n - [Loops](#loops)\n - [While Loop](#while-loop)\n - [Break and Continue - Part 1](#break-and-continue---part-1)\n - [For Loop](#for-loop)\n - [Break and Continue - Part 2](#break-and-continue---part-2)\n - [The Range Function](#the-range-function)\n - [Nested For Loop](#nested-for-loop)\n - [For Else](#for-else)\n - [Pass](#pass)\n - [💻 Exercises: Day 10](#-exercises-day-10)\n - [Exercises: Level 1](#exercises-level-1)\n - [Exercises: Level 2](#exercises-level-2)\n - [Exercises: Level 3](#exercises-level-3)\n\n# 📘 Day 10\n\n## Loops\n\nLife is full of routines. In programming we also do lots of repetitive tasks. In order to handle repetitive task programming languages use loops. Python programming language also provides the following types of two loops:\n\n1. while loop\n2. for loop\n\n### While Loop\n\nWe use the reserved word _while_ to make a while loop. It is used to execute a block of statements repeatedly until a given condition is satisfied. When the condition becomes false, the lines of code after the loop will be continued to be executed.\n\n```py\n # syntax\nwhile condition:\n code goes here\n```\n\n**Example:**\n\n```py\ncount = 0\nwhile count < 5:\n print(count)\n count = count + 1\n#prints from 0 to 4\n```\n\nIn the above while loop, the condition becomes false when count is 5. That is when the loop stops.\nIf we are interested to run block of code once the condition is no longer true, we can use _else_.\n\n```py\n # syntax\nwhile condition:\n code goes here\nelse:\n code goes here\n```\n\n**Example:**\n\n```py\ncount = 0\nwhile count < 5:\n print(count)\n count = count + 1\nelse:\n print(count)\n```\n\nThe above loop condition will be false when count is 5 and the loop stops, and execution starts the else statement. As a result 5 will be printed.\n\n### Break and Continue - Part 1\n\n- Break: We use break when we like to get out of or stop the loop.\n\n```py\n# syntax\nwhile condition:\n code goes here\n if another_condition:\n break\n```\n\n**Example:**\n\n```py\ncount = 0\nwhile count < 5:\n print(count)\n count = count + 1\n if count == 3:\n break\n```\n\nThe above while loop only prints 0, 1, 2, but when it reaches 3 it stops.\n\n- Continue: With the continue statement we can skip the current iteration, and continue with the next:\n\n```py\n # syntax\nwhile condition:\n code goes here\n if another_condition:\n continue\n```\n\n**Example:**\n\n```py\ncount = 0\nwhile count < 5:\n if count == 3:\n count += 1\n continue\n print(count)\n count = count + 1\n```\n\nThe above while loop only prints 0, 1, 2 and 4 (skips 3).\n\n### For Loop\n\nA _for_ keyword is used to make a for loop, similar with other programming languages, but with some syntax differences. Loop is used for iterating over a sequence (that is either a list, a tuple, a dictionary, a set, or a string).\n\n-Using For loop on list\n\n```py\n# syntax\nfor iterator in lst:\n code goes here\n```\n\n**Example:**\n\n```py\nnumbers = [0, 1, 2, 3, 4, 5]\nfor number in numbers: # number is temporary name to refer to the list's items, valid only inside this loop\n print(number) # the numbers will be printed line by line, from 0 to 5\n```\n\n-Using For loop on string\n\n```py\n# syntax\nfor iterator in string:\n code goes here\n```\n\n**Example:**\n\n```py\nlanguage = 'Python'\nfor letter in language:\n print(letter)\n\n\nfor i in range(len(language)):\n print(language[i])\n```\n\n-Using For loop on tuple\n\n```py\n# syntax\nfor iterator in tpl:\n code goes here\n```\n\n**Example:**\n\n```py\nnumbers = (0, 1, 2, 3, 4, 5)\nfor number in numbers:\n print(number)\n```\n\n- For loop with dictionary\n Looping through a dictionary gives you the key of the dictionary.\n\n```py\n # syntax\nfor iterator in dct:\n code goes here\n```\n\n**Example:**\n\n```py\nperson = {\n 'first_name':'Asabeneh',\n 'last_name':'Yetayeh',\n 'age':250,\n 'country':'Finland',\n 'is_marred':True,\n 'skills':['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address':{\n 'street':'Space street',\n 'zipcode':'02210'\n }\n}\nfor key in person:\n print(key)\n\nfor key, value in person.items():\n print(key, value) # this way we get both keys and values printed out\n```\n\n-Using For Loop in set\n\n```py\n# syntax\nfor iterator in st:\n code goes here\n```\n\n**Example:**\n\n```py\nit_companies = {'Facebook', 'Google', 'Microsoft', 'Apple', 'IBM', 'Oracle', 'Amazon'}\nfor company in it_companies:\n print(company)\n```\n\n### Break and Continue - Part 2\n\nShort reminder:\n_Break_: We use break when we want to stop our loop before it is completed.\n\n```py\n# syntax\nfor iterator in sequence:\n code goes here\n if condition:\n break\n```\n\n**Example:**\n\n```py\nnumbers = (0,1,2,3,4,5)\nfor number in numbers:\n print(number)\n if number == 3:\n break\n```\n\nIn the above example, the loop stops when it reaches 3.\n\nContinue: We use continue when we want to skip some of the steps in the iteration of the loop.\n\n```py\n # syntax\nfor iterator in sequence:\n code goes here\n if condition:\n continue\n```\n\n**Example:**\n\n```py\nnumbers = (0,1,2,3,4,5)\nfor number in numbers:\n print(number)\n if number == 3:\n continue\n print('Next number should be ', number + 1) if number != 5 else print(\"loop's end\") # for short hand conditions need both if and else statements\nprint('outside the loop')\n```\n\nIn the example above, if the number equals 3, the step _after_ the condition (but inside the loop) is skipped and the execution of the loop continues if there are any iterations left.\n\n### The Range Function\n\nThe _range()_ function is used to return a list of numbers. The _range(start, end, step)_ takes three parameters: starting, ending and increment. By default it starts from 0 and the increment is 1. The range sequence needs at least 1 argument (end).\nCreating sequences using range\n\n```py\nlst = list(range(11))\nprint(lst) # [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\nst = set(range(1, 11)) # 2 arguments indicate start and end of the sequence, step set to default 1\nprint(st) # {1, 2, 3, 4, 5, 6, 7, 8, 9, 10}\n\nlst = list(range(0,11,2))\nprint(lst) # [0, 2, 4, 6, 8, 10]\nst = set(range(0,11,2))\nprint(st) # {0, 2, 4, 6, 8, 10}\n\n# for backward from start to end \nlst = list(range(11,0,-2))\nprint(lst) # [11,9,7,5,3,1]\n```\n\n```py\n# syntax\nfor iterator in range(start, end, step):\n```\n\n**Example:**\n\n```py\nfor number in range(11):\n print(number) # prints 0 to 10, not including 11\n```\n\n### Nested For Loop\n\nWe can write loops inside a loop.\n\n```py\n# syntax\nfor x in y:\n for t in x:\n print(t)\n```\n\n**Example:**\n\n```py\nperson = {\n 'first_name': 'Asabeneh',\n 'last_name': 'Yetayeh',\n 'age': 250,\n 'country': 'Finland',\n 'is_marred': True,\n 'skills': ['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address': {\n 'street': 'Space street',\n 'zipcode': '02210'\n }\n}\nfor key in person:\n if key == 'skills':\n for skill in person['skills']:\n print(skill)\n```\n\n### For Else\n\nIf we want to execute some message when the loop ends, we use else.\n\n```py\n# syntax\nfor iterator in range(start, end, step):\n do something\nelse:\n print('The loop ended')\n```\n\n**Example:**\n\n```py\nfor number in range(11):\n print(number) # prints 0 to 10, not including 11\nelse:\n print('The loop stops at', number)\n```\n\n### Pass\n\nIn python when statement is required (after semicolon), but we don't like to execute any code there, we can write the word _pass_ to avoid errors. Also we can use it as a placeholder, for future statements.\n\n**Example:**\n\n```py\nfor number in range(6):\n pass\n```\n\n🌕 You established a big milestone, you are unstoppable. Keep going! You have just completed day 10 challenges and you are 10 steps a head in to your way to greatness. Now do some exercises for your brain and muscles.\n\n## 💻 Exercises: Day 10\n\n### Exercises: Level 1\n\n1. Iterate 0 to 10 using for loop, do the same using while loop.\n2. Iterate 10 to 0 using for loop, do the same using while loop.\n3. Write a loop that makes seven calls to print(), so we get on the output the following triangle:\n\n ```py\n #\n ##\n ###\n ####\n #####\n ######\n #######\n ```\n\n4. Use nested loops to create the following:\n\n ```sh\n # # # # # # # #\n # # # # # # # #\n # # # # # # # #\n # # # # # # # #\n # # # # # # # #\n # # # # # # # #\n # # # # # # # #\n # # # # # # # #\n ```\n\n5. Print the following pattern:\n\n ```sh\n 0 x 0 = 0\n 1 x 1 = 1\n 2 x 2 = 4\n 3 x 3 = 9\n 4 x 4 = 16\n 5 x 5 = 25\n 6 x 6 = 36\n 7 x 7 = 49\n 8 x 8 = 64\n 9 x 9 = 81\n 10 x 10 = 100\n ```\n\n6. Iterate through the list, ['Python', 'Numpy','Pandas','Django', 'Flask'] using a for loop and print out the items.\n7. Use for loop to iterate from 0 to 100 and print only even numbers\n8. Use for loop to iterate from 0 to 100 and print only odd numbers\n\n### Exercises: Level 2\n\n1. Use for loop to iterate from 0 to 100 and print the sum of all numbers.\n\n```sh\nThe sum of all numbers is 5050.\n```\n\n2. Use for loop to iterate from 0 to 100 and print the sum of all evens and the sum of all odds.\n\n ```sh\n The sum of all evens is 2550. And the sum of all odds is 2500.\n ```\n\n### Exercises: Level 3\n\n1. Go to the data folder and use the [countries.py](https://github.com/Asabeneh/30-Days-Of-Python/blob/master/data/countries.py) file. Loop through the countries and extract all the countries containing the word _land_.\n1. This is a fruit list, ['banana', 'orange', 'mango', 'lemon'] reverse the order using loop.\n1. Go to the data folder and use the [countries_data.py](https://github.com/Asabeneh/30-Days-Of-Python/blob/master/data/countries-data.py) file.\n 1. What are the total number of languages in the data\n 2. Find the ten most spoken languages from the data\n 3. Find the 10 most populated countries in the world\n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 9](../09_Day_Conditionals/09_conditionals.md) | [Day 11 >>](../11_Day_Functions/11_functions.md)\n"
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"path": "11_Day_Functions/11_functions.md",
"content": "
\n\n[<< Day 10](../10_Day_Loops/10_loops.md) | [Day 12 >>](../12_Day_Modules/12_modules.md)\n\n\n\n- [📘 Day 11](#-day-11)\n - [Functions](#functions)\n - [Defining a Function](#defining-a-function)\n - [Declaring and Calling a Function](#declaring-and-calling-a-function)\n - [Function without Parameters](#function-without-parameters)\n - [Function Returning a Value - Part 1](#function-returning-a-value---part-1)\n - [Function with Parameters](#function-with-parameters)\n - [Passing Arguments with Key and Value](#passing-arguments-with-key-and-value)\n - [Function Returning a Value - Part 2](#function-returning-a-value---part-2)\n - [Function with Default Parameters](#function-with-default-parameters)\n - [Arbitrary Number of Arguments](#arbitrary-number-of-arguments)\n - [Default and Arbitrary Number of Parameters in Functions](#default-and-arbitrary-number-of-parameters-in-functions)\n - [Function as a Parameter of Another Function](#function-as-a-parameter-of-another-function)\n - [Testimony](#testimony)\n - [💻 Exercises: Day 11](#-exercises-day-11)\n - [Exercises: Level 1](#exercises-level-1)\n - [Exercises: Level 2](#exercises-level-2)\n - [Exercises: Level 3](#exercises-level-3)\n\n# 📘 Day 11\n\n## Functions\n\nSo far we have seen many built-in Python functions. In this section, we will focus on custom functions. What is a function? Before we start making functions, let us learn what a function is and why we need them?\n\n### Defining a Function\n\nA function is a reusable block of code or programming statements designed to perform a certain task. To define or declare a function, Python provides the _def_ keyword. The following is the syntax for defining a function. The function block of code is executed only if the function is called or invoked.\n\n### Declaring and Calling a Function\n\nWhen we make a function, we call it declaring a function. When we start using the it, we call it _calling_ or _invoking_ a function. Functions can be declared with or without parameters.\n\n```py\n# syntax\n# Declaring a function\ndef function_name():\n codes\n codes\n# Calling a function\nfunction_name()\n```\n\n### Function without Parameters\n\nFunction can be declared without parameters.\n\n**Example:**\n\n```py\ndef generate_full_name ():\n first_name = 'Asabeneh'\n last_name = 'Yetayeh'\n space = ' '\n full_name = first_name + space + last_name\n print(full_name)\ngenerate_full_name () # calling a function\n\ndef add_two_numbers ():\n num_one = 2\n num_two = 3\n total = num_one + num_two\n print(total)\nadd_two_numbers()\n```\n\n### Function Returning a Value - Part 1\n\nFunctions return values using the _return_ statement. If a function has no return statement, it returns None. Let us rewrite the above functions using return. From now on, we get a value from a function when we call the function and print it.\n\n```py\ndef generate_full_name ():\n first_name = 'Asabeneh'\n last_name = 'Yetayeh'\n space = ' '\n full_name = first_name + space + last_name\n return full_name\nprint(generate_full_name())\n\ndef add_two_numbers ():\n num_one = 2\n num_two = 3\n total = num_one + num_two\n return total\nprint(add_two_numbers())\n```\n\n### Function with Parameters\n\nIn a function we can pass different data types(number, string, boolean, list, tuple, dictionary or set) as parameters.\n\n- Single Parameter: If our function takes a parameter we should call our function with an argument\n\n```py\n # syntax\n # Declaring a function\n def function_name(parameter):\n codes\n codes\n # Calling function\n print(function_name(argument))\n```\n\n**Example:**\n\n```py\ndef greetings (name):\n message = name + ', welcome to Python for Everyone!'\n return message\n\nprint(greetings('Asabeneh'))\n\ndef add_ten(num):\n ten = 10\n return num + ten\nprint(add_ten(90))\n\ndef square_number(x):\n return x * x\nprint(square_number(2))\n\ndef area_of_circle (r):\n PI = 3.14\n area = PI * r ** 2\n return area\nprint(area_of_circle(10))\n\ndef sum_of_numbers(n):\n total = 0\n for i in range(n+1):\n total+=i\n return total\nprint(sum_of_numbers(10)) # 55\nprint(sum_of_numbers(100)) # 5050\n```\n\n- Two Parameter: A function may or may not have a parameter or parameters. A function may also have two or more parameters. If our function takes parameters we should call it with arguments. Let us check a function with two parameters:\n\n```py\n # syntax\n # Declaring a function\n def function_name(para1, para2):\n codes\n codes\n # Calling function\n print(function_name(arg1, arg2))\n```\n\n**Example:**\n\n```py\ndef generate_full_name (first_name, last_name):\n space = ' '\n full_name = first_name + space + last_name\n return full_name\nprint('Full Name: ', generate_full_name('Asabeneh','Yetayeh'))\n\ndef sum_two_numbers (num_one, num_two):\n sum = num_one + num_two\n return sum\nprint('Sum of two numbers: ', sum_two_numbers(1, 9))\n\ndef calculate_age (current_year, birth_year):\n age = current_year - birth_year\n return age \n\nprint('Age: ', calculate_age(2021, 1819))\n\ndef weight_of_object (mass, gravity):\n weight = str(mass * gravity)+ ' N' # the value has to be changed to a string first\n return weight\nprint('Weight of an object in Newtons: ', weight_of_object(100, 9.81))\n```\n\n### Passing Arguments with Key and Value\n\nIf we pass the arguments with key and value, the order of the arguments does not matter.\n\n```py\n# syntax\n# Declaring a function\ndef function_name(para1, para2):\n codes\n codes\n# Calling function\nprint(function_name(para1 = 'John', para2 = 'Doe')) # the order of arguments does not matter here\n```\n\n**Example:**\n\n```py\ndef print_fullname(firstname, lastname):\n space = ' '\n full_name = firstname + space + lastname\n print(full_name)\nprint_fullname(firstname = 'Asabeneh', lastname = 'Yetayeh')\n\ndef add_two_numbers (num1, num2):\n total = num1 + num2\n return total\nprint(add_two_numbers(num2 = 3, num1 = 2)) # Order does not matter \n```\n\n### Function Returning a Value - Part 2\n\nIf we do not return a value with a function, then our function is returning _None_ by default. To return a value with a function we use the keyword _return_ followed by the variable we are returning. We can return any kind of data types from a function.\n\n- Returning a string:\n**Example:**\n\n```py\ndef print_name(firstname):\n return firstname\nprint_name('Asabeneh') # Asabeneh\n\ndef print_full_name(firstname, lastname):\n space = ' '\n full_name = firstname + space + lastname\n return full_name\nprint_full_name(firstname='Asabeneh', lastname='Yetayeh')\n```\n\n- Returning a number:\n\n**Example:**\n\n```py\ndef add_two_numbers (num1, num2):\n total = num1 + num2\n return total\nprint(add_two_numbers(2, 3))\n\ndef calculate_age (current_year, birth_year):\n age = current_year - birth_year\n return age\nprint('Age: ', calculate_age(2019, 1819))\n```\n\n- Returning a boolean:\n **Example:**\n\n```py\ndef is_even (n):\n if n % 2 == 0:\n return True # return stops further execution of the function, similar to break \n return False\nprint(is_even(10)) # True\nprint(is_even(7)) # False\n```\n\n- Returning a list:\n **Example:**\n\n```py\ndef find_even_numbers(n):\n evens = []\n for i in range(n + 1):\n if i % 2 == 0:\n evens.append(i)\n return evens\nprint(find_even_numbers(10))\n```\n\n### Function with Default Parameters\n\nSometimes we pass default values to parameters, when we invoke the function. If we do not pass arguments when calling the function, their default values will be used.\n\n```py\n# syntax\n# Declaring a function\ndef function_name(param = value):\n codes\n codes\n# Calling function\nfunction_name()\nfunction_name(arg)\n```\n\n**Example:**\n\n```py\ndef greetings (name = 'Peter'):\n message = name + ', welcome to Python for Everyone!'\n return message\nprint(greetings())\nprint(greetings('Asabeneh'))\n\ndef generate_full_name (first_name = 'Asabeneh', last_name = 'Yetayeh'):\n space = ' '\n full_name = first_name + space + last_name\n return full_name\n\nprint(generate_full_name())\nprint(generate_full_name('David','Smith'))\n\ndef calculate_age (birth_year,current_year = 2021):\n age = current_year - birth_year\n return age \nprint('Age: ', calculate_age(1821))\n\ndef weight_of_object (mass, gravity = 9.81):\n weight = str(mass * gravity)+ ' N' # the value has to be changed to string first\n return weight\nprint('Weight of an object in Newtons: ', weight_of_object(100)) # 9.81 - average gravity on Earth's surface\nprint('Weight of an object in Newtons: ', weight_of_object(100, 1.62)) # gravity on the surface of the Moon\n```\n\n### Arbitrary Number of Arguments\n\nIf we do not know the number of arguments we pass to our function, we can create a function which can take arbitrary number of arguments by adding \\* before the parameter name.\n\n```py\n# syntax\n# Declaring a function\ndef function_name(*args):\n codes\n codes\n# Calling function\nfunction_name(param1, param2, param3,..)\n```\n\n**Example:**\n\n```py\ndef sum_all_nums(*nums):\n total = 0\n for num in nums:\n total += num # same as total = total + num \n return total\nprint(sum_all_nums(2, 3, 5)) # 10\n```\n\n### Default and Arbitrary Number of Parameters in Functions\n\n```py\ndef generate_groups (team,*args):\n print(team)\n for i in args:\n print(i) \ngenerate_groups('Team-1','Asabeneh','Brook','David','Eyob')\n```\n### Dictionary unpacking\n\nYou can call a function which has named arguments using a dictionary with matching key names. You do so using ``**``.\n\n```py\n# Define a function that takes two arguments: 'name' and 'location'\ndef greet(name, location):\n # Print a greeting message using the provided arguments\n print(\"Hi there\", name, \"how is the weather in\", location)\n\n# Call the function using keyword arguments\ngreet(name=\"Alice\", location=\"New York\") \n# Output: Hi there Alice how is the weather in New York\n\n# Create a dictionary with keys matching the function's parameter names\nmy_dict = {\"name\": \"Alice\", \"location\": \"New York\"}\n\n# Call the function using dictionary unpacking\ngreet(**my_dict) \n# The ** operator unpacks the dictionary, passing its key-value pairs \n# as keyword arguments to the function.\n# Output: Hi there Alice how is the weather in New York\n```\n\n### Arbitrary Number of Named Arguments\n\nYou can also define a function to accept an arbitrary number of named arguments.\n\n```py\ndef arbitrary_named_args(**args):\n print(\"I received an arbitrary number of arguments, totaling\", len(args))\n print(\"They are provided as a dictionary in my function:\", type(args))\n print(\"Let's print them:\")\n for k, v in args.items():\n print(\" * key:\", k, \"value:\", v)\n```\n\nGenerally avoid this unless required as it makes it harder to understand what the function accepts and does.\n\n### Function as a Parameter of Another Function\n\n```py\n#You can pass functions around as parameters\ndef square_number (n):\n return n ** n\ndef do_something(f, x):\n return f(x)\nprint(do_something(square_number, 3)) # 27\n```\n\n🌕 You achieved quite a lot so far. Keep going! You have just completed day 11 challenges and you are 11 steps a head in to your way to greatness. Now do some exercises for your brain and muscles.\n\n## Testimony\n\nNow it is time to express your thoughts about the Author and 30DaysOfPython. You can leave your testimonial on this [link](https://testimonial-s3sw.onrender.com/)\n\n## 💻 Exercises: Day 11\n\n### Exercises: Level 1\n\n1. Declare a function _add_two_numbers_. It takes two parameters and it returns a sum.\n2. Area of a circle is calculated as follows: area = π x r x r. Write a function that calculates _area_of_circle_.\n3. Write a function called add_all_nums which takes arbitrary number of arguments and sums all the arguments. Check if all the list items are number types. If not do give a reasonable feedback.\n4. Temperature in °C can be converted to °F using this formula: °F = (°C x 9/5) + 32. Write a function which converts °C to °F, _convert_celsius_to-fahrenheit_.\n5. Write a function called check-season, it takes a month parameter and returns the season: Autumn, Winter, Spring or Summer.\n6. Write a function called calculate_slope which return the slope of a linear equation\n7. Quadratic equation is calculated as follows: ax² + bx + c = 0. Write a function which calculates solution set of a quadratic equation, _solve_quadratic_eqn_.\n8. Declare a function named print_list. It takes a list as a parameter and it prints out each element of the list.\n9. Declare a function named reverse_list. It takes an array as a parameter and it returns the reverse of the array (use loops).\n\n```py\nprint(reverse_list([1, 2, 3, 4, 5]))\n# [5, 4, 3, 2, 1]\nprint(reverse_list([\"A\", \"B\", \"C\"])) \n# [\"C\", \"B\", \"A\"]\n```\n\n10. Declare a function named capitalize_list_items. It takes a list as a parameter and it returns a capitalized list of items\n11. Declare a function named add_item. It takes a list and an item parameters. It returns a list with the item added at the end.\n\n```py\nfood_stuff = ['Potato', 'Tomato', 'Mango', 'Milk'];\nprint(add_item(food_stuff, 'Meat')) # ['Potato', 'Tomato', 'Mango', 'Milk','Meat'];\nnumbers = [2, 3, 7, 9];\nprint(add_item(numbers, 5)) # [2, 3, 7, 9, 5]\n\n```\n\n12. Declare a function named remove_item. It takes a list and an item parameters. It returns a list with the item removed from it.\n\n```py\nfood_stuff = ['Potato', 'Tomato', 'Mango', 'Milk']\nprint(remove_item(food_stuff, 'Mango')) # ['Potato', 'Tomato', 'Milk'];\nnumbers = [2, 3, 7, 9]\nprint(remove_item(numbers, 3)) # [2, 7, 9]\n```\n\n13. Declare a function named sum_of_numbers. It takes a number parameter and it adds all the numbers in that range.\n\n```py\nprint(sum_of_numbers(5)) # 15\nprint(sum_of_numbers(10)) # 55\nprint(sum_of_numbers(100)) # 5050\n```\n\n14. Declare a function named sum_of_odds. It takes a number parameter and it adds all the odd numbers in that range.\n15. Declare a function named sum_of_even. It takes a number parameter and it adds all the even numbers in that - range.\n\n### Exercises: Level 2\n\n1. Declare a function named evens_and_odds . It takes a positive integer as parameter and it counts number of evens and odds in the number.\n\n```py\n print(evens_and_odds(100))\n # The number of odds are 50.\n # The number of evens are 51.\n```\n\n1. Call your function factorial, it takes a whole number as a parameter and it return a factorial of the number\n1. Call your function _is_empty_, it takes a parameter and it checks if it is empty or not\n1. Write different functions which take lists. They should calculate_mean, calculate_median, calculate_mode, calculate_range, calculate_variance, calculate_std (standard deviation).\n1. Write a function called _greet_ which takes a default argument, _name_. If no argument is supplied it should print \"Hello, Guest!\", otherwise it should greet the person by name.\n\n```py\n greet()\n # \"Hello, Guest!\n greet(\"Alice\")\n # \"Hello, Alice!\"\n```\n1. Create a function called _show_args_ to take an arbitrary number of named arguments and print their names and values.\n ```py\n show_args(name=\"Alice\", age=30, city=\"New York\")\n # Received: name: Alice, age: 30, city: New York\n show_args(name=\"Bob\", pet=\"Fluffy, the bunny\")\n # Received: name: Bob, pet: Fluffy, the bunny\n ```\n\n\n### Exercises: Level 3\n\n1. Write a function called is_prime, which checks if a number is prime.\n1. Write a functions which checks if all items are unique in the list.\n1. Write a function which checks if all the items of the list are of the same data type.\n1. Write a function which check if provided variable is a valid python variable\n1. Go to the data folder and access the countries-data.py file.\n\n- Create a function called the most_spoken_languages in the world. It should return 10 or 20 most spoken languages in the world in descending order\n- Create a function called the most_populated_countries. It should return 10 or 20 most populated countries in descending order.\n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 10](../10_Day_Loops/10_loops.md) | [Day 12 >>](../12_Day_Modules/12_modules.md)\n"
},
{
"path": "12_Day_Modules/12_modules.md",
"content": "
\n\n[<< Day 11](../11_Day_Functions/11_functions.md) | [Day 13>>](../13_Day_List_comprehension/13_list_comprehension.md)\n\n\n\n- [📘 Day 12](#-day-12)\n - [Modules](#modules)\n - [What is a Module](#what-is-a-module)\n - [Creating a Module](#creating-a-module)\n - [Importing a Module](#importing-a-module)\n - [Import Functions from a Module](#import-functions-from-a-module)\n - [Import Functions from a Module and Renaming](#import-functions-from-a-module-and-renaming)\n - [Import Built-in Modules](#import-built-in-modules)\n - [OS Module](#os-module)\n - [Sys Module](#sys-module)\n - [Statistics Module](#statistics-module)\n - [Math Module](#math-module)\n - [String Module](#string-module)\n - [Random Module](#random-module)\n - [💻 Exercises: Day 12](#-exercises-day-12)\n - [Exercises: Level 1](#exercises-level-1)\n - [Exercises: Level 2](#exercises-level-2)\n - [Exercises: Level 3](#exercises-level-3)\n\n# 📘 Day 12\n\n## Modules\n\n### What is a Module\n\nA module is a file containing a set of codes or a set of functions which can be included to an application. A module could be a file containing a single variable, a function or a big code base.\n\n### Creating a Module\n\nTo create a module we write our codes in a python script and we save it as a .py file. Create a file named mymodule.py inside your project folder. Let us write some code in this file.\n\n```py\n# mymodule.py file\ndef generate_full_name(firstname, lastname):\n return firstname + ' ' + lastname\n```\n\nCreate main.py file in your project directory and import the mymodule.py file.\n\n### Importing a Module\n\nTo import the file we use the _import_ keyword and the name of the file only.\n\n```py\n# main.py file\nimport mymodule\nprint(mymodule.generate_full_name('Asabeneh', 'Yetayeh')) # Asabeneh Yetayeh\n```\n\n### Import Functions from a Module\n\nWe can have many functions in a file and we can import all the functions differently.\n\n```py\n# main.py file\nfrom mymodule import generate_full_name, sum_two_nums, person, gravity\nprint(generate_full_name('Asabneh','Yetayeh'))\nprint(sum_two_nums(1,9))\nmass = 100\nweight = mass * gravity\nprint(weight)\nprint(person['firstname'])\n```\n\n### Import Functions from a Module and Renaming\n\nDuring importing we can rename the name of the module.\n\n```py\n# main.py file\nfrom mymodule import generate_full_name as fullname, sum_two_nums as total, person as p, gravity as g\nprint(fullname('Asabneh','Yetayeh'))\nprint(total(1, 9))\nmass = 100 \nweight = mass * g\nprint(weight)\nprint(p)\nprint(p['firstname'])\n```\n\n## Import Built-in Modules\n\nLike other programming languages we can also import modules by importing the file/function using the key word _import_. Let's import the common module we will use most of the time. Some of the common built-in modules: _math_, _datetime_, _os_,_sys_, _random_, _statistics_, _collections_, _json_,_re_\n\n### OS Module\n\nUsing python _os_ module it is possible to automatically perform many operating system tasks. The OS module in Python provides functions for creating, changing current working directory, and removing a directory (folder), fetching its contents, changing and identifying the current directory.\n\n```py\n# import the module\nimport os\n# Creating a directory\nos.mkdir('directory_name')\n# Changing the current directory\nos.chdir('path')\n# Getting current working directory\nos.getcwd()\n# Removing directory\nos.rmdir()\n```\n\n### Sys Module\n\nThe sys module provides functions and variables used to manipulate different parts of the Python runtime environment. Function sys.argv returns a list of command line arguments passed to a Python script. The item at index 0 in this list is always the name of the script, at index 1 is the argument passed from the command line.\n\nExample of a script.py file:\n\n```py\nimport sys\n#print(sys.argv[0], argv[1],sys.argv[2]) # this line would print out: filename argument1 argument2\nprint('Welcome {}. Enjoy {} challenge!'.format(sys.argv[1], sys.argv[2]))\n```\n\nNow to check how this script works I wrote in command line:\n\n```sh\npython script.py Asabeneh 30DaysOfPython\n```\n\nThe result:\n\n```sh\nWelcome Asabeneh. Enjoy 30DayOfPython challenge! \n```\n\nSome useful sys commands:\n\n```py\n# to exit sys\nsys.exit()\n# To know the largest integer variable it takes\nsys.maxsize\n# To know environment path\nsys.path\n# To know the version of python you are using\nsys.version\n```\n\n### Statistics Module\n\nThe statistics module provides functions for mathematical statistics of numeric data. The popular statistical functions which are defined in this module: _mean_, _median_, _mode_, _stdev_ etc.\n\n```py\nfrom statistics import * # importing all the statistics modules\nages = [20, 20, 4, 24, 25, 22, 26, 20, 23, 22, 26]\nprint(mean(ages)) # ~22.9\nprint(median(ages)) # 23\nprint(mode(ages)) # 20\nprint(stdev(ages)) # ~2.3\n```\n\n### Math Module\n\nModule containing many mathematical operations and constants.\n\n```py\nimport math\nprint(math.pi) # 3.141592653589793, pi constant\nprint(math.sqrt(2)) # 1.4142135623730951, square root\nprint(math.pow(2, 3)) # 8.0, exponential function\nprint(math.floor(9.81)) # 9, rounding to the lowest\nprint(math.ceil(9.81)) # 10, rounding to the highest\nprint(math.log10(100)) # 2, logarithm with 10 as base\n```\n\nNow, we have imported the *math* module which contains lots of function which can help us to perform mathematical calculations. To check what functions the module has got, we can use _help(math)_, or _dir(math)_. This will display the available functions in the module. If we want to import only a specific function from the module we import it as follows:\n\n```py\nfrom math import pi\nprint(pi)\n```\n\nIt is also possible to import multiple functions at once\n\n```py\n\nfrom math import pi, sqrt, pow, floor, ceil, log10\nprint(pi) # 3.141592653589793\nprint(sqrt(2)) # 1.4142135623730951\nprint(pow(2, 3)) # 8.0\nprint(floor(9.81)) # 9\nprint(ceil(9.81)) # 10\nprint(math.log10(100)) # 2\n\n```\n\nBut if we want to import all the function in math module we can use \\* .\n\n```py\nfrom math import *\nprint(pi) # 3.141592653589793, pi constant\nprint(sqrt(2)) # 1.4142135623730951, square root\nprint(pow(2, 3)) # 8.0, exponential\nprint(floor(9.81)) # 9, rounding to the lowest\nprint(ceil(9.81)) # 10, rounding to the highest\nprint(math.log10(100)) # 2\n```\n\nWhen we import we can also rename the name of the function.\n\n```py\nfrom math import pi as PI\nprint(PI) # 3.141592653589793\n```\n\n### String Module\n\nA string module is a useful module for many purposes. The example below shows some use of the string module.\n\n```py\nimport string\nprint(string.ascii_letters) # abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ\nprint(string.digits) # 0123456789\nprint(string.punctuation) # !\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~\n```\n\n### Random Module\n\nBy now you are familiar with importing modules. Let us do one more import to get very familiar with it. Let us import _random_ module which gives us a random number between 0 and 0.9999.... The _random_ module has lots of functions but in this section we will only use _random_ and _randint_.\n\n```py\nfrom random import random, randint\nprint(random()) # it doesn't take any arguments; it returns a value between 0 and 0.9999\nprint(randint(5, 20)) # it returns a random integer number between [5, 20] inclusive\n```\n\n🌕 You are going far. Keep going! You have just completed day 12 challenges and you are 12 steps a head in to your way to greatness. Now do some exercises for your brain and muscles.\n\n## 💻 Exercises: Day 12\n\n### Exercises: Level 1\n\n1. Write a function which generates a six digit/character random_user_id. \n ```py\n print(random_user_id()) \n '1ee33d'\n ```\n2. Modify the previous task. Declare a function named user_id_gen_by_user. It doesn’t take any parameters but it takes two inputs using input(). One of the inputs is the number of characters and the second input is the number of IDs which are supposed to be generated.\n \n```py\nprint(user_id_gen_by_user()) # user input: 5 5\n#output:\n#kcsy2\n#SMFYb\n#bWmeq\n#ZXOYh\n#2Rgxf\n \nprint(user_id_gen_by_user()) # 16 5\n#1GCSgPLMaBAVQZ26\n#YD7eFwNQKNs7qXaT\n#ycArC5yrRupyG00S\n#UbGxOFI7UXSWAyKN\n#dIV0SSUTgAdKwStr\n```\n\n3. Write a function named rgb_color_gen. It will generate rgb colors (3 values ranging from 0 to 255 each).\n \n```py\nprint(rgb_color_gen())\n# rgb(125,244,255) - the output should be in this form\n```\n\n### Exercises: Level 2\n\n1. Write a function list_of_hexa_colors which returns any number of hexadecimal colors in an array (six hexadecimal numbers written after #. Hexadecimal numeral system is made out of 16 symbols, 0-9 and first 6 letters of the alphabet, a-f. Check the task 6 for output examples).\n1. Write a function list_of_rgb_colors which returns any number of RGB colors in an array.\n1. Write a function generate_colors which can generate any number of hexa or rgb colors.\n\n```py\n generate_colors('hexa', 3) # ['#a3e12f','#03ed55','#eb3d2b'] \n generate_colors('hexa', 1) # ['#b334ef']\n generate_colors('rgb', 3) # ['rgb(5, 55, 175','rgb(50, 105, 100','rgb(15, 26, 80'] \n generate_colors('rgb', 1) # ['rgb(33,79, 176)']\n ```\n\n### Exercises: Level 3\n\n1. Call your function shuffle_list, it takes a list as a parameter and it returns a shuffled list\n1. Write a function which returns an array of seven random numbers in a range of 0-9. All the numbers must be unique.\n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 11](../11_Day_Functions/11_functions.md) | [Day 13>>](../13_Day_List_comprehension/13_list_comprehension.md)\n"
},
{
"path": "12_Day_Modules/main.py",
"content": "\nfrom mymodule import generate_full_name as fullname, sum_two_nums as total, person as p, gravity as g\nprint(fullname('Asabneh','Yetayeh'))\nprint(total(1, 9))\nmass = 100\nprint(mass)\nweight = mass * g\nprint(weight)\nprint(p)\nprint(p['firstname'])"
},
{
"path": "12_Day_Modules/mymodule.py",
"content": "def generate_full_name(firstname, lastname):\n space = ' '\n fullname = firstname + space + lastname\n return fullname\n\ndef sum_two_nums (num1, num2):\n return num1 + num2\ngravity = 9.81\nperson = {\n \"firstname\": \"Asabeneh\",\n \"age\": 250,\n \"country\": \"Finland\",\n \"city\":'Helsinki'\n}\n\n\n"
},
{
"path": "13_Day_List_comprehension/13_list_comprehension.md",
"content": "
\n\n[<< Day 12](../12_Day_Modules/12_modules.md) | [Day 14>>](../14_Day_Higher_order_functions/14_higher_order_functions.md)\n\n\n\n- [📘 Day 13](#-day-13)\n - [List Comprehension](#list-comprehension)\n - [Lambda Function](#lambda-function)\n - [Creating a Lambda Function](#creating-a-lambda-function)\n - [Lambda Function Inside Another Function](#lambda-function-inside-another-function)\n - [💻 Exercises: Day 13](#-exercises-day-13)\n\n# 📘 Day 13\n\n## List Comprehension\n\nList comprehension in Python is a compact way of creating a list from a sequence. It is a short way to create a new list. List comprehension is considerably faster than processing a list using the _for_ loop.\n\n```py\n# syntax\n[expression for i in iterable if condition]\n```\n\n**Example:1**\n\nFor instance if you want to change a string to a list of characters. You can use a couple of methods. Let's see some of them:\n\n```py\n# One way\nlanguage = 'Python'\nlst = list(language) # changing the string to list\nprint(type(lst)) # list\nprint(lst) # ['P', 'y', 't', 'h', 'o', 'n']\n\n# Second way: list comprehension\nlst = [i for i in language]\nprint(type(lst)) # list\nprint(lst) # ['P', 'y', 't', 'h', 'o', 'n']\n\n```\n\n**Example:2**\n\nFor instance if you want to generate a list of numbers\n\n```py\n# Generating numbers\nnumbers = [i for i in range(11)] # to generate numbers from 0 to 10\nprint(numbers) # [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\n\n# It is possible to do mathematical operations during iteration\nsquares = [i * i for i in range(11)]\nprint(squares) # [0, 1, 4, 9, 16, 25, 36, 49, 64, 81, 100]\n\n# It is also possible to make a list of tuples\nnumbers = [(i, i * i) for i in range(11)]\nprint(numbers) # [(0, 0), (1, 1), (2, 4), (3, 9), (4, 16), (5, 25)]\n\n```\n\n**Example:2**\n\nList comprehension can be combined with if expression\n\n\n```py\n# Generating even numbers\neven_numbers = [i for i in range(21) if i % 2 == 0] # to generate even numbers list in range 0 to 21\nprint(even_numbers) # [0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20]\n\n# Generating odd numbers\nodd_numbers = [i for i in range(21) if i % 2 != 0] # to generate odd numbers in range 0 to 21\nprint(odd_numbers) # [1, 3, 5, 7, 9, 11, 13, 15, 17, 19]\n# Filter numbers: let's filter out positive even numbers from the list below\nnumbers = [-8, -7, -3, -1, 0, 1, 3, 4, 5, 7, 6, 8, 10]\npositive_even_numbers = [i for i in numbers if i % 2 == 0 and i > 0]\nprint(positive_even_numbers) # [2, 4, 6, 8, 10, 12, 14, 16, 18, 20]\n\n# Flattening a two dimensional array\nlist_of_lists = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]\nflattened_list = [ number for row in list_of_lists for number in row]\nprint(flattened_list) # [1, 2, 3, 4, 5, 6, 7, 8, 9]\n```\n\n## Lambda Function\n\nLambda function is a small anonymous function without a name. It can take any number of arguments, but can only have one expression. Lambda function is similar to anonymous functions in JavaScript. We need it when we want to write an anonymous function inside another function.\n\n### Creating a Lambda Function\n\nTo create a lambda function we use _lambda_ keyword followed by a parameter(s), followed by an expression. See the syntax and the example below. Lambda function does not use return but it explicitly returns the expression.\n\n```py\n# syntax\nx = lambda param1, param2, param3: param1 + param2 + param3\nprint(x(arg1, arg2, arg3))\n```\n\n**Example:**\n\n```py\n# Named function\ndef add_two_nums(a, b):\n return a + b\n\nprint(add_two_nums(2, 3)) # 5\n# Lets change the above function to a lambda function\nadd_two_nums = lambda a, b: a + b\nprint(add_two_nums(2,3)) # 5\n\n# Self invoking lambda function\n(lambda a, b: a + b)(2,3) # 5 - need to encapsulate it in print() to see the result in the console\n\nsquare = lambda x : x ** 2\nprint(square(3)) # 9\ncube = lambda x : x ** 3\nprint(cube(3)) # 27\n\n# Multiple variables\nmultiple_variable = lambda a, b, c: a ** 2 - 3 * b + 4 * c\nprint(multiple_variable(5, 5, 3)) # 22\n```\n\n### Lambda Function Inside Another Function\n\nUsing a lambda function inside another function.\n\n```py\ndef power(x):\n return lambda n : x ** n\n\ncube = power(2)(3) # function power now need 2 arguments to run, in separate rounded brackets\nprint(cube) # 8\ntwo_power_of_five = power(2)(5) \nprint(two_power_of_five) # 32\n```\n\n🌕 Keep up the good work. Keep the momentum going, the sky is the limit! You have just completed day 13 challenges and you are 13 steps a head in to your way to greatness. Now do some exercises for your brain and muscles.\n\n## 💻 Exercises: Day 13\n\n1. Filter only negative and zero in the list using list comprehension\n ```py\n numbers = [-4, -3, -2, -1, 0, 2, 4, 6]\n ```\n2. Flatten the following list of lists of lists to a one dimensional list :\n\n ```py\n list_of_lists =[[1, 2, 3], [4, 5, 6], [7, 8, 9]]\n\n output\n [1, 2, 3, 4, 5, 6, 7, 8, 9]\n ```\n\n3. Using list comprehension create the following list of tuples:\n ```py\n [(0, 1, 0, 0, 0, 0, 0),\n (1, 1, 1, 1, 1, 1, 1),\n (2, 1, 2, 4, 8, 16, 32),\n (3, 1, 3, 9, 27, 81, 243),\n (4, 1, 4, 16, 64, 256, 1024),\n (5, 1, 5, 25, 125, 625, 3125),\n (6, 1, 6, 36, 216, 1296, 7776),\n (7, 1, 7, 49, 343, 2401, 16807),\n (8, 1, 8, 64, 512, 4096, 32768),\n (9, 1, 9, 81, 729, 6561, 59049),\n (10, 1, 10, 100, 1000, 10000, 100000)]\n ```\n4. Flatten the following list to a new list:\n ```py\n countries = [[('Finland', 'Helsinki')], [('Sweden', 'Stockholm')], [('Norway', 'Oslo')]]\n output:\n [['FINLAND','FIN', 'HELSINKI'], ['SWEDEN', 'SWE', 'STOCKHOLM'], ['NORWAY', 'NOR', 'OSLO']]\n ```\n5. Change the following list to a list of dictionaries:\n ```py\n countries = [[('Finland', 'Helsinki')], [('Sweden', 'Stockholm')], [('Norway', 'Oslo')]]\n output:\n [{'country': 'FINLAND', 'city': 'HELSINKI'},\n {'country': 'SWEDEN', 'city': 'STOCKHOLM'},\n {'country': 'NORWAY', 'city': 'OSLO'}]\n ```\n6. Change the following list of lists to a list of concatenated strings:\n ```py\n names = [[('Asabeneh', 'Yetayeh')], [('David', 'Smith')], [('Donald', 'Trump')], [('Bill', 'Gates')]]\n output\n ['Asabeneh Yetaeyeh', 'David Smith', 'Donald Trump', 'Bill Gates']\n ```\n7. Write a lambda function which can solve a slope or y-intercept of linear functions.\n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 12](../12_Day_Modules/12_modules.md) | [Day 14>>](../14_Day_Higher_order_functions/14_higher_order_functions.md)\n"
},
{
"path": "14_Day_Higher_order_functions/14_higher_order_functions.md",
"content": "
\n
30 Days Of Python: Day 14 - Higher Order Functions
\n\n[<< Day 13](../13_Day_List_comprehension/13_list_comprehension.md) | [Day 15>>](../15_Day_Python_type_errors/15_python_type_errors.md)\n\n\n- [📘 Day 14](#-day-14)\n - [Higher Order Functions](#higher-order-functions)\n - [Function as a Parameter](#function-as-a-parameter)\n - [Function as a Return Value](#function-as-a-return-value)\n - [Python Closures](#python-closures)\n - [Python Decorators](#python-decorators)\n - [Creating Decorators](#creating-decorators)\n - [Applying Multiple Decorators to a Single Function](#applying-multiple-decorators-to-a-single-function)\n - [Accepting Parameters in Decorator Functions](#accepting-parameters-in-decorator-functions)\n - [Built-in Higher Order Functions](#built-in-higher-order-functions)\n - [Python - Map Function](#python---map-function)\n - [Python - Filter Function](#python---filter-function)\n - [Python - Reduce Function](#python---reduce-function)\n - [💻 Exercises: Day 14](#-exercises-day-14)\n - [Exercises: Level 1](#exercises-level-1)\n - [Exercises: Level 2](#exercises-level-2)\n - [Exercises: Level 3](#exercises-level-3)\n\n# 📘 Day 14\n\n## Higher Order Functions\n\nIn Python functions are treated as first class citizens, allowing you to perform the following operations on functions:\n\n- A function can take one or more functions as parameters\n- A function can be returned as a result of another function\n- A function can be modified\n- A function can be assigned to a variable\n\nIn this section, we will cover:\n\n1. Handling functions as parameters\n2. Returning functions as return value from another functions\n3. Using Python closures and decorators\n\n### Function as a Parameter\n\n```py\ndef sum_numbers(nums): # normal function\n return sum(nums) # a sad function abusing the built-in sum function :<\n\ndef higher_order_function(f, lst): # function as a parameter\n summation = f(lst)\n return summation\nresult = higher_order_function(sum_numbers, [1, 2, 3, 4, 5])\nprint(result) # 15\n```\n\n### Function as a Return Value\n\n```py\ndef square(x): # a square function\n return x ** 2\n\ndef cube(x): # a cube function\n return x ** 3\n\ndef absolute(x): # an absolute value function\n if x >= 0:\n return x\n else:\n return -(x)\n\ndef higher_order_function(type): # a higher order function returning a function\n if type == 'square':\n return square\n elif type == 'cube':\n return cube\n elif type == 'absolute':\n return absolute\n\nresult = higher_order_function('square')\nprint(result(3)) # 9\nresult = higher_order_function('cube')\nprint(result(3)) # 27\nresult = higher_order_function('absolute')\nprint(result(-3)) # 3\n```\n\nYou can see from the above example that the higher order function is returning different functions depending on the passed parameter\n\n## Python Closures\n\nPython allows a nested function to access the outer scope of the enclosing function. This is is known as a Closure. Let us have a look at how closures work in Python. In Python, closure is created by nesting a function inside another encapsulating function and then returning the inner function. See the example below.\n\n**Example:**\n\n```py\ndef add_ten():\n ten = 10\n def add(num):\n return num + ten\n return add\n\nclosure_result = add_ten()\nprint(closure_result(5)) # 15\nprint(closure_result(10)) # 20\n```\n\n## Python Decorators\n\nA decorator is a design pattern in Python that allows a user to add new functionality to an existing object without modifying its structure. Decorators are usually called before the definition of a function you want to decorate.\n\n### Creating Decorators\n\nTo create a decorator function, we need an outer function with an inner wrapper function.\n\n**Example:**\n\n```py\n# Normal function\ndef greeting():\n return 'Welcome to Python'\ndef uppercase_decorator(function):\n def wrapper():\n func = function()\n make_uppercase = func.upper()\n return make_uppercase\n return wrapper\ng = uppercase_decorator(greeting)\nprint(g()) # WELCOME TO PYTHON\n\n## Let us implement the example above with a decorator\n\n'''This decorator function is a higher order function\nthat takes a function as a parameter'''\ndef uppercase_decorator(function):\n def wrapper():\n func = function()\n make_uppercase = func.upper()\n return make_uppercase\n return wrapper\n@uppercase_decorator\ndef greeting():\n return 'Welcome to Python'\nprint(greeting()) # WELCOME TO PYTHON\n\n```\n\n### Applying Multiple Decorators to a Single Function\n\n```py\n\n'''These decorator functions are higher order functions\nthat take functions as parameters'''\n\n# First Decorator\ndef uppercase_decorator(function):\n def wrapper():\n func = function()\n make_uppercase = func.upper()\n return make_uppercase\n return wrapper\n\n# Second decorator\ndef split_string_decorator(function):\n def wrapper():\n func = function()\n splitted_string = func.split()\n return splitted_string\n return wrapper\n\n#Decorators will be executed from bottom to top\n@split_string_decorator\n@uppercase_decorator # order with decorators is important in this case - .upper() function does not work with lists\ndef greeting():\n return 'Welcome to Python'\nprint(greeting()) # ['WELCOME', 'TO', 'PYTHON']\n```\n\n### Accepting Parameters in Decorator Functions\n\nMost of the time we need our functions to take parameters, so we might need to define a decorator that accepts parameters.\n\n```py\ndef decorator_with_parameters(function):\n def wrapper_accepting_parameters(para1, para2, para3):\n function(para1, para2, para3)\n print(\"I live in {}\".format(para3))\n return wrapper_accepting_parameters\n\n@decorator_with_parameters\ndef print_full_name(first_name, last_name, country):\n print(\"I am {} {}. I love to teach.\".format(\n first_name, last_name))\n\nprint_full_name(\"Asabeneh\", \"Yetayeh\",'Finland')\n```\n\n## Built-in Higher Order Functions\n\nSome of the built-in higher order functions that we cover in this part are _map()_, _filter_, and _reduce_.\nLambda function can be passed as a parameter and the best use case of lambda functions is in functions like map, filter and reduce.\n\n### Python - Map Function\n\nThe map() function is a built-in function that takes a function and iterable as parameters.\n\n```py\n # syntax\n map(function, iterable)\n```\n\n**Example:1**\n\n```py\nnumbers = [1, 2, 3, 4, 5] # iterable\ndef square(x):\n return x ** 2\nnumbers_squared = map(square, numbers)\nprint(list(numbers_squared)) # [1, 4, 9, 16, 25]\n# Lets apply it with a lambda function\nnumbers_squared = map(lambda x : x ** 2, numbers)\nprint(list(numbers_squared)) # [1, 4, 9, 16, 25]\n```\n\n**Example:2**\n\n```py\nnumbers_str = ['1', '2', '3', '4', '5'] # iterable\nnumbers_int = map(int, numbers_str)\nprint(list(numbers_int)) # [1, 2, 3, 4, 5]\n```\n\n**Example:3**\n\n```py\nnames = ['Asabeneh', 'Lidiya', 'Ermias', 'Abraham'] # iterable\n\ndef change_to_upper(name):\n return name.upper()\n\nnames_upper_cased = map(change_to_upper, names)\nprint(list(names_upper_cased)) # ['ASABENEH', 'LIDIYA', 'ERMIAS', 'ABRAHAM']\n\n# Let us apply it with a lambda function\nnames_upper_cased = map(lambda name: name.upper(), names)\nprint(list(names_upper_cased)) # ['ASABENEH', 'LIDIYA', 'ERMIAS', 'ABRAHAM']\n```\n\nWhat actually map does is iterating over a list. For instance, it changes the names to upper case and returns a new list.\n\n### Python - Filter Function\n\nThe filter() function calls the specified function which returns boolean for each item of the specified iterable (list). It filters the items that satisfy the filtering criteria.\n\n```py\n # syntax\n filter(function, iterable)\n```\n\n**Example:1**\n\n```py\n# Lets filter only even nubers\nnumbers = [1, 2, 3, 4, 5] # iterable\n\ndef is_even(num):\n if num % 2 == 0:\n return True\n return False\n\neven_numbers = filter(is_even, numbers)\nprint(list(even_numbers)) # [2, 4]\n```\n\n**Example:2**\n\n```py\nnumbers = [1, 2, 3, 4, 5] # iterable\n\ndef is_odd(num):\n if num % 2 != 0:\n return True\n return False\n\nodd_numbers = filter(is_odd, numbers)\nprint(list(odd_numbers)) # [1, 3, 5]\n```\n\n```py\n# Filter long name\nnames = ['Asabeneh', 'Lidiya', 'Ermias', 'Abraham'] # iterable\ndef is_name_long(name):\n if len(name) > 7:\n return True\n return False\n\nlong_names = filter(is_name_long, names)\nprint(list(long_names)) # ['Asabeneh']\n```\n\n### Python - Reduce Function\n\nThe _reduce()_ function is defined in the functools module and we should import it from this module. Like map and filter it takes two parameters, a function and an iterable. However, it does not return another iterable, instead it returns a single value.\n**Example:1**\n\n```py\nnumbers_str = ['1', '2', '3', '4', '5'] # iterable\ndef add_two_nums(x, y):\n return int(x) + int(y)\n\ntotal = reduce(add_two_nums, numbers_str)\nprint(total) # 15\n```\n\n## 💻 Exercises: Day 14\n\n```py\ncountries = ['Estonia', 'Finland', 'Sweden', 'Denmark', 'Norway', 'Iceland']\nnames = ['Asabeneh', 'Lidiya', 'Ermias', 'Abraham']\nnumbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\n```\n\n### Exercises: Level 1\n\n1. Explain the difference between map, filter, and reduce.\n2. Explain the difference between higher order function, closure and decorator\n3. Define a call function before map, filter or reduce, see examples.\n4. Use for loop to print each country in the countries list.\n5. Use for to print each name in the names list.\n6. Use for to print each number in the numbers list.\n\n### Exercises: Level 2\n\n1. Use map to create a new list by changing each country to uppercase in the countries list\n1. Use map to create a new list by changing each number to its square in the numbers list\n1. Use map to change each name to uppercase in the names list\n1. Use filter to filter out countries containing 'land'.\n1. Use filter to filter out countries having exactly six characters.\n1. Use filter to filter out countries containing six letters and more in the country list.\n1. Use filter to filter out countries starting with an 'E'\n1. Chain two or more list iterators (eg. arr.map(callback).filter(callback).reduce(callback))\n1. Declare a function called get_string_lists which takes a list as a parameter and then returns a list containing only string items.\n1. Use reduce to sum all the numbers in the numbers list.\n1. Use reduce to concatenate all the countries and to produce this sentence: Estonia, Finland, Sweden, Denmark, Norway, and Iceland are north European countries\n1. Declare a function called categorize_countries that returns a list of countries with some common pattern (you can find the [countries list](https://github.com/Asabeneh/30-Days-Of-Python/blob/master/data/countries.py) in this repository as countries.js(eg 'land', 'ia', 'island', 'stan')).\n1. Create a function returning a dictionary, where keys stand for starting letters of countries and values are the number of country names starting with that letter.\n2. Declare a get_first_ten_countries function - it returns a list of first ten countries from the countries.js list in the data folder.\n1. Declare a get_last_ten_countries function that returns the last ten countries in the countries list.\n\n### Exercises: Level 3\n\n1. Use the countries_data.py (https://github.com/Asabeneh/30-Days-Of-Python/blob/master/data/countries-data.py) file and follow the tasks below:\n - Sort countries by name, by capital, by population\n - Sort out the ten most spoken languages by location.\n - Sort out the ten most populated countries.\n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 13](../13_Day_List_comprehension/13_list_comprehension.md) | [Day 15>>](../15_Day_Python_type_errors/15_python_type_errors.md)"
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\n\n[<< Day 14](../14_Day_Higher_order_functions/14_higher_order_functions.md) | [Day 16 >>](../16_Day_Python_date_time/16_python_datetime.md)\n\n\n- [📘 Day 15](#-day-15)\n - [Python Error Types](#python-error-types)\n - [SyntaxError](#syntaxerror)\n - [NameError](#nameerror)\n - [IndexError](#indexerror)\n - [ModuleNotFoundError](#modulenotfounderror)\n - [AttributeError](#attributeerror)\n - [KeyError](#keyerror)\n - [TypeError](#typeerror)\n - [ImportError](#importerror)\n - [ValueError](#valueerror)\n - [ZeroDivisionError](#zerodivisionerror)\n - [💻 Exercises: Day 15](#-exercises-day-15)\n\n# 📘 Day 15\n\n## Python Error Types\n\nWhen we write code it is common that we make a typo or some other common error. If our code fails to run, the Python interpreter will display a message, containing feedback with information on where the problem occurs and the type of an error. It will also sometimes gives us suggestions on a possible fix. Understanding different types of errors in programming languages will help us to debug our code quickly and also it makes us better at what we do.\n\nLet us see the most common error types one by one. First let us open our Python interactive shell. Go to your you computer terminal and write 'python'. The python interactive shell will be opened.\n\n### SyntaxError\n\n**Example 1: SyntaxError**\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> print 'hello world'\n File \"\", line 1\n print 'hello world'\n ^\nSyntaxError: Missing parentheses in call to 'print'. Did you mean print('hello world')?\n>>>\n```\n\nAs you can see we made a syntax error because we forgot to enclose the string with parenthesis and Python already suggests the solution. Let us fix it.\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> print 'hello world'\n File \"\", line 1\n print 'hello world'\n ^\nSyntaxError: Missing parentheses in call to 'print'. Did you mean print('hello world')?\n>>> print('hello world')\nhello world\n>>>\n```\n\nThe error was a _SyntaxError_. After the fix our code was executed without a hitch. Let see more error types.\n\n### NameError\n\n**Example 1: NameError**\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> print(age)\nTraceback (most recent call last):\n File \"\", line 1, in \nNameError: name 'age' is not defined\n>>>\n```\n\nAs you can see from the message above, name age is not defined. Yes, it is true that we did not define an age variable but we were trying to print it out as if we had had declared it. Now, lets fix this by declaring it and assigning with a value.\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> print(age)\nTraceback (most recent call last):\n File \"\", line 1, in \nNameError: name 'age' is not defined\n>>> age = 25\n>>> print(age)\n25\n>>>\n```\n\nThe type of error was a _NameError_. We debugged the error by defining the variable name.\n\n### IndexError\n\n**Example 1: IndexError**\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> numbers = [1, 2, 3, 4, 5]\n>>> numbers[5]\nTraceback (most recent call last):\n File \"\", line 1, in \nIndexError: list index out of range\n>>>\n```\n\nIn the example above, Python raised an _IndexError_, because the list has only indexes from 0 to 4 , so it was out of range.\n\n### ModuleNotFoundError\n\n**Example 1: ModuleNotFoundError**\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> import maths\nTraceback (most recent call last):\n File \"\", line 1, in \nModuleNotFoundError: No module named 'maths'\n>>>\n```\n\nIn the example above, I added an extra s to math deliberately and _ModuleNotFoundError_ was raised. Lets fix it by removing the extra s from math.\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> import maths\nTraceback (most recent call last):\n File \"\", line 1, in \nModuleNotFoundError: No module named 'maths'\n>>> import math\n>>>\n```\n\nWe fixed it, so let's use some of the functions from the math module.\n\n### AttributeError\n\n**Example 1: AttributeError**\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> import maths\nTraceback (most recent call last):\n File \"\", line 1, in \nModuleNotFoundError: No module named 'maths'\n>>> import math\n>>> math.PI\nTraceback (most recent call last):\n File \"\", line 1, in \nAttributeError: module 'math' has no attribute 'PI'\n>>>\n```\n\nAs you can see, I made a mistake again! Instead of pi, I tried to call a PI constant from maths module. It raised an attribute error, it means, that the attribute does not exist in the module. Lets fix it by changing from PI to pi.\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> import maths\nTraceback (most recent call last):\n File \"\", line 1, in \nModuleNotFoundError: No module named 'maths'\n>>> import math\n>>> math.PI\nTraceback (most recent call last):\n File \"\", line 1, in \nAttributeError: module 'math' has no attribute 'PI'\n>>> math.pi\n3.141592653589793\n>>>\n```\n\nNow, when we call pi from the math module we got the result.\n\n### KeyError\n\n**Example 1: KeyError**\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> users = {'name':'Asab', 'age':250, 'country':'Finland'}\n>>> users['name']\n'Asab'\n>>> users['county']\nTraceback (most recent call last):\n File \"\", line 1, in \nKeyError: 'county'\n>>>\n```\n\nAs you can see, there was a typo in the key used to get the dictionary value. so, this is a key error and the fix is quite straight forward. Let's do this!\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> user = {'name':'Asab', 'age':250, 'country':'Finland'}\n>>> user['name']\n'Asab'\n>>> user['county']\nTraceback (most recent call last):\n File \"\", line 1, in \nKeyError: 'county'\n>>> user['country']\n'Finland'\n>>>\n```\n\nWe debugged the error, our code ran and we got the value.\n\n### TypeError\n\n**Example 1: TypeError**\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> 4 + '3'\nTraceback (most recent call last):\n File \"\", line 1, in \nTypeError: unsupported operand type(s) for +: 'int' and 'str'\n>>>\n```\n\nIn the example above, a TypeError is raised because we cannot add a number to a string. First solution would be to convert the string to int or float. Another solution would be converting the number to a string (the result then would be '43'). Let us follow the first fix.\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> 4 + '3'\nTraceback (most recent call last):\n File \"\", line 1, in \nTypeError: unsupported operand type(s) for +: 'int' and 'str'\n>>> 4 + int('3')\n7\n>>> 4 + float('3')\n7.0\n>>>\n```\n\nError removed and we got the result we expected.\n\n### ImportError\n\n**Example 1: TypeError**\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> from math import power\nTraceback (most recent call last):\n File \"\", line 1, in \nImportError: cannot import name 'power' from 'math'\n>>>\n```\n\nThere is no function called power in the math module, it goes with a different name: _pow_. Let's correct it:\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> from math import power\nTraceback (most recent call last):\n File \"\", line 1, in \nImportError: cannot import name 'power' from 'math'\n>>> from math import pow\n>>> pow(2,3)\n8.0\n>>>\n```\n\n### ValueError\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> int('12a')\nTraceback (most recent call last):\n File \"\", line 1, in \nValueError: invalid literal for int() with base 10: '12a'\n>>>\n```\n\nIn this case we cannot change the given string to a number, because of the 'a' letter in it.\n\n### ZeroDivisionError\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> 1/0\nTraceback (most recent call last):\n File \"\", line 1, in \nZeroDivisionError: division by zero\n>>>\n```\n\nWe cannot divide a number by zero.\n\nWe have covered some of the python error types, if you want to check more about it check the python documentation about python error types.\nIf you are good at reading the error types, then you will be able to fix your bugs fast and you will also become a better programmer.\n\n🌕 You are excelling. You made it to half way to your way to greatness. Now do some exercises for your brain and for your muscle.\n\n## 💻 Exercises: Day 15\n\n1. Open you python interactive shell and try all the examples covered in this section.\n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 14](../14_Day_Higher_order_functions/14_higher_order_functions.md) | [Day 16 >>](../16_Day_Python_date_time/16_python_datetime.md)\n"
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\n\n[<< Day 15](../15_Day_Python_type_errors/15_python_type_errors.md) | [Day 17 >>](../17_Day_Exception_handling/17_exception_handling.md)\n\n\n- [📘 Day 16](#-day-16)\n - [Python *datetime*](#python-datetime)\n - [Getting *datetime* Information](#getting-datetime-information)\n - [Formatting Date Output Using *strftime*](#formatting-date-output-using-strftime)\n - [String to Time Using *strptime*](#string-to-time-using-strptime)\n - [Using *date* from *datetime*](#using-date-from-datetime)\n - [Time Objects to Represent Time](#time-objects-to-represent-time)\n - [Difference Between Two Points in Time Using](#difference-between-two-points-in-time-using)\n - [Difference Between Two Points in Time Using *timedelta*](#difference-between-two-points-in-time-using-timedelta)\n - [💻 Exercises: Day 16](#-exercises-day-16)\n# 📘 Day 16\n\n## Python *datetime*\n\nPython has got _datetime_ module to handle date and time.\n\n```py\nimport datetime\nprint(dir(datetime))\n['MAXYEAR', 'MINYEAR', '__builtins__', '__cached__', '__doc__', '__file__', '__loader__', '__name__', '__package__', '__spec__', 'date', 'datetime', 'datetime_CAPI', 'sys', 'time', 'timedelta', 'timezone', 'tzinfo']\n```\n\nWith dir or help built-in commands it is possible to know the available functions in a certain module. As you can see, in the datetime module there are many functions, but we will focus on _date_, _datetime_, _time_ and _timedelta_. Let se see them one by one.\n\n### Getting *datetime* Information\n\n```py\nfrom datetime import datetime\nnow = datetime.now()\nprint(now) # 2021-07-08 07:34:46.549883\nday = now.day # 8\nmonth = now.month # 7\nyear = now.year # 2021\nhour = now.hour # 7\nminute = now.minute # 38\nsecond = now.second\ntimestamp = now.timestamp()\nprint(day, month, year, hour, minute)\nprint('timestamp', timestamp)\nprint(f'{day}/{month}/{year}, {hour}:{minute}') # 8/7/2021, 7:38\n```\n\nTimestamp or Unix timestamp is the number of seconds elapsed from 1st of January 1970 UTC.\n\n### Formatting Date Output Using *strftime*\n\n```py\nfrom datetime import datetime\nnew_year = datetime(2020, 1, 1)\nprint(new_year) # 2020-01-01 00:00:00\nday = new_year.day\nmonth = new_year.month\nyear = new_year.year\nhour = new_year.hour\nminute = new_year.minute\nsecond = new_year.second\nprint(day, month, year, hour, minute) #1 1 2020 0 0\nprint(f'{day}/{month}/{year}, {hour}:{minute}') # 1/1/2020, 0:0\n\n```\n\nFormatting date time using *strftime* method and the documentation can be found [here](https://strftime.org/).\n\n```py\nfrom datetime import datetime\n# current date and time\nnow = datetime.now()\nt = now.strftime(\"%H:%M:%S\")\nprint(\"time:\", t) # time: 18:21:40\ntime_one = now.strftime(\"%m/%d/%Y, %H:%M:%S\")\n# mm/dd/YY H:M:S format\nprint(\"time one:\", time_one) # time one: 06/28/2022, 18:21:40\ntime_two = now.strftime(\"%d/%m/%Y, %H:%M:%S\")\n# dd/mm/YY H:M:S format\nprint(\"time two:\", time_two) # time two: 28/06/2022, 18:21:40\n```\n\n```sh\ntime: 01:05:01\ntime one: 12/05/2019, 01:05:01\ntime two: 05/12/2019, 01:05:01\n```\n\nHere are all the _strftime_ symbols we use to format time. An example of all the formats for this module.\n\n\n\n### String to Time Using *strptime*\nHere is a [documentation](https://www.programiz.com/python-programming/datetime/strptime) hat helps to understand the format. \n\n```py\nfrom datetime import datetime\ndate_string = \"5 December, 2019\"\nprint(\"date_string =\", date_string) # date_string = 5 December, 2019\ndate_object = datetime.strptime(date_string, \"%d %B, %Y\")\nprint(\"date_object =\", date_object) # date_object = 2019-12-05 00:00:00\n```\n\n```sh\ndate_string = 5 December, 2019\ndate_object = 2019-12-05 00:00:00\n```\n\n### Using *date* from *datetime*\n\n```py\nfrom datetime import date\nd = date(2020, 1, 1)\nprint(d) # 2020-01-01\nprint('Current date:', d.today()) # 2019-12-05\n# date object of today's date\ntoday = date.today()\nprint(\"Current year:\", today.year) # 2019\nprint(\"Current month:\", today.month) # 12\nprint(\"Current day:\", today.day) # 5\n```\n\n### Time Objects to Represent Time\n\n```py\nfrom datetime import time\n# time(hour = 0, minute = 0, second = 0)\na = time()\nprint(\"a =\", a) # a = 00:00:00\n# time(hour, minute and second)\nb = time(10, 30, 50)\nprint(\"b =\", b) # b = 10:30:50\n# time(hour, minute and second)\nc = time(hour=10, minute=30, second=50)\nprint(\"c =\", c) # c = 10:30:50\n# time(hour, minute, second, microsecond)\nd = time(10, 30, 50, 200555)\nprint(\"d =\", d) # d = 10:30:50.200555\n```\n\noutput \na = 00:00:00 \nb = 10:30:50 \nc = 10:30:50 \nd = 10:30:50.200555\n\n### Difference Between Two Points in Time Using\n\n```py\nfrom datetime import date, datetime\ntoday = date(year=2019, month=12, day=5)\nnew_year = date(year=2020, month=1, day=1)\ntime_left_for_newyear = new_year - today\n# Time left for new year: 27 days, 0:00:00\nprint('Time left for new year: ', time_left_for_newyear) # Time left for new year: 27 days, 0:00:00\n\nt1 = datetime(year = 2019, month = 12, day = 5, hour = 0, minute = 59, second = 0)\nt2 = datetime(year = 2020, month = 1, day = 1, hour = 0, minute = 0, second = 0)\ndiff = t2 - t1\nprint('Time left for new year:', diff) # Time left for new year: 26 days, 23: 01: 00\n```\n\n### Difference Between Two Points in Time Using *timedelta*\n\n```py\nfrom datetime import timedelta\nt1 = timedelta(weeks=12, days=10, hours=4, seconds=20)\nt2 = timedelta(days=7, hours=5, minutes=3, seconds=30)\nt3 = t1 - t2\nprint(\"t3 =\", t3)\n```\n\n```sh\n date_string = 5 December, 2019\n date_object = 2019-12-05 00:00:00\n t3 = 86 days, 22:56:50\n```\n\n🌕 You are an extraordinary. You are 16 steps a head to your way to greatness. Now do some exercises for your brain and muscles.\n\n## 💻 Exercises: Day 16\n\n1. Get the current day, month, year, hour, minute and timestamp from datetime module\n2. Format the current date using this format: \"%m/%d/%Y, %H:%M:%S\")\n3. Today is 5 December, 2019. Change this time string to time.\n4. Calculate the time difference between now and new year.\n5. Calculate the time difference between 1 January 1970 and now.\n6. Think, what can you use the datetime module for? Examples:\n - Time series analysis\n - To get a timestamp of any activities in an application\n - Adding posts on a blog \n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 15](../15_Day_Python_type_errors/15_python_type_errors.md) | [Day 17 >>](../17_Day_Exception_handling/17_exception_handling.md)\n"
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\n\n[<< Day 16](../16_Day_Python_date_time/16_python_datetime.md) | [Day 18 >>](../18_Day_Regular_expressions/18_regular_expressions.md)\n\n\n\n- [📘 Day 17](#-day-17)\n - [Exception Handling](#exception-handling)\n - [Packing and Unpacking Arguments in Python](#packing-and-unpacking-arguments-in-python)\n - [Unpacking](#unpacking)\n - [Unpacking Lists](#unpacking-lists)\n - [Unpacking Dictionaries](#unpacking-dictionaries)\n - [Packing](#packing)\n - [Packing Lists](#packing-lists)\n - [Packing Dictionaries](#packing-dictionaries)\n - [Spreading in Python](#spreading-in-python)\n - [Enumerate](#enumerate)\n - [Zip](#zip)\n - [Exercises: Day 17](#exercises-day-17)\n\n# 📘 Day 17\n\n## Exception Handling\n\nPython uses _try_ and _except_ to handle errors gracefully. A graceful exit (or graceful handling) of errors is a simple programming idiom - a program detects a serious error condition and \"exits gracefully\", in a controlled manner as a result. Often the program prints a descriptive error message to a terminal or log as part of the graceful exit, this makes our application more robust. The cause of an exception is often external to the program itself. An example of exceptions could be an incorrect input, wrong file name, unable to find a file, a malfunctioning IO device. Graceful handling of errors prevents our applications from crashing.\n\nWe have covered the different Python _error_ types in the previous section. If we use _try_ and _except_ in our program, then it will not raise errors in those blocks.\n\n\n\n```py\ntry:\n code in this block if things go well\nexcept:\n code in this block run if things go wrong\n```\n\n**Example:**\n\n```py\ntry:\n print(10 + '5')\nexcept:\n print('Something went wrong')\n```\n\nIn the example above the second operand is a string. We could change it to float or int to add it with the number to make it work. But without any changes, the second block, _except_, will be executed.\n\n**Example:**\n\n```py\ntry:\n name = input('Enter your name:')\n year_born = input('Year you were born:')\n age = 2019 - year_born\n print(f'You are {name}. And your age is {age}.')\nexcept:\n print('Something went wrong')\n```\n\n```sh\nSomething went wrong\n```\n\nIn the above example, the exception block will run and we do not know exactly the problem. To analyze the problem, we can use the different error types with except.\n\nIn the following example, it will handle the error and will also tell us the kind of error raised.\n\n```py\ntry:\n name = input('Enter your name:')\n year_born = input('Year you were born:')\n age = 2019 - year_born\n print(f'You are {name}. And your age is {age}.')\nexcept TypeError:\n print('Type error occured')\nexcept ValueError:\n print('Value error occured')\nexcept ZeroDivisionError:\n print('zero division error occured')\n```\n\n```sh\nEnter your name:Asabeneh\nYear you born:1920\nType error occured\n```\n\nIn the code above the output is going to be _TypeError_.\nNow, let's add an additional block:\n\n```py\ntry:\n name = input('Enter your name:')\n year_born = input('Year you born:')\n age = 2019 - int(year_born)\n print(f'You are {name}. And your age is {age}.')\nexcept TypeError:\n print('Type error occur')\nexcept ValueError:\n print('Value error occur')\nexcept ZeroDivisionError:\n print('zero division error occur')\nelse:\n print('I usually run with the try block')\nfinally:\n print('I alway run.')\n```\n\n```sh\nEnter your name:Asabeneh\nYear you born:1920\nYou are Asabeneh. And your age is 99.\nI usually run with the try block\nI alway run.\n```\n\nIt is also shorten the above code as follows:\n\n```py\ntry:\n name = input('Enter your name:')\n year_born = input('Year you born:')\n age = 2019 - int(year_born)\n print(f'You are {name}. And your age is {age}.')\nexcept Exception as e:\n print(e)\n\n```\n\n## Packing and Unpacking Arguments in Python\n\nWe use two operators:\n\n- \\* for tuples\n- \\*\\* for dictionaries\n\nLet us take as an example below. It takes only arguments but we have list. We can unpack the list and changes to argument.\n\n### Unpacking\n\n#### Unpacking Lists\n\n```py\ndef sum_of_five_nums(a, b, c, d, e):\n return a + b + c + d + e\n\nlst = [1, 2, 3, 4, 5]\nprint(sum_of_five_nums(lst)) # TypeError: sum_of_five_nums() missing 4 required positional arguments: 'b', 'c', 'd', and 'e'\n```\n\nWhen we run the this code, it raises an error, because this function takes numbers (not a list) as arguments. Let us unpack/destructure the list.\n\n```py\ndef sum_of_five_nums(a, b, c, d, e):\n return a + b + c + d + e\n\nlst = [1, 2, 3, 4, 5]\nprint(sum_of_five_nums(*lst)) # 15\n```\n\nWe can also use unpacking in the range built-in function that expects a start and an end.\n\n```py\nnumbers = range(2, 7) # normal call with separate arguments\nprint(list(numbers)) # [2, 3, 4, 5, 6]\nargs = [2, 7]\nnumbers = range(*args) # call with arguments unpacked from a list\nprint(numbers) # [2, 3, 4, 5,6]\n\n```\n\nA list or a tuple can also be unpacked like this:\n\n```py\ncountries = ['Finland', 'Sweden', 'Norway', 'Denmark', 'Iceland']\nfin, sw, nor, *rest = countries\nprint(fin, sw, nor, rest) # Finland Sweden Norway ['Denmark', 'Iceland']\nnumbers = [1, 2, 3, 4, 5, 6, 7]\none, *middle, last = numbers\nprint(one, middle, last) # 1 [2, 3, 4, 5, 6] 7\n```\n\n#### Unpacking Dictionaries\n\n```py\ndef unpacking_person_info(name, country, city, age):\n return f'{name} lives in {country}, {city}. He is {age} year old.'\ndct = {'name':'Asabeneh', 'country':'Finland', 'city':'Helsinki', 'age':250}\nprint(unpacking_person_info(**dct)) # Asabeneh lives in Finland, Helsinki. He is 250 years old.\n```\n\n### Packing\n\nSometimes we never know how many arguments need to be passed to a python function. We can use the packing method to allow our function to take unlimited number or arbitrary number of arguments.\n\n### Packing Lists\n\n```py\ndef sum_all(*args):\n s = 0\n for i in args:\n s += i\n return s\nprint(sum_all(1, 2, 3)) # 6\nprint(sum_all(1, 2, 3, 4, 5, 6, 7)) # 28\n```\n\n#### Packing Dictionaries\n\n```py\ndef packing_person_info(**kwargs):\n # check the type of kwargs and it is a dict type\n # print(type(kwargs))\n # Printing dictionary items\n for key in kwargs:\n print(f\"{key} = {kwargs[key]}\")\n return kwargs\n\nprint(packing_person_info(name=\"Asabeneh\",\n country=\"Finland\", city=\"Helsinki\", age=250))\n```\n\n```sh\nname = Asabeneh\ncountry = Finland\ncity = Helsinki\nage = 250\n{'name': 'Asabeneh', 'country': 'Finland', 'city': 'Helsinki', 'age': 250}\n```\n\n## Spreading in Python\n\nLike in JavaScript, spreading is possible in Python. Let us check it in an example below:\n\n```py\nlst_one = [1, 2, 3]\nlst_two = [4, 5, 6, 7]\nlst = [0, *lst_one, *lst_two]\nprint(lst) # [0, 1, 2, 3, 4, 5, 6, 7]\ncountry_lst_one = ['Finland', 'Sweden', 'Norway']\ncountry_lst_two = ['Denmark', 'Iceland']\nnordic_countries = [*country_lst_one, *country_lst_two]\nprint(nordic_countries) # ['Finland', 'Sweden', 'Norway', 'Denmark', 'Iceland']\n```\n\n## Enumerate\n\nIf we are interested in an index of a list, we use _enumerate_ built-in function to get the index of each item in the list.\n\n```py\nfor index, item in enumerate([20, 30, 40]):\n print(index, item)\n```\n\n```py\ncountries = ['Finland', 'Sweden', 'Norway', 'Denmark', 'Iceland']\nfor index, i in enumerate(countries):\n if i == 'Finland':\n print(f'The country {i} has been found at index {index}')\n```\n\n```sh\nThe country Finland has been found at index 0.\n```\n\n## Zip\n\nSometimes we would like to combine lists when looping through them. See the example below:\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon', 'lime'] \nvegetables = ['Tomato', 'Potato', 'Cabbage','Onion', 'Carrot']\nfruits_and_veges = []\nfor f, v in zip(fruits, vegetables):\n fruits_and_veges.append({'fruit':f, 'veg':v})\n\nprint(fruits_and_veges)\n```\n\n```sh\n[{'fruit': 'banana', 'veg': 'Tomato'}, {'fruit': 'orange', 'veg': 'Potato'}, {'fruit': 'mango', 'veg': 'Cabbage'}, {'fruit': 'lemon', 'veg': 'Onion'}, {'fruit': 'lime', 'veg': 'Carrot'}]\n```\n\n🌕 You are determined. You are 17 steps a head to your way to greatness. Now do some exercises for your brain and muscles.\n\n## Exercises: Day 17\n\n1. names = ['Finland', 'Sweden', 'Norway','Denmark','Iceland', 'Estonia','Russia']. Unpack the first five countries and store them in a variable nordic_countries, store Estonia and Russia in es, and ru respectively.\n\n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 16](../16_Day_Python_date_time/16_python_datetime.md) | [Day 18 >>](../18_Day_Regular_expressions/18_regular_expressions.md)\n"
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\n\n\n[<< Day 17](../17_Day_Exception_handling/17_exception_handling.md) | [Day 19>>](../19_Day_File_handling/19_file_handling.md)\n\n\n\n- [📘 Day 18](#-day-18)\n - [Regular Expressions](#regular-expressions)\n - [The *re* Module](#the-re-module)\n - [Methods in *re* Module](#methods-in-re-module)\n - [Match](#match)\n - [Search](#search)\n - [Searching for All Matches Using *findall*](#searching-for-all-matches-using-findall)\n - [Replacing a Substring](#replacing-a-substring)\n - [Splitting Text Using RegEx Split](#splitting-text-using-regex-split)\n - [Writing RegEx Patterns](#writing-regex-patterns)\n - [Square Bracket](#square-bracket)\n - [Escape character(\\\\) in RegEx](#escape-character-in-regex)\n - [One or more times(+)](#one-or-more-times)\n - [Period(.)](#period)\n - [Zero or more times(\\*)](#zero-or-more-times)\n - [Zero or one time(?)](#zero-or-one-time)\n - [Quantifier in RegEx](#quantifier-in-regex)\n - [Cart ^](#cart-)\n - [💻 Exercises: Day 18](#-exercises-day-18)\n - [Exercises: Level 1](#exercises-level-1)\n - [Exercises: Level 2](#exercises-level-2)\n - [Exercises: Level 3](#exercises-level-3)\n\n# 📘 Day 18\n\n## Regular Expressions\n\nA regular expression or RegEx is a special text string that helps to find patterns in data. A RegEx can be used to check if some pattern exists in a different data type. To use RegEx in python first we should import the RegEx module which is called *re*.\n\n### The *re* Module\n\nAfter importing the module we can use it to detect or find patterns.\n\n```py\nimport re\n```\n\n### Methods in *re* Module\n\nTo find a pattern we use different set of *re* character sets that allows to search for a match in a string.\n\n- *re.match()*: searches only in the beginning of the first line of the string and returns matched objects if found, else returns None.\n- *re.search*: Returns a match object if there is one anywhere in the string, including multiline strings.\n- *re.findall*: Returns a list containing all matches\n- *re.split*: Takes a string, splits it at the match points, returns a list\n- *re.sub*: Replaces one or many matches within a string\n\n#### Match\n\n```py\n# syntax\nre.match(substring, string, re.I)\n# substring is a string or a pattern, string is the text we look for a pattern , re.I is case ignore\n```\n\n```py\nimport re\n\ntxt = 'I love to teach python and javaScript'\n# It returns an object with span, and match\nmatch = re.match('I love to teach', txt, re.I)\nprint(match) # \n# We can get the starting and ending position of the match as tuple using span\nspan = match.span()\nprint(span) # (0, 15)\n# Lets find the start and stop position from the span\nstart, end = span\nprint(start, end) # 0 15\nsubstring = txt[start:end]\nprint(substring) # I love to teach\n```\n\nAs you can see from the example above, the pattern we are looking for (or the substring we are looking for) is *I love to teach*. The match function returns an object **only** if the text starts with the pattern.\n\n```py\nimport re\n\ntxt = 'I love to teach python and javaScript'\nmatch = re.match('I like to teach', txt, re.I)\nprint(match) # None\n```\n\nThe string does not string with *I like to teach*, therefore there was no match and the match method returned None.\n\n#### Search\n\n```py\n# syntax\nre.search(substring, string, re.I)\n# substring is a pattern, string is the text we look for a pattern , re.I is case ignore flag\n```\n\n```py\nimport re\n\ntxt = '''Python is the most beautiful language that a human being has ever created.\nI recommend python for a first programming language'''\n\n# It returns an object with span and match\nmatch = re.search('first', txt, re.I)\nprint(match) # \n# We can get the starting and ending position of the match as tuple using span\nspan = match.span()\nprint(span) # (100, 105)\n# Lets find the start and stop position from the span\nstart, end = span\nprint(start, end) # 100 105\nsubstring = txt[start:end]\nprint(substring) # first\n```\n\nAs you can see, search is much better than match because it can look for the pattern throughout the text. Search returns a match object with a first match that was found, otherwise it returns *None*. A much better *re* function is *findall*. This function checks for the pattern through the whole string and returns all the matches as a list.\n\n#### Searching for All Matches Using *findall*\n\n*findall()* returns all the matches as a list\n\n```py\ntxt = '''Python is the most beautiful language that a human being has ever created.\nI recommend python for a first programming language'''\n\n# It return a list\nmatches = re.findall('language', txt, re.I)\nprint(matches) # ['language', 'language']\n```\n\nAs you can see, the word *language* was found two times in the string. Let us practice some more.\nNow we will look for both Python and python words in the string:\n\n```py\ntxt = '''Python is the most beautiful language that a human being has ever created.\nI recommend python for a first programming language'''\n\n# It returns list\nmatches = re.findall('python', txt, re.I)\nprint(matches) # ['Python', 'python']\n\n```\n\nSince we are using *re.I* both lowercase and uppercase letters are included. If we do not have the re.I flag, then we will have to write our pattern differently. Let us check it out:\n\n```py\ntxt = '''Python is the most beautiful language that a human being has ever created.\nI recommend python for a first programming language'''\n\nmatches = re.findall('Python|python', txt)\nprint(matches) # ['Python', 'python']\n\n#\nmatches = re.findall('[Pp]ython', txt)\nprint(matches) # ['Python', 'python']\n\n```\n\n#### Replacing a Substring\n\n```py\ntxt = '''Python is the most beautiful language that a human being has ever created.\nI recommend python for a first programming language'''\n\nmatch_replaced = re.sub('Python|python', 'JavaScript', txt, re.I)\nprint(match_replaced) # JavaScript is the most beautiful language that a human being has ever created.I recommend python for a first programming language\n# OR\nmatch_replaced = re.sub('[Pp]ython', 'JavaScript', txt, re.I)\nprint(match_replaced) # JavaScript is the most beautiful language that a human being has ever created.I recommend python for a first programming language\n```\n\nLet us add one more example. The following string is really hard to read unless we remove the % symbol. Replacing the % with an empty string will clean the text.\n\n```py\n\ntxt = '''%I a%m te%%a%%che%r% a%n%d %% I l%o%ve te%ach%ing.\nT%he%re i%s n%o%th%ing as r%ewarding a%s e%duc%at%i%ng a%n%d e%m%p%ow%er%ing p%e%o%ple.\nI fo%und te%a%ching m%ore i%n%t%er%%es%ting t%h%an any other %jobs.\nD%o%es thi%s m%ot%iv%a%te %y%o%u to b%e a t%e%a%cher?'''\n\nmatches = re.sub('%', '', txt)\nprint(matches)\n```\n\n```sh\nI am teacher and I love teaching.\nThere is nothing as rewarding as educating and empowering people.\nI found teaching more interesting than any other jobs. Does this motivate you to be a teacher?\n```\n\n## Splitting Text Using RegEx Split\n\n```py\ntxt = '''I am teacher and I love teaching.\nThere is nothing as rewarding as educating and empowering people.\nI found teaching more interesting than any other jobs.\nDoes this motivate you to be a teacher?'''\nprint(re.split('\\n', txt)) # splitting using \\n - end of line symbol\n```\n\n```sh\n['I am teacher and I love teaching.', 'There is nothing as rewarding as educating and empowering people.', 'I found teaching more interesting than any other jobs.', 'Does this motivate you to be a teacher?']\n```\n\n## Writing RegEx Patterns\n\nTo declare a string variable we use a single or double quote. To declare RegEx variable *r''*.\nThe following pattern only identifies apple with lowercase, to make it case insensitive either we should rewrite our pattern or we should add a flag.\n\n```py\nimport re\n\nregex_pattern = r'apple'\ntxt = 'Apple and banana are fruits. An old cliche says an apple a day a doctor way has been replaced by a banana a day keeps the doctor far far away. '\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['apple']\n\n# To make case insensitive adding flag '\nmatches = re.findall(regex_pattern, txt, re.I)\nprint(matches) # ['Apple', 'apple']\n# or we can use a set of characters method\nregex_pattern = r'[Aa]pple' # this mean the first letter could be Apple or apple\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['Apple', 'apple']\n\n```\n\n* []: A set of characters\n - [a-c] means, a or b or c\n - [a-z] means, any letter from a to z\n - [A-Z] means, any character from A to Z\n - [0-3] means, 0 or 1 or 2 or 3\n - [0-9] means any number from 0 to 9\n - [A-Za-z0-9] any single character, that is a to z, A to Z or 0 to 9\n- \\\\: uses to escape special characters\n - \\d means: match where the string contains digits (numbers from 0-9)\n - \\D means: match where the string does not contain digits\n- . : any character except new line character(\\n)\n- ^: starts with\n - r'^substring' eg r'^love', a sentence that starts with a word love\n - r'[^abc] means not a, not b, not c.\n- $: ends with\n - r'substring$' eg r'love$', sentence that ends with a word love\n- *: zero or more times\n - r'[a]*' means a optional or it can occur many times.\n- +: one or more times\n - r'[a]+' means at least once (or more)\n- ?: zero or one time\n - r'[a]?' means zero times or once\n- {3}: Exactly 3 characters\n- {3,}: At least 3 characters\n- {3,8}: 3 to 8 characters\n- |: Either or\n - r'apple|banana' means either apple or a banana\n- (): Capture and group\n\n\n\nLet us use examples to clarify the meta characters above\n\n### Square Bracket\n\nLet us use square bracket to include lower and upper case\n\n```py\nregex_pattern = r'[Aa]pple' # this square bracket mean either A or a\ntxt = 'Apple and banana are fruits. An old cliche says an apple a day a doctor way has been replaced by a banana a day keeps the doctor far far away.'\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['Apple', 'apple']\n```\n\nIf we want to look for the banana, we write the pattern as follows:\n\n```py\nregex_pattern = r'[Aa]pple|[Bb]anana' # this square bracket means either A or a\ntxt = 'Apple and banana are fruits. An old cliche says an apple a day a doctor way has been replaced by a banana a day keeps the doctor far far away.'\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['Apple', 'banana', 'apple', 'banana']\n```\n\nUsing the square bracket and or operator , we manage to extract Apple, apple, Banana and banana.\n\n### Escape character(\\\\) in RegEx\n\n```py\nregex_pattern = r'\\d' # d is a special character which means digits\ntxt = 'This regular expression example was made on December 6, 2019 and revised on July 8, 2021'\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['6', '2', '0', '1', '9', '8', '2', '0', '2', '1'], this is not what we want\n```\n\n### One or more times(+)\n\n```py\nregex_pattern = r'\\d+' # d is a special character which means digits, + mean one or more times\ntxt = 'This regular expression example was made on December 6, 2019 and revised on July 8, 2021'\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['6', '2019', '8', '2021'] - now, this is better!\n```\n\n### Period(.)\n\n```py\nregex_pattern = r'[a].' # this square bracket means a and . means any character except new line\ntxt = '''Apple and banana are fruits'''\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['an', 'an', 'an', 'a ', 'ar']\n\nregex_pattern = r'[a].+' # . any character, + any character one or more times\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['and banana are fruits']\n```\n\n### Zero or more times(\\*)\n\nZero or many times. The pattern could may not occur or it can occur many times.\n\n```py\nregex_pattern = r'[a].*' # . any character, * any character zero or more times\ntxt = '''Apple and banana are fruits'''\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['and banana are fruits']\n```\n\n### Zero or one time(?)\n\nZero or one time. The pattern may not occur or it may occur once.\n\n```py\ntxt = '''I am not sure if there is a convention how to write the word e-mail.\nSome people write it as email others may write it as Email or E-mail.'''\nregex_pattern = r'[Ee]-?mail' # ? means here that '-' is optional\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['e-mail', 'email', 'Email', 'E-mail']\n```\n\n### Quantifier in RegEx\n\nWe can specify the length of the substring we are looking for in a text, using a curly bracket. Let us imagine, we are interested in a substring with a length of 4 characters:\n\n```py\ntxt = 'This regular expression example was made on December 6, 2019 and revised on July 8, 2021'\nregex_pattern = r'\\d{4}' # exactly four times\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['2019', '2021']\n\ntxt = 'This regular expression example was made on December 6, 2019 and revised on July 8, 2021'\nregex_pattern = r'\\d{1,4}'\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['6', '2019', '8', '2021'] \n```\n\n### Cart ^\n\n- Starts with\n\n```py\ntxt = 'This regular expression example was made on December 6, 2019 and revised on July 8, 2021'\nregex_pattern = r'^This' # ^ means starts with\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['This']\n```\n\n- Negation\n\n```py\ntxt = 'This regular expression example was made on December 6, 2019 and revised on July 8, 2021'\nregex_pattern = r'[^A-Za-z ]+' # ^ in set character means negation, not A to Z, not a to z, no space\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['6,', '2019', '8', '2021']\n```\n\n## 💻 Exercises: Day 18\n\n### Exercises: Level 1\n\n 1. What is the most frequent word in the following paragraph?\n\n```py\n paragraph = 'I love teaching. If you do not love teaching what else can you love. I love Python if you do not love something which can give you all the capabilities to develop an application what else can you love.\n```\n\n```sh\n [\n (6, 'love'),\n (5, 'you'),\n (3, 'can'),\n (2, 'what'),\n (2, 'teaching'),\n (2, 'not'),\n (2, 'else'),\n (2, 'do'),\n (2, 'I'),\n (1, 'which'),\n (1, 'to'),\n (1, 'the'),\n (1, 'something'),\n (1, 'if'),\n (1, 'give'),\n (1, 'develop'),\n (1, 'capabilities'),\n (1, 'application'),\n (1, 'an'),\n (1, 'all'),\n (1, 'Python'),\n (1, 'If')\n ]\n```\n\n2. The position of some particles on the horizontal x-axis are -12, -4, -3 and -1 in the negative direction, 0 at origin, 4 and 8 in the positive direction. Extract these numbers from this whole text and find the distance between the two furthest particles.\n\n```py\npoints = ['-12', '-4', '-3', '-1', '0', '4', '8']\nsorted_points = [-12, -4, -3, -1, -1, 0, 2, 4, 8]\ndistance = 8 -(-12) # 20\n```\n\n### Exercises: Level 2\n\n1. Write a pattern which identifies if a string is a valid python variable\n\n ```sh\n is_valid_variable('first_name') # True\n is_valid_variable('first-name') # False\n is_valid_variable('1first_name') # False\n is_valid_variable('firstname') # True\n ```\n\n### Exercises: Level 3\n\n1. Clean the following text. After cleaning, count three most frequent words in the string.\n\n ```py\n sentence = '''%I $am@% a %tea@cher%, &and& I lo%#ve %tea@ching%;. There $is nothing; &as& mo@re rewarding as educa@ting &and& @emp%o@wering peo@ple. ;I found tea@ching m%o@re interesting tha@n any other %jo@bs. %Do@es thi%s mo@tivate yo@u to be a tea@cher!?'''\n\n print(clean_text(sentence));\n I am a teacher and I love teaching There is nothing as more rewarding as educating and empowering people I found teaching more interesting than any other jobs Does this motivate you to be a teacher\n print(most_frequent_words(cleaned_text)) # [(3, 'I'), (2, 'teaching'), (2, 'teacher')]\n ```\n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 17](../17_Day_Exception_handling/17_exception_handling.md) | [Day 19>>](../19_Day_File_handling/19_file_handling.md)\n"
},
{
"path": "19_Day_File_handling/19_file_handling.md",
"content": "
\n\n[<< Day 18](../18_Day_Regular_expressions/18_regular_expressions.md) | [Day 20 >>](../20_Day_Python_package_manager/20_python_package_manager.md)\n\n\n\n- [📘 Day 19](#-day-19)\n - [File Handling](#file-handling)\n - [Opening Files for Reading](#opening-files-for-reading)\n - [Opening Files for Writing and Updating](#opening-files-for-writing-and-updating)\n - [Deleting Files](#deleting-files)\n - [File Types](#file-types)\n - [File with txt Extension](#file-with-txt-extension)\n - [File with json Extension](#file-with-json-extension)\n - [Changing JSON to Dictionary](#changing-json-to-dictionary)\n - [Changing Dictionary to JSON](#changing-dictionary-to-json)\n - [Saving as JSON File](#saving-as-json-file)\n - [File with csv Extension](#file-with-csv-extension)\n - [File with xlsx Extension](#file-with-xlsx-extension)\n - [File with xml Extension](#file-with-xml-extension)\n - [💻 Exercises: Day 19](#-exercises-day-19)\n - [Exercises: Level 1](#exercises-level-1)\n - [Exercises: Level 2](#exercises-level-2)\n - [Exercises: Level 3](#exercises-level-3)\n\n# 📘 Day 19\n\n## File Handling\n\nSo far we have seen different Python data types. We usually store our data in different file formats. In addition to handling files, we will also see different file formats(.txt, .json, .xml, .csv, .tsv, .excel) in this section. First, let us get familiar with handling files with common file format(.txt).\n\nFile handling is an import part of programming which allows us to create, read, update and delete files. In Python to handle data we use _open()_ built-in function.\n\n```py\n# Syntax\nopen('filename', mode) # mode(r, a, w, x, t,b) could be to read, write, update\n```\n\n- \"r\" - Read - Default value. Opens a file for reading, it returns an error if the file does not exist\n- \"a\" - Append - Opens a file for appending, creates the file if it does not exist\n- \"w\" - Write - Opens a file for writing, creates the file if it does not exist\n- \"x\" - Create - Creates the specified file, returns an error if the file exists\n- \"t\" - Text - Default value. Text mode\n- \"b\" - Binary - Binary mode (e.g. images)\n\n### Opening Files for Reading\n\nThe default mode of _open_ is reading, so we do not have to specify 'r' or 'rt'. I have created and saved a file named reading_file_example.txt in the files directory. Let us see how it is done:\n\n```py\nf = open('./files/reading_file_example.txt')\nprint(f) # <_io.TextIOWrapper name='./files/reading_file_example.txt' mode='r' encoding='UTF-8'>\n```\n\nAs you can see in the example above, I printed the opened file and it gave some information about it. Opened file has different reading methods: _read()_, _readline_, _readlines_. An opened file has to be closed with _close()_ method.\n\n- _read()_: read the whole text as string. If we want to limit the number of characters we want to read, we can limit it by passing int value to the *read(number)* method.\n\n```py\nf = open('./files/reading_file_example.txt')\ntxt = f.read()\nprint(type(txt))\nprint(txt)\nf.close()\n```\n\n```sh\n# output\n\nThis is an example to show how to open a file and read.\nThis is the second line of the text.\n```\n\nInstead of printing all the text, let us print the first 10 characters of the text file.\n\n```py\nf = open('./files/reading_file_example.txt')\ntxt = f.read(10)\nprint(type(txt))\nprint(txt)\nf.close()\n```\n\n```sh\n# output\n\nThis is an\n```\n\n- _readline()_: read only the first line\n\n```py\nf = open('./files/reading_file_example.txt')\nline = f.readline()\nprint(type(line))\nprint(line)\nf.close()\n```\n\n```sh\n# output\n\nThis is an example to show how to open a file and read.\n```\n\n- _readlines()_: read all the text line by line and returns a list of lines\n\n```py\nf = open('./files/reading_file_example.txt')\nlines = f.readlines()\nprint(type(lines))\nprint(lines)\nf.close()\n```\n\n```sh\n# output\n\n['This is an example to show how to open a file and read.\\n', 'This is the second line of the text.']\n```\n\nAnother way to get all the lines as a list is using _splitlines()_:\n\n```py\nf = open('./files/reading_file_example.txt')\nlines = f.read().splitlines()\nprint(type(lines))\nprint(lines)\nf.close()\n```\n\n```sh\n# output\n\n['This is an example to show how to open a file and read.', 'This is the second line of the text.']\n```\n\nAfter we open a file, we should close it. There is a high tendency of forgetting to close them. There is a new way of opening files using _with_ - closes the files by itself. Let us rewrite the the previous example with the _with_ method:\n\n```py\nwith open('./files/reading_file_example.txt') as f:\n lines = f.read().splitlines()\n print(type(lines))\n print(lines)\n```\n\n```sh\n# output\n\n['This is an example to show how to open a file and read.', 'This is the second line of the text.']\n```\n\n### Opening Files for Writing and Updating\n\nTo write to an existing file, we must add a mode as parameter to the _open()_ function:\n\n- \"a\" - append - will append to the end of the file, if the file does not exist it creates a new file.\n- \"w\" - write - will overwrite any existing content, if the file does not exist it creates.\n\nLet us append some text to the file we have been reading:\n\n```py\nwith open('./files/reading_file_example.txt','a') as f:\n f.write('This text has to be appended at the end')\n```\n\nThe method below creates a new file, if the file does not exist:\n\n```py\nwith open('./files/writing_file_example.txt','w') as f:\n f.write('This text will be written in a newly created file')\n```\n\n### Deleting Files\n\nWe have seen in previous section, how to make and remove a directory using _os_ module. Again now, if we want to remove a file we use _os_ module.\n\n```py\nimport os\nos.remove('./files/example.txt')\n\n```\n\nIf the file does not exist, the remove method will raise an error, so it is good to use a condition like this:\n\n```py\nimport os\nif os.path.exists('./files/example.txt'):\n os.remove('./files/example.txt')\nelse:\n print('The file does not exist')\n```\n\n## File Types\n\n### File with txt Extension\n\nFile with _txt_ extension is a very common form of data and we have covered it in the previous section. Let us move to the JSON file\n\n### File with json Extension\n\nJSON stands for JavaScript Object Notation. Actually, it is a stringified JavaScript object or Python dictionary.\n\n_Example:_\n\n```py\n# dictionary\nperson_dct= {\n \"name\":\"Asabeneh\",\n \"country\":\"Finland\",\n \"city\":\"Helsinki\",\n \"skills\":[\"JavaScrip\", \"React\",\"Python\"]\n}\n# JSON: A string form a dictionary\nperson_json = \"{'name': 'Asabeneh', 'country': 'Finland', 'city': 'Helsinki', 'skills': ['JavaScrip', 'React', 'Python']}\"\n\n# we use three quotes and make it multiple line to make it more readable\nperson_json = '''{\n \"name\":\"Asabeneh\",\n \"country\":\"Finland\",\n \"city\":\"Helsinki\",\n \"skills\":[\"JavaScrip\", \"React\",\"Python\"]\n}'''\n```\n\n### Changing JSON to Dictionary\n\nTo change a JSON to a dictionary, first we import the json module and then we use _loads_ method.\n\n```py\nimport json\n# JSON\nperson_json = '''{\n \"name\": \"Asabeneh\",\n \"country\": \"Finland\",\n \"city\": \"Helsinki\",\n \"skills\": [\"JavaScrip\", \"React\", \"Python\"]\n}'''\n# let's change JSON to dictionary\nperson_dct = json.loads(person_json)\nprint(type(person_dct))\nprint(person_dct)\nprint(person_dct['name'])\n```\n\n```sh\n# output\n\n{'name': 'Asabeneh', 'country': 'Finland', 'city': 'Helsinki', 'skills': ['JavaScrip', 'React', 'Python']}\nAsabeneh\n```\n\n### Changing Dictionary to JSON\n\nTo change a dictionary to a JSON we use _dumps_ method from the json module.\n\n```py\nimport json\n# python dictionary\nperson = {\n \"name\": \"Asabeneh\",\n \"country\": \"Finland\",\n \"city\": \"Helsinki\",\n \"skills\": [\"JavaScrip\", \"React\", \"Python\"]\n}\n# let's convert it to json\nperson_json = json.dumps(person, indent=4) # indent could be 2, 4, 8. It beautifies the json\nprint(type(person_json))\nprint(person_json)\n```\n\n```sh\n# output\n# when you print it, it does not have the quote, but actually it is a string\n# JSON does not have type, it is a string type.\n\n{\n \"name\": \"Asabeneh\",\n \"country\": \"Finland\",\n \"city\": \"Helsinki\",\n \"skills\": [\n \"JavaScrip\",\n \"React\",\n \"Python\"\n ]\n}\n```\n\n### Saving as JSON File\n\nWe can also save our data as a json file. Let us save it as a json file using the following steps. For writing a json file, we use the json.dump() method, it can take dictionary, output file, ensure_ascii and indent.\n\n```py\nimport json\n# python dictionary\nperson = {\n \"name\": \"Asabeneh\",\n \"country\": \"Finland\",\n \"city\": \"Helsinki\",\n \"skills\": [\"JavaScrip\", \"React\", \"Python\"]\n}\nwith open('./files/json_example.json', 'w', encoding='utf-8') as f:\n json.dump(person, f, ensure_ascii=False, indent=4)\n```\n\nIn the code above, we use encoding and indentation. Indentation makes the json file easy to read.\n\n### File with csv Extension\n\nCSV stands for comma separated values. CSV is a simple file format used to store tabular data, such as a spreadsheet or database. CSV is a very common data format in data science.\n\n**Example:**\n\n```csv\n\"name\",\"country\",\"city\",\"skills\"\n\"Asabeneh\",\"Finland\",\"Helsinki\",\"JavaScript\"\n```\n\n**Example:**\n\n```py\nimport csv\nwith open('./files/csv_example.csv') as f:\n csv_reader = csv.reader(f, delimiter=',') # we use, reader method to read csv\n line_count = 0\n for row in csv_reader:\n if line_count == 0:\n print(f'Column names are :{\", \".join(row)}')\n line_count += 1\n else:\n print(\n f'\\t{row[0]} is a teachers. He lives in {row[1]}, {row[2]}.')\n line_count += 1\n print(f'Number of lines: {line_count}')\n```\n\n```sh\n# output:\nColumn names are :name, country, city, skills\nNumber of lines: 1\n Asabeneh is a teacher. He lives in Finland, Helsinki.\nNumber of lines: 2\n```\n\n### File with xlsx Extension\n\nTo read excel files we need to install _xlrd_ package. We will cover this after we cover package installing using pip.\n\n```py\nimport xlrd\nexcel_book = xlrd.open_workbook('sample.xls')\nprint(excel_book.nsheets)\nprint(excel_book.sheet_names)\n```\n\n### File with xml Extension\n\nXML is another structured data format which looks like HTML. In XML the tags are not predefined. The first line is an XML declaration. The person tag is the root of the XML. The person has a gender attribute.\n**Example:XML**\n\n```xml\n\n\n Asabeneh\n Finland\n Helsinki\n \n JavaScrip\n React\n Python\n \n\n```\n\nFor more information on how to read an XML file check the [documentation](https://docs.python.org/2/library/xml.etree.elementtree.html)\n\n```py\nimport xml.etree.ElementTree as ET\ntree = ET.parse('./files/xml_example.xml')\nroot = tree.getroot()\nprint('Root tag:', root.tag)\nprint('Attribute:', root.attrib)\nfor child in root:\n print('field: ', child.tag)\n```\n\n```sh\n# output\nRoot tag: person\nAttribute: {'gender': 'male'}\nfield: name\nfield: country\nfield: city\nfield: skills\n```\n\n🌕 You are making a big progress. Maintain your momentum, keep the good work. Now do some exercises for your brain and muscles.\n\n## 💻 Exercises: Day 19\n\n### Exercises: Level 1\n\n1. Write a function which count number of lines and number of words in a text. All the files are in the data the folder:\n 1) Read obama_speech.txt file and count number of lines and words\n 2) Read michelle_obama_speech.txt file and count number of lines and words\n 3) Read donald_speech.txt file and count number of lines and words\n 4) Read melina_trump_speech.txt file and count number of lines and words\n2. Read the countries_data.json data file in data directory, create a function that finds the ten most spoken languages\n\n ```py\n # Your output should look like this\n print(most_spoken_languages(filename='./data/countries_data.json', 10))\n [(91, 'English'),\n (45, 'French'),\n (25, 'Arabic'),\n (24, 'Spanish'),\n (9, 'Russian'),\n (9, 'Portuguese'),\n (8, 'Dutch'),\n (7, 'German'),\n (5, 'Chinese'),\n (4, 'Swahili'),\n (4, 'Serbian')]\n\n # Your output should look like this\n print(most_spoken_languages(filename='./data/countries_data.json', 3))\n [(91, 'English'),\n (45, 'French'),\n (25, 'Arabic')]\n ```\n\n3. Read the countries_data.json data file in data directory, create a function that creates a list of the ten most populated countries\n\n ```py\n # Your output should look like this\n print(most_populated_countries(filename='./data/countries_data.json', 10))\n\n [\n {'country': 'China', 'population': 1377422166},\n {'country': 'India', 'population': 1295210000},\n {'country': 'United States of America', 'population': 323947000},\n {'country': 'Indonesia', 'population': 258705000},\n {'country': 'Brazil', 'population': 206135893},\n {'country': 'Pakistan', 'population': 194125062},\n {'country': 'Nigeria', 'population': 186988000},\n {'country': 'Bangladesh', 'population': 161006790},\n {'country': 'Russian Federation', 'population': 146599183},\n {'country': 'Japan', 'population': 126960000}\n ]\n\n # Your output should look like this\n\n print(most_populated_countries(filename='./data/countries_data.json', 3))\n [\n {'country': 'China', 'population': 1377422166},\n {'country': 'India', 'population': 1295210000},\n {'country': 'United States of America', 'population': 323947000}\n ]\n ```\n\n### Exercises: Level 2\n\n1. Extract all incoming email addresses as a list from the email_exchange_big.txt file.\n2. Find the most common words in the English language. Call the name of your function find_most_common_words, it will take two parameters - a string or a file and a positive integer, indicating the number of words. Your function will return an array of tuples in descending order. Check the output\n\n```py\n # Your output should look like this\n print(find_most_common_words('sample.txt', 10))\n [(10, 'the'),\n (8, 'be'),\n (6, 'to'),\n (6, 'of'),\n (5, 'and'),\n (4, 'a'),\n (4, 'in'),\n (3, 'that'),\n (2, 'have'),\n (2, 'I')]\n\n # Your output should look like this\n print(find_most_common_words('sample.txt', 5))\n\n [(10, 'the'),\n (8, 'be'),\n (6, 'to'),\n (6, 'of'),\n (5, 'and')]\n```\n\n3. Use the function, find_most_frequent_words to find:\n 1) The ten most frequent words used in [Obama's speech](https://github.com/Asabeneh/30-Days-Of-Python/blob/master/data/obama_speech.txt)\n 2) The ten most frequent words used in [Michelle's speech](https://github.com/Asabeneh/30-Days-Of-Python/blob/master/data/michelle_obama_speech.txt)\n 3) The ten most frequent words used in [Trump's speech](https://github.com/Asabeneh/30-Days-Of-Python/blob/master/data/donald_speech.txt)\n 4) The ten most frequent words used in [Melina's speech](https://github.com/Asabeneh/30-Days-Of-Python/blob/master/data/melina_trump_speech.txt)\n4. Write a python application that checks similarity between two texts. It takes a file or a string as a parameter and it will evaluate the similarity of the two texts. For instance check the similarity between the transcripts of [Michelle's](https://github.com/Asabeneh/30-Days-Of-Python/blob/master/data/michelle_obama_speech.txt) and [Melina's](https://github.com/Asabeneh/30-Days-Of-Python/blob/master/data/melina_trump_speech.txt) speech. You may need a couple of functions, function to clean the text(clean_text), function to remove support words(remove_support_words) and finally to check the similarity(check_text_similarity). List of [stop words](https://github.com/Asabeneh/30-Days-Of-Python/blob/master/data/stop_words.py) are in the data directory\n5. Find the 10 most repeated words in the romeo_and_juliet.txt\n6. Read the [hacker news csv](https://github.com/Asabeneh/30-Days-Of-Python/blob/master/data/hacker_news.csv) file and find out:\n 1) Count the number of lines containing python or Python\n 2) Count the number lines containing JavaScript, javascript or Javascript\n 3) Count the number lines containing Java and not JavaScript\n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 18](../18_Day_Regular_expressions/18_regular_expressions.md) | [Day 20 >>](../20_Day_Python_package_manager/20_python_package_manager.md)\n"
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\n\n[<< Day 19](../19_Day_File_handling/19_file_handling.md) | [Day 21 >>](../21_Day_Classes_and_objects/21_classes_and_objects.md)\n\n\n\n- [📘 Day 20](#-day-20)\n - [Python PIP - Python Package Manager](#python-pip---python-package-manager)\n - [What is PIP ?](#what-is-pip-)\n - [Installing PIP](#installing-pip)\n - [Installing packages using pip](#installing-packages-using-pip)\n - [Uninstalling Packages](#uninstalling-packages)\n - [List of Packages](#list-of-packages)\n - [Show Package](#show-package)\n - [PIP Freeze](#pip-freeze)\n - [Reading from URL](#reading-from-url)\n - [Creating a Package](#creating-a-package)\n - [Further Information About Packages](#further-information-about-packages)\n - [Exercises: Day 20](#exercises-day-20)\n\n# 📘 Day 20\n\n## Python PIP - Python Package Manager\n\n### What is PIP ?\n\nPIP stands for Preferred installer program. We use _pip_ to install different Python packages.\nPackage is a Python module that can contain one or more modules or other packages. A module or modules that we can install to our application is a package.\nIn programming, we do not have to write every utility program, instead we install packages and import them to our applications.\n\n### Installing PIP\n\nIf you did not install pip, let us install it now. Go to your terminal or command prompt and copy and paste this:\n\n```sh\nasabeneh@Asabeneh:~$ pip install pip\n```\n\nCheck if pip is installed by writing\n\n```sh\npip --version\n```\n\n```py\nasabeneh@Asabeneh:~$ pip --version\npip 21.1.3 from /usr/local/lib/python3.7/site-packages/pip (python 3.9.6)\n```\n\nAs you can see, I am using pip version 21.1.3, if you see some number a bit below or above that, means you have pip installed.\n\nLet us check some of the packages used in the Python community for different purposes. Just to let you know that there are lots of packages available for use with different applications.\n\n### Installing packages using pip\n\nLet us try to install _numpy_, called numeric python. It is one of the most popular packages in machine learning and data science community.\n\n- NumPy is the fundamental package for scientific computing with Python. It contains among other things:\n - a powerful N-dimensional array object\n - sophisticated (broadcasting) functions\n - tools for integrating C/C++ and Fortran code\n - useful linear algebra, Fourier transform, and random number capabilities\n\n```sh\nasabeneh@Asabeneh:~$ pip install numpy\n```\n\nLet us start using numpy. Open your python interactive shell, write python and then import numpy as follows:\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> import numpy\n>>> numpy.version.version\n'1.20.1'\n>>> lst = [1, 2, 3,4, 5]\n>>> np_arr = numpy.array(lst)\n>>> np_arr\narray([1, 2, 3, 4, 5])\n>>> len(np_arr)\n5\n>>> np_arr * 2\narray([ 2, 4, 6, 8, 10])\n>>> np_arr + 2\narray([3, 4, 5, 6, 7])\n>>>\n```\n\nPandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. Let us install the big brother of numpy, _pandas_:\n\n```sh\nasabeneh@Asabeneh:~$ pip install pandas\n```\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> import pandas\n```\n\nThis section is not about numpy nor pandas, here we are trying to learn how to install packages and how to import them. If it is needed, we will talk about different packages in other sections.\n\nLet us import a web browser module, which can help us to open any website. We do not need to install this module, it is already installed by default with Python 3. For instance if you like to open any number of websites at any time or if you like to schedule something, this _webbrowser_ module can be used.\n\n```py\nimport webbrowser # web browser module to open websites\n\n# list of urls: python\nurl_lists = [\n 'http://www.python.org',\n 'https://www.linkedin.com/in/asabeneh/',\n 'https://github.com/Asabeneh',\n 'https://twitter.com/Asabeneh',\n]\n\n# opens the above list of websites in a different tab\nfor url in url_lists:\n webbrowser.open_new_tab(url)\n```\n\n### Uninstalling Packages\n\nIf you do not like to keep the installed packages, you can remove them using the following command.\n\n```sh\npip uninstall packagename\n```\n\n### List of Packages\n\nTo see the installed packages on our machine. We can use pip followed by list.\n\n```sh\npip list\n```\n\n### Show Package\n\nTo show information about a package\n\n```sh\npip show packagename\n```\n\n```sh\nasabeneh@Asabeneh:~$ pip show pandas\nName: pandas\nVersion: 1.2.3\nSummary: Powerful data structures for data analysis, time series, and statistics\nHome-page: http://pandas.pydata.org\nAuthor: None\nAuthor-email: None\nLicense: BSD\nLocation: /usr/local/lib/python3.7/site-packages\nRequires: python-dateutil, pytz, numpy\nRequired-by:\n```\n\nIf we want even more details, just add --verbose\n\n```sh\nasabeneh@Asabeneh:~$ pip show --verbose pandas\nName: pandas\nVersion: 1.2.3\nSummary: Powerful data structures for data analysis, time series, and statistics\nHome-page: http://pandas.pydata.org\nAuthor: None\nAuthor-email: None\nLicense: BSD\nLocation: /usr/local/lib/python3.7/site-packages\nRequires: numpy, pytz, python-dateutil\nRequired-by:\nMetadata-Version: 2.1\nInstaller: pip\nClassifiers:\n Development Status :: 5 - Production/Stable\n Environment :: Console\n Operating System :: OS Independent\n Intended Audience :: Science/Research\n Programming Language :: Python\n Programming Language :: Python :: 3\n Programming Language :: Python :: 3.5\n Programming Language :: Python :: 3.6\n Programming Language :: Python :: 3.7\n Programming Language :: Python :: 3.8\n Programming Language :: Cython\n Topic :: Scientific/Engineering\nEntry-points:\n [pandas_plotting_backends]\n matplotlib = pandas:plotting._matplotlib\n```\n\n### PIP Freeze\n\nGenerate installed Python packages with their version and the output is suitable to use it in a requirements file. A requirements.txt file is a file that should contain all the installed Python packages in a Python project.\n\n```sh\nasabeneh@Asabeneh:~$ pip freeze\ndocutils==0.11\nJinja2==2.7.2\nMarkupSafe==0.19\nPygments==1.6\nSphinx==1.2.2\n```\n\nThe pip freeze gave us the packages used, installed and their version. We use it with requirements.txt file for deployment.\n\n### Reading from URL\n\nBy now you are familiar with how to read or write on a file located on you local machine. Sometimes, we would like to read from a website using url or from an API.\nAPI stands for Application Program Interface. It is a means to exchange structured data between servers primarily as json data. To open a network connection, we need a package called _requests_ - it allows to open a network connection and to implement CRUD(create, read, update and delete) operations. In this section, we will cover only reading ore getting part of a CRUD.\n\nLet us install _requests_:\n\n```py\nasabeneh@Asabeneh:~$ pip install requests\n```\n\nWe will see _get_, _status_code_, _headers_, _text_ and _json_ methods in _requests_ module:\n - _get()_: to open a network and fetch data from url - it returns a response object\n - _status_code_: After we fetched data, we can check the status of the operation (success, error, etc)\n - _headers_: To check the header types\n - _text_: to extract the text from the fetched response object \n - _json_: to extract json data\nLet's read a txt file from this website, https://www.w3.org/TR/PNG/iso_8859-1.txt.\n\n```py\nimport requests # importing the request module\n\nurl = 'https://www.w3.org/TR/PNG/iso_8859-1.txt' # text from a website\n\nresponse = requests.get(url) # opening a network and fetching a data\nprint(response)\nprint(response.status_code) # status code, success:200\nprint(response.headers) # headers information\nprint(response.text) # gives all the text from the page\n```\n\n```sh\n\n200\n{'date': 'Sun, 08 Dec 2019 18:00:31 GMT', 'last-modified': 'Fri, 07 Nov 2003 05:51:11 GMT', 'etag': '\"17e9-3cb82080711c0;50c0b26855880-gzip\"', 'accept-ranges': 'bytes', 'cache-control': 'max-age=31536000', 'expires': 'Mon, 07 Dec 2020 18:00:31 GMT', 'vary': 'Accept-Encoding', 'content-encoding': 'gzip', 'access-control-allow-origin': '*', 'content-length': '1616', 'content-type': 'text/plain', 'strict-transport-security': 'max-age=15552000; includeSubdomains; preload', 'content-security-policy': 'upgrade-insecure-requests'}\n```\n\n- Let us read from an API. API stands for Application Program Interface. It is a means to exchange structure data between servers primarily a json data. An example of an API:https://restcountries.eu/rest/v2/all. Let us read this API using _requests_ module.\n\n```py\nimport requests\nurl = 'https://restcountries.eu/rest/v2/all' # countries api\nresponse = requests.get(url) # opening a network and fetching a data\nprint(response) # response object\nprint(response.status_code) # status code, success:200\ncountries = response.json()\nprint(countries[:1]) # we sliced only the first country, remove the slicing to see all countries\n```\n\n```sh\n\n200\n[{'alpha2Code': 'AF',\n 'alpha3Code': 'AFG',\n 'altSpellings': ['AF', 'Afġānistān'],\n 'area': 652230.0,\n 'borders': ['IRN', 'PAK', 'TKM', 'UZB', 'TJK', 'CHN'],\n 'callingCodes': ['93'],\n 'capital': 'Kabul',\n 'cioc': 'AFG',\n 'currencies': [{'code': 'AFN', 'name': 'Afghan afghani', 'symbol': '؋'}],\n 'demonym': 'Afghan',\n 'flag': 'https://restcountries.eu/data/afg.svg',\n 'gini': 27.8,\n 'languages': [{'iso639_1': 'ps',\n 'iso639_2': 'pus',\n 'name': 'Pashto',\n 'nativeName': 'پښتو'},\n {'iso639_1': 'uz',\n 'iso639_2': 'uzb',\n 'name': 'Uzbek',\n 'nativeName': 'Oʻzbek'},\n {'iso639_1': 'tk',\n 'iso639_2': 'tuk',\n 'name': 'Turkmen',\n 'nativeName': 'Türkmen'}],\n 'latlng': [33.0, 65.0],\n 'name': 'Afghanistan',\n 'nativeName': 'افغانستان',\n 'numericCode': '004',\n 'population': 27657145,\n 'region': 'Asia',\n 'regionalBlocs': [{'acronym': 'SAARC',\n 'name': 'South Asian Association for Regional Cooperation',\n 'otherAcronyms': [],\n 'otherNames': []}],\n 'subregion': 'Southern Asia',\n 'timezones': ['UTC+04:30'],\n 'topLevelDomain': ['.af'],\n 'translations': {'br': 'Afeganistão',\n 'de': 'Afghanistan',\n 'es': 'Afganistán',\n 'fa': 'افغانستان',\n 'fr': 'Afghanistan',\n 'hr': 'Afganistan',\n 'it': 'Afghanistan',\n 'ja': 'アフガニスタン',\n 'nl': 'Afghanistan',\n 'pt': 'Afeganistão'}}]\n```\n\nWe use _json()_ method from response object, if the we are fetching JSON data. For txt, html, xml and other file formats we can use _text_.\n\n### Creating a Package\n\nWe organize a large number of files in different folders and sub-folders based on some criteria, so that we can find and manage them easily. As you know, a module can contain multiple objects, such as classes, functions, etc. A package can contain one or more relevant modules. A package is actually a folder containing one or more module files. Let us create a package named mypackage, using the following steps:\n\nCreate a new folder named mypackage inside 30DaysOfPython folder\nCreate an empty **__init__**.py file in the mypackage folder.\nCreate modules arithmetic.py and greet.py with following code:\n\n```py\n# mypackage/arithmetics.py\n# arithmetics.py\ndef add_numbers(*args):\n total = 0\n for num in args:\n total += num\n return total\n\n\ndef subtract(a, b):\n return (a - b)\n\n\ndef multiple(a, b):\n return a * b\n\n\ndef division(a, b):\n return a / b\n\n\ndef remainder(a, b):\n return a % b\n\n\ndef power(a, b):\n return a ** b\n```\n\n```py\n# mypackage/greet.py\n# greet.py\ndef greet_person(firstname, lastname):\n return f'{firstname} {lastname}, welcome to 30DaysOfPython Challenge!'\n```\n\nThe folder structure of your package should look like this:\n\n```sh\n─ mypackage\n ├── __init__.py\n ├── arithmetic.py\n └── greet.py\n```\n\nNow let's open the python interactive shell and try the package we have created:\n\n```sh\nasabeneh@Asabeneh:~/Desktop/30DaysOfPython$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> from mypackage import arithmetics\n>>> arithmetics.add_numbers(1, 2, 3, 5)\n11\n>>> arithmetics.subtract(5, 3)\n2\n>>> arithmetics.multiple(5, 3)\n15\n>>> arithmetics.division(5, 3)\n1.6666666666666667\n>>> arithmetics.remainder(5, 3)\n2\n>>> arithmetics.power(5, 3)\n125\n>>> from mypackage import greet\n>>> greet.greet_person('Asabeneh', 'Yetayeh')\n'Asabeneh Yetayeh, welcome to 30DaysOfPython Challenge!'\n>>>\n```\n\nAs you can see our package works perfectly. The package folder contains a special file called **__init__**.py - it stores the package's content. If we put **__init__**.py in the package folder, python start recognizes it as a package.\nThe **__init__**.py exposes specified resources from its modules to be imported to other python files. An empty **__init__**.py file makes all functions available when a package is imported. The **__init__**.py is essential for the folder to be recognized by Python as a package.\n\n### Further Information About Packages\n\n- Database\n - SQLAlchemy or SQLObject - Object oriented access to several different database systems\n - _pip install SQLAlchemy_\n- Web Development\n - Django - High-level web framework.\n - _pip install django_\n - Flask - micro framework for Python based on Werkzeug, Jinja 2. (It's BSD licensed)\n - _pip install flask_\n- HTML Parser\n - [Beautiful Soup](https://www.crummy.com/software/BeautifulSoup/bs4/doc/) - HTML/XML parser designed for quick turnaround projects like screen-scraping, will accept bad markup.\n - _pip install beautifulsoup4_\n - PyQuery - implements jQuery in Python; faster than BeautifulSoup, apparently.\n\n- XML Processing\n - ElementTree - The Element type is a simple but flexible container object, designed to store hierarchical data structures, such as simplified XML infosets, in memory. --Note: Python 2.5 and up has ElementTree in the Standard Library\n- GUI\n - PyQt - Bindings for the cross-platform Qt framework.\n - TkInter - The traditional Python user interface toolkit.\n- Data Analysis, Data Science and Machine learning\n - Numpy: Numpy(numeric python) is known as one of the most popular machine learning library in Python.\n - Pandas: is a data analysis, data science and a machine learning library in Python that provides data structures of high-level and a wide variety of tools for analysis.\n - SciPy: SciPy is a machine learning library for application developers and engineers. SciPy library contains modules for optimization, linear algebra, integration, image processing, and statistics.\n - Scikit-Learn: It is NumPy and SciPy. It is considered as one of the best libraries for working with complex data.\n - TensorFlow: is a machine learning library built by Google.\n - Keras: is considered as one of the coolest machine learning libraries in Python. It provides an easier mechanism to express neural networks. Keras also provides some of the best utilities for compiling models, processing data-sets, visualization of graphs, and much more.\n- Network:\n - requests: is a package which we can use to send requests to a server(GET, POST, DELETE, PUT)\n - _pip install requests_\n\n🌕 You are always progressing and you are a head of 20 steps to your way to greatness. Now do some exercises for your brain and muscles.\n\n## Exercises: Day 20\n\n1. Read this url and find the 10 most frequent words. romeo_and_juliet = 'http://www.gutenberg.org/files/1112/1112.txt'\n2. Read the cats API and cats_api = 'https://api.thecatapi.com/v1/breeds' and find :\n 1. the min, max, mean, median, standard deviation of cats' weight in metric units.\n 2. the min, max, mean, median, standard deviation of cats' lifespan in years.\n 3. Create a frequency table of country and breed of cats\n3. Read the [countries API](https://restcountries.eu/rest/v2/all) and find\n 1. the 10 largest countries\n 2. the 10 most spoken languages\n 3. the total number of languages in the countries API\n4. UCI is one of the most common places to get data sets for data science and machine learning. Read the content of UCL (https://archive.ics.uci.edu/ml/datasets.php). Without additional libraries it will be difficult, so you may try it with BeautifulSoup4\n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 19](../19_Day_File_handling/19_file_handling.md) | [Day 21 >>](../21_Day_Classes_and_objects/21_classes_and_objects.md)\n"
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"content": "def add_numbers(*args):\n total = 0\n for num in args:\n total += num\n return total\n\n\ndef subtract(a, b):\n return (a - b)\n\n\ndef multiple(a, b):\n return a * b\n\n\ndef division(a, b):\n return a / b\n\n\ndef remainder(a, b):\n return a % b\n\n\ndef power(a, b):\n return a ** b"
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"path": "20_Day_Python_package_manager/greet.py",
"content": "def greet_person(firstname, lastname):\n return f'{firstname} {lastname}, welcome to 30DaysOfPython Challenge!'"
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\n\n[<< Day 20](../20_Day_Python_package_manager/20_python_package_manager.md) | [Day 22 >>](../22_Day_Web_scraping/22_web_scraping.md)\n\n\n\n- [📘 Day 21](#-day-21)\n - [Classes and Objects](#classes-and-objects)\n - [Creating a Class](#creating-a-class)\n - [Creating an Object](#creating-an-object)\n - [Class Constructor](#class-constructor)\n - [Object Methods](#object-methods)\n - [Object Default Methods](#object-default-methods)\n - [Method to Modify Class Default Values](#method-to-modify-class-default-values)\n - [Inheritance](#inheritance)\n - [Overriding parent method](#overriding-parent-method)\n - [💻 Exercises: Day 21](#-exercises-day-21)\n - [Exercises: Level 1](#exercises-level-1)\n - [Exercises: Level 2](#exercises-level-2)\n - [Exercises: Level 3](#exercises-level-3)\n\n# 📘 Day 21\n\n## Classes and Objects\n\nPython is an object oriented programming language. Everything in Python is an object, with its properties and methods. A number, string, list, dictionary, tuple, set etc. used in a program is an object of a corresponding built-in class. We create class to create an object. A class is like an object constructor, or a \"blueprint\" for creating objects. We instantiate a class to create an object. The class defines attributes and the behavior of the object, while the object, on the other hand, represents the class.\n\nWe have been working with classes and objects right from the beginning of this challenge unknowingly. Every element in a Python program is an object of a class.\nLet us check if everything in python is a class:\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> num = 10\n>>> type(num)\n\n>>> string = 'string'\n>>> type(string)\n\n>>> boolean = True\n>>> type(boolean)\n\n>>> lst = []\n>>> type(lst)\n\n>>> tpl = ()\n>>> type(tpl)\n\n>>> set1 = set()\n>>> type(set1)\n\n>>> dct = {}\n>>> type(dct)\n\n```\n\n### Creating a Class\n\nTo create a class we need the key word **class** followed by the name and colon. Class name should be **CamelCase**.\n\n```sh\n# syntax\nclass ClassName:\n code goes here\n```\n\n**Example:**\n\n```py\nclass Person:\n pass\nprint(Person)\n```\n\n```sh\n<__main__.Person object at 0x10804e510>\n```\n\n### Creating an Object\n\nWe can create an object by calling the class.\n\n```py\np = Person()\nprint(p)\n```\n\n### Class Constructor\n\nIn the examples above, we have created an object from the Person class. However, a class without a constructor is not really useful in real applications. Let us use constructor function to make our class more useful. Like the constructor function in Java or JavaScript, Python has also a built-in **__init__**() constructor function. The **__init__** constructor function has self parameter which is a reference to the current instance of the class\n**Examples:**\n\n```py\nclass Person:\n def __init__ (self, name):\n # self allows to attach parameter to the class\n self.name =name\n\np = Person('Asabeneh')\nprint(p.name)\nprint(p)\n```\n\n```sh\n# output\nAsabeneh\n<__main__.Person object at 0x2abf46907e80>\n```\n\nLet us add more parameters to the constructor function.\n\n```py\nclass Person:\n def __init__(self, firstname, lastname, age, country, city):\n self.firstname = firstname\n self.lastname = lastname\n self.age = age\n self.country = country\n self.city = city\n\n\np = Person('Asabeneh', 'Yetayeh', 250, 'Finland', 'Helsinki')\nprint(p.firstname)\nprint(p.lastname)\nprint(p.age)\nprint(p.country)\nprint(p.city)\n```\n\n```sh\n# output\nAsabeneh\nYetayeh\n250\nFinland\nHelsinki\n```\n\n### Object Methods\n\nObjects can have methods. The methods are functions which belong to the object.\n\n**Example:**\n\n```py\nclass Person:\n def __init__(self, firstname, lastname, age, country, city):\n self.firstname = firstname\n self.lastname = lastname\n self.age = age\n self.country = country\n self.city = city\n def person_info(self):\n return f'{self.firstname} {self.lastname} is {self.age} years old. He lives in {self.city}, {self.country}'\n\np = Person('Asabeneh', 'Yetayeh', 250, 'Finland', 'Helsinki')\nprint(p.person_info())\n```\n\n```sh\n# output\nAsabeneh Yetayeh is 250 years old. He lives in Helsinki, Finland\n```\n\n### Object Default Methods\n\nSometimes, you may want to have default values for your object methods. If we give default values for the parameters in the constructor, we can avoid errors when we call or instantiate our class without parameters. Let's see how it looks:\n\n**Example:**\n\n```py\nclass Person:\n def __init__(self, firstname='Asabeneh', lastname='Yetayeh', age=250, country='Finland', city='Helsinki'):\n self.firstname = firstname\n self.lastname = lastname\n self.age = age\n self.country = country\n self.city = city\n\n def person_info(self):\n return f'{self.firstname} {self.lastname} is {self.age} years old. He lives in {self.city}, {self.country}.'\n\np1 = Person()\nprint(p1.person_info())\np2 = Person('John', 'Doe', 30, 'Nomanland', 'Noman city')\nprint(p2.person_info())\n```\n\n```sh\n# output\nAsabeneh Yetayeh is 250 years old. He lives in Helsinki, Finland.\nJohn Doe is 30 years old. He lives in Noman city, Nomanland.\n```\n\n### Method to Modify Class Default Values\n\nIn the example below, the person class, all the constructor parameters have default values. In addition to that, we have skills parameter, which we can access using a method. Let us create add_skill method to add skills to the skills list.\n\n```py\nclass Person:\n def __init__(self, firstname='Asabeneh', lastname='Yetayeh', age=250, country='Finland', city='Helsinki'):\n self.firstname = firstname\n self.lastname = lastname\n self.age = age\n self.country = country\n self.city = city\n self.skills = []\n\n def person_info(self):\n return f'{self.firstname} {self.lastname} is {self.age} years old. He lives in {self.city}, {self.country}.'\n def add_skill(self, skill):\n self.skills.append(skill)\n\np1 = Person()\nprint(p1.person_info())\np1.add_skill('HTML')\np1.add_skill('CSS')\np1.add_skill('JavaScript')\np2 = Person('John', 'Doe', 30, 'Nomanland', 'Noman city')\nprint(p2.person_info())\nprint(p1.skills)\nprint(p2.skills)\n```\n\n```sh\n# output\nAsabeneh Yetayeh is 250 years old. He lives in Helsinki, Finland.\nJohn Doe is 30 years old. He lives in Noman city, Nomanland.\n['HTML', 'CSS', 'JavaScript']\n[]\n```\n\n### Inheritance\n\nUsing inheritance we can reuse parent class code. Inheritance allows us to define a class that inherits all the methods and properties from parent class. The parent class or super or base class is the class which gives all the methods and properties. Child class is the class that inherits from another or parent class.\nLet us create a student class by inheriting from person class.\n\n```py\nclass Student(Person):\n pass\n\n\ns1 = Student('Eyob', 'Yetayeh', 30, 'Finland', 'Helsinki')\ns2 = Student('Lidiya', 'Teklemariam', 28, 'Finland', 'Espoo')\nprint(s1.person_info())\ns1.add_skill('JavaScript')\ns1.add_skill('React')\ns1.add_skill('Python')\nprint(s1.skills)\n\nprint(s2.person_info())\ns2.add_skill('Organizing')\ns2.add_skill('Marketing')\ns2.add_skill('Digital Marketing')\nprint(s2.skills)\n\n```\n\n```sh\noutput\nEyob Yetayeh is 30 years old. He lives in Helsinki, Finland.\n['JavaScript', 'React', 'Python']\nLidiya Teklemariam is 28 years old. He lives in Espoo, Finland.\n['Organizing', 'Marketing', 'Digital Marketing']\n```\n\nWe did not call the **__init__**() constructor in the child class. If we didn't call it then we can still access all the properties from the parent. But if we do call the constructor we can access the parent properties by calling _super_. \nWe can add a new method to the child or we can override the parent class methods by creating the same method name in the child class. When we add the **__init__**() function, the child class will no longer inherit the parent's **__init__**() function.\n\n### Overriding parent method\n\n```py\nclass Student(Person):\n def __init__ (self, firstname='Asabeneh', lastname='Yetayeh',age=250, country='Finland', city='Helsinki', gender='male'):\n self.gender = gender\n super().__init__(firstname, lastname,age, country, city)\n def person_info(self):\n gender = 'He' if self.gender =='male' else 'She'\n return f'{self.firstname} {self.lastname} is {self.age} years old. {gender} lives in {self.city}, {self.country}.'\n\ns1 = Student('Eyob', 'Yetayeh', 30, 'Finland', 'Helsinki','male')\ns2 = Student('Lidiya', 'Teklemariam', 28, 'Finland', 'Espoo', 'female')\nprint(s1.person_info())\ns1.add_skill('JavaScript')\ns1.add_skill('React')\ns1.add_skill('Python')\nprint(s1.skills)\n\nprint(s2.person_info())\ns2.add_skill('Organizing')\ns2.add_skill('Marketing')\ns2.add_skill('Digital Marketing')\nprint(s2.skills)\n```\n\n```sh\nEyob Yetayeh is 30 years old. He lives in Helsinki, Finland.\n['JavaScript', 'React', 'Python']\nLidiya Teklemariam is 28 years old. She lives in Espoo, Finland.\n['Organizing', 'Marketing', 'Digital Marketing']\n```\n\nWe can use super() built-in function or the parent name Person to automatically inherit the methods and properties from its parent. In the example above we override the parent method. The child method has a different feature, it can identify, if the gender is male or female and assign the proper pronoun(He/She).\n\n🌕 Now, you are fully charged with a super power of programming. Now do some exercises for your brain and muscles.\n\n## 💻 Exercises: Day 21\n\n### Exercises: Level 1\n\n1. Python has the module called _statistics_ and we can use this module to do all the statistical calculations. However, to learn how to make function and reuse function let us try to develop a program, which calculates the measure of central tendency of a sample (mean, median, mode) and measure of variability (range, variance, standard deviation). In addition to those measures, find the min, max, count, percentile, and frequency distribution of the sample. You can create a class called Statistics and create all the functions that do statistical calculations as methods for the Statistics class. Check the output below.\n\n```py\nages = [31, 26, 34, 37, 27, 26, 32, 32, 26, 27, 27, 24, 32, 33, 27, 25, 26, 38, 37, 31, 34, 24, 33, 29, 26]\n\nprint('Count:', data.count()) # 25\nprint('Sum: ', data.sum()) # 744\nprint('Min: ', data.min()) # 24\nprint('Max: ', data.max()) # 38\nprint('Range: ', data.range()) # 14\nprint('Mean: ', data.mean()) # 30\nprint('Median: ', data.median()) # 29\nprint('Mode: ', data.mode()) # {'mode': 26, 'count': 5}\nprint('Standard Deviation: ', data.std()) # 4.2\nprint('Variance: ', data.var()) # 17.5\nprint('Frequency Distribution: ', data.freq_dist()) # [(20.0, 26), (16.0, 27), (12.0, 32), (8.0, 37), (8.0, 34), (8.0, 33), (8.0, 31), (8.0, 24), (4.0, 38), (4.0, 29), (4.0, 25)]\n```\n\n```sh\n# you output should look like this\nprint(data.describe())\nCount: 25\nSum: 744\nMin: 24\nMax: 38\nRange: 14\nMean: 30\nMedian: 29\nMode: (26, 5)\nVariance: 17.5\nStandard Deviation: 4.2\nFrequency Distribution: [(20.0, 26), (16.0, 27), (12.0, 32), (8.0, 37), (8.0, 34), (8.0, 33), (8.0, 31), (8.0, 24), (4.0, 38), (4.0, 29), (4.0, 25)]\n```\n\n### Exercises: Level 2\n\n1. Create a class called PersonAccount. It has firstname, lastname, incomes, expenses properties and it has total_income, total_expense, account_info, add_income, add_expense and account_balance methods. Incomes is a set of incomes and its description. The same goes for expenses. \n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 20](../20_Day_Python_package_manager/20_python_package_manager.md) | [Day 22 >>](../22_Day_Web_scraping/22_web_scraping.md)\n"
},
{
"path": "22_Day_Web_scraping/22_web_scraping.md",
"content": "
\n\n[<< Day 21](../21_Day_Classes_and_objects/21_classes_and_objects.md) | [Day 23 >>](../23_Day_Virtual_environment/23_virtual_environment.md)\n\n\n\n- [📘 Day 22](#-day-22)\n - [Python Web Scraping](#python-web-scraping)\n - [What is Web Scrapping](#what-is-web-scrapping)\n - [💻 Exercises: Day 22](#-exercises-day-22)\n\n# 📘 Day 22\n\n## Python Web Scraping\n\n### What is Web Scrapping\n\nThe internet is full of huge amount of data which can be used for different purposes. To collect this data we need to know how to scrape data from a website.\n\nWeb scraping is the process of extracting and collecting data from websites and storing it on a local machine or in a database.\n\nIn this section, we will use beautifulsoup and requests package to scrape data. The package version we are using is beautifulsoup 4.\n\nTo start scraping websites you need _requests_, _beautifoulSoup4_ and a _website_.\n\n```sh\npip install requests\npip install beautifulsoup4\n```\n\nTo scrape data from websites, basic understanding of HTML tags and CSS selectors is needed. We target content from a website using HTML tags, classes or/and ids.\nLet us import the requests and BeautifulSoup module\n\n```py\nimport requests\nfrom bs4 import BeautifulSoup\n```\n\nLet us declare url variable for the website which we are going to scrape.\n\n```py\n\nimport requests\nfrom bs4 import BeautifulSoup\nurl = 'https://archive.ics.uci.edu/ml/datasets.php'\n\n# Lets use the requests get method to fetch the data from url\n\nresponse = requests.get(url)\n# lets check the status\nstatus = response.status_code\nprint(status) # 200 means the fetching was successful\n```\n\n```sh\n200\n```\n\nUsing beautifulSoup to parse content from the page\n\n```py\nimport requests\nfrom bs4 import BeautifulSoup\nurl = 'https://archive.ics.uci.edu/ml/datasets.php'\n\nresponse = requests.get(url)\ncontent = response.content # we get all the content from the website\nsoup = BeautifulSoup(content, 'html.parser') # beautiful soup will give a chance to parse\nprint(soup.title) # UCI Machine Learning Repository: Data Sets\nprint(soup.title.get_text()) # UCI Machine Learning Repository: Data Sets\nprint(soup.body) # gives the whole page on the website\nprint(response.status_code)\n\ntables = soup.find_all('table', {'cellpadding':'3'})\n# We are targeting the table with cellpadding attribute with the value of 3\n# We can select using id, class or HTML tag , for more information check the beautifulsoup doc\ntable = tables[0] # the result is a list, we are taking out data from it\nfor td in table.find('tr').find_all('td'):\n print(td.text)\n```\n\nIf you run this code, you can see that the extraction is half done. You can continue doing it because it is part of exercise 1.\nFor reference check the [beautifulsoup documentation](https://www.crummy.com/software/BeautifulSoup/bs4/doc/#quick-start)\n\n🌕 You are so special, you are progressing everyday. You are left with only eight days to your way to greatness. Now do some exercises for your brain and muscles.\n\n## 💻 Exercises: Day 22\n\n1. Scrape the following website and store the data as json file(url = 'http://www.bu.edu/president/boston-university-facts-stats/').\n1. Extract the table in this url (https://archive.ics.uci.edu/ml/datasets.php) and change it to a json file\n2. Scrape the presidents table and store the data as json(https://en.wikipedia.org/wiki/List_of_presidents_of_the_United_States). The table is not very structured and the scrapping may take very long time.\n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 21](../21_Day_Web_scraping/21_class_and_object.md) | [Day 23 >>](../23_Day_Virtual_environment/23_virtual_environment.md)\n"
},
{
"path": "22_Day_Web_scraping/scrapped_data.json",
"content": "[\n {\n \"category\": \"Community\",\n \"Student Body\": \"34,589\",\n \"Living Alumni\": \"398,195\",\n \"Total Employees\": \"10,517\",\n \"Faculty\": \"4,171\",\n \"Nondegree Students\": \"2,008\",\n \"Graduate & Professional Students\": \"15,645\",\n \"Undergraduate Students\": \"16,936\"\n },\n {\n \"category\": \"Campus\",\n \"Classrooms\": \"834\",\n \"Buildings\": \"370\",\n \"Laboratories\": \"1,681\",\n \"Libraries\": \"21\",\n \"Campus Area (acres)\": \"169\"\n },\n {\n \"category\": \"Academics\",\n \"Study Abroad Programs\": \"70+\",\n \"Average Class Size\": \"27\",\n \"Faculty\": \"4,171\",\n \"Student/Faculty Ratio\": \"10:1\",\n \"Schools and Colleges\": \"17\",\n \"Programs of Study\": \"300+\"\n },\n {\n \"category\": \"Grant & Contract Awards\",\n \"Research Awards\": \"$574.1M\",\n \"BMC Clinical Research Grants\": \"$88.0M\"\n },\n {\n \"category\": \"Undergraduate Financial Aid & Scholarships\",\n \"Average Total Need-Based Financial Aid\": \"$46,252\",\n \"Average Need-Based Grant/Scholarship\": \"$40,969\",\n \"Grants & Scholarships (need-based)\": \"$275.6M\",\n \"Grants & Scholarships (non-need-based)\": \"$28.7M\"\n },\n {\n \"category\": \"Student Life\",\n \"Community Service Hours\": \"1.6M+\",\n \"Alternative Service Breaks Participants\": \"300+\",\n \"BU on Social\": \"new accounts daily\",\n \"Cultural & Religious Organizations\": \"60+\",\n \"Community Service & Justice Organizations\": \"80+\",\n \"Academic & Professional Organizations\": \"120+\",\n \"Art & Performance Organizations\": \"60+\",\n \"Student Organizations\": \"450+\",\n \"First-Year Student Outreach Project Volunteers\": \"800+\"\n },\n {\n \"category\": \"Research\",\n \"Faculty Publications\": \"6,000+\",\n \"Student UROP Participants\": \"450+\",\n \"Centers & Institutes\": \"130+\"\n },\n {\n \"category\": \"International Community\",\n \"Global Initiatives\": \"300+\",\n \"Cultural Student Groups\": \"40+\",\n \"Alumni Countries\": \"180+\",\n \"International Students\": \"11,000+\"\n },\n {\n \"category\": \"Athletics\",\n \"Intramural Sports & Tournaments\": \"15+\",\n \"Club and Intramural Sports Participants\": \"7,000+\",\n \"Club Sports Teams\": \"50\",\n \"Varsity Sports\": \"24\"\n }\n]"
},
{
"path": "23_Day_Virtual_environment/23_virtual_environment.md",
"content": "
\n\n[<< Day 22](../22_Day_Web_scraping/22_web_scraping.md) | [Day 24 >>](../24_Day_Statistics/24_statistics.md)\n\n\n\n- [📘 Day 23](#-day-23)\n - [Setting up Virtual Environments](#setting-up-virtual-environments)\n - [💻 Exercises: Day 23](#-exercises-day-23)\n\n# 📘 Day 23\n\n## Setting up Virtual Environments\n\nTo start with project, it would be better to have a virtual environment. Virtual environment can help us to create an isolated or separate environment. This will help us to avoid conflicts in dependencies across projects. If you write pip freeze on your terminal you will see all the installed packages on your computer. If we use virtualenv, we will access only packages which are specific for that project. Open your terminal and install virtualenv\n\n```sh\nasabeneh@Asabeneh:~$ pip install virtualenv\n```\n\nInside the 30DaysOfPython folder create a flask_project folder.\n\nAfter installing the virtualenv package go to your project folder and create a virtual env by writing:\n\nFor Mac/Linux:\n```sh\nasabeneh@Asabeneh:~/Desktop/30DaysOfPython/flask_project\\$ virtualenv venv\n\n```\n\nFor Windows:\n```sh\nC:\\Users\\User\\Documents\\30DaysOfPython\\flask_project>python -m venv venv\n```\n\nI prefer to call the new project venv, but feel free to name it differently. Let us check if the the venv was created by using ls (or dir for windows command prompt) command.\n\n```sh\nasabeneh@Asabeneh:~/Desktop/30DaysOfPython/flask_project$ ls\nvenv/\n```\n\nLet us activate the virtual environment by writing the following command at our project folder.\n\nFor Mac/Linux:\n```sh\nasabeneh@Asabeneh:~/Desktop/30DaysOfPython/flask_project$ source venv/bin/activate\n```\nActivation of the virtual environment in Windows may very on Windows Power shell and git bash. \n\nFor Windows Power Shell:\n```sh\nC:\\Users\\User\\Documents\\30DaysOfPython\\flask_project> venv\\Scripts\\activate\n```\n\nFor Windows Git bash:\n```sh\nC:\\Users\\User\\Documents\\30DaysOfPython\\flask_project> venv\\Scripts\\. activate\n```\n\nAfter you write the activation command, your project directory will start with venv. See the example below.\n\n```sh\n(venv) asabeneh@Asabeneh:~/Desktop/30DaysOfPython/flask_project$\n```\n\nNow, lets check the available packages in this project by writing pip freeze. You will not see any packages.\n\nWe are going to do a small flask project so let us install flask package to this project.\n\n```sh\n(venv) asabeneh@Asabeneh:~/Desktop/30DaysOfPython/flask_project$ pip install Flask\n```\n\nNow, let us write pip freeze to see a list of installed packages in the project:\n\n```sh\n(venv) asabeneh@Asabeneh:~/Desktop/30DaysOfPython/flask_project$ pip freeze\nClick==7.0\nFlask==1.1.1\nitsdangerous==1.1.0\nJinja2==2.10.3\nMarkupSafe==1.1.1\nWerkzeug==0.16.0\n```\n\nWhen you finish you should dactivate active project using _deactivate_.\n\n```sh\n(venv) asabeneh@Asabeneh:~/Desktop/30DaysOfPython$ deactivate\n```\n\nThe necessary modules to work with flask are installed. Now, your project directory is ready for a flask project. You should include the venv to your .gitignore file not to push it to github.\n\n## 💻 Exercises: Day 23\n\n1. Create a project directory with a virtual environment based on the example given above.\n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 22](../22_Day_Web_scraping/22_web_scraping.md) | [Day 24 >>](../24_Day_Statistics/24_statistics.md)\n"
},
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"path": "24_Day_Statistics/24_statistics.md",
"content": "
\n\n[<< Day 24](../24_Day_Statistics/24_statistics.md) | [Day 26 >>](../26_Day_Python_web/26_python_web.md)\n\n\n\n- [📘 Day 25](#-day-25)\n - [Pandas](#pandas)\n - [Installing Pandas](#installing-pandas)\n - [Importing Pandas](#importing-pandas)\n - [Creating Pandas Series with Default Index](#creating-pandas-series-with-default-index)\n - [Creating Pandas Series with custom index](#creating--pandas-series-with-custom-index)\n - [Creating Pandas Series from a Dictionary](#creating-pandas-series-from-a-dictionary)\n - [Creating a Constant Pandas Series](#creating-a-constant-pandas-series)\n - [Creating a Pandas Series Using Linspace](#creating-a--pandas-series-using-linspace)\n - [DataFrames](#dataframes)\n - [Creating DataFrames from List of Lists](#creating-dataframes-from-list-of-lists)\n - [Creating DataFrame Using Dictionary](#creating-dataframe-using-dictionary)\n - [Creating DataFrames from a List of Dictionaries](#creating-dataframes-from-a-list-of-dictionaries)\n - [Reading CSV File Using Pandas](#reading-csv-file-using-pandas)\n - [Data Exploration](#data-exploration)\n - [Modifying a DataFrame](#modifying-a-dataframe)\n - [Creating a DataFrame](#creating-a-dataframe)\n - [Adding a New Column](#adding-a-new-column)\n - [Modifying column values](#modifying-column-values)\n - [Formatting DataFrame columns](#formatting-dataframe-columns)\n - [Checking data types of Column values](#checking-data-types-of-column-values)\n - [Boolean Indexing](#boolean-indexing)\n - [Exercises: Day 25](#exercises-day-25)\n\n# 📘 Day 25\n\n## Pandas\n\nPandas is an open source, high-performance, easy-to-use data structures and data analysis tools for the Python programming language.\nPandas adds data structures and tools designed to work with table-like data which is *Series* and *Data Frames*.\nPandas provides tools for data manipulation:\n\n- reshaping\n- merging\n- sorting\n- slicing\n- aggregation\n- imputation.\nIf you are using anaconda, you do not have install pandas.\n\n### Installing Pandas\n\nFor Mac:\n```py\npip install conda\nconda install pandas\n```\n\nFor Windows:\n```py\npip install conda\npip install pandas\n```\n\nPandas data structure is based on *Series* and *DataFrames*.\n\nA *series* is a *column* and a DataFrame is a *multidimensional table* made up of collection of *series*. In order to create a pandas series we should use numpy to create a one dimensional arrays or a python list.\nLet us see an example of a series:\n\nNames Pandas Series\n\n\n\nCountries Series\n\n\n\nCities Series\n\n\n\nAs you can see, pandas series is just one column of data. If we want to have multiple columns we use data frames. The example below shows pandas DataFrames.\n\nLet us see, an example of a pandas data frame:\n\n\n\nData frame is a collection of rows and columns. Look at the table below; it has many more columns than the example above:\n\n\n\nNext, we will see how to import pandas and how to create Series and DataFrames using pandas\n\n### Importing Pandas\n\n```python\nimport pandas as pd # importing pandas as pd\nimport numpy as np # importing numpy as np\n```\n\n### Creating Pandas Series with Default Index\n\n```python\nnums = [1, 2, 3, 4,5]\ns = pd.Series(nums)\nprint(s)\n```\n\n```sh\n 0 1\n 1 2\n 2 3\n 3 4\n 4 5\n dtype: int64\n```\n\n### Creating Pandas Series with custom index\n\n```python\nnums = [1, 2, 3, 4, 5]\ns = pd.Series(nums, index=[1, 2, 3, 4, 5])\nprint(s)\n```\n\n```sh\n 1 1\n 2 2\n 3 3\n 4 4\n 5 5\n dtype: int64\n```\n\n```python\nfruits = ['Orange','Banana','Mango']\nfruits = pd.Series(fruits, index=[1, 2, 3])\nprint(fruits)\n```\n\n```sh\n 1 Orange\n 2 Banana\n 3 Mango\n dtype: object\n```\n\n### Creating Pandas Series from a Dictionary\n\n```python\ndct = {'name':'Asabeneh','country':'Finland','city':'Helsinki'}\n```\n\n```python\ns = pd.Series(dct)\nprint(s)\n```\n\n```sh\n name Asabeneh\n country Finland\n city Helsinki\n dtype: object\n```\n\n### Creating a Constant Pandas Series\n\n```python\ns = pd.Series(10, index = [1, 2, 3])\nprint(s)\n```\n\n```sh\n 1 10\n 2 10\n 3 10\n dtype: int64\n```\n\n### Creating a Pandas Series Using Linspace\n\n```python\ns = pd.Series(np.linspace(5, 20, 10)) # linspace(starting, end, items)\nprint(s)\n```\n\n```sh\n 0 5.000000\n 1 6.666667\n 2 8.333333\n 3 10.000000\n 4 11.666667\n 5 13.333333\n 6 15.000000\n 7 16.666667\n 8 18.333333\n 9 20.000000\n dtype: float64\n```\n\n## DataFrames\n\nPandas data frames can be created in different ways.\n\n### Creating DataFrames from List of Lists\n\n```python\ndata = [\n ['Asabeneh', 'Finland', 'Helsink'],\n ['David', 'UK', 'London'],\n ['John', 'Sweden', 'Stockholm']\n]\ndf = pd.DataFrame(data, columns=['Names','Country','City'])\nprint(df)\n```\n\n
\n\n### Creating DataFrames from a List of Dictionaries\n\n```python\ndata = [\n {'Name': 'Asabeneh', 'Country': 'Finland', 'City': 'Helsinki'},\n {'Name': 'David', 'Country': 'UK', 'City': 'London'},\n {'Name': 'John', 'Country': 'Sweden', 'City': 'Stockholm'}]\ndf = pd.DataFrame(data)\nprint(df)\n```\n\n
\n \n
\n
\n
Name
\n
Country
\n
City
\n
\n \n \n
\n
0
\n
Asabeneh
\n
Finland
\n
Helsinki
\n
\n
\n
1
\n
David
\n
UK
\n
London
\n
\n
\n
2
\n
John
\n
Sweden
\n
Stockholm
\n
\n \n
\n\n## Reading CSV File Using Pandas\n\nTo download the CSV file, what is needed in this example, console/command line is enough:\n\n```sh\ncurl -O https://raw.githubusercontent.com/Asabeneh/30-Days-Of-Python/master/data/weight-height.csv\n```\n\nPut the downloaded file in your working directory.\n\n```python\nimport pandas as pd\n\ndf = pd.read_csv('weight-height.csv')\nprint(df)\n```\n\n### Data Exploration\n\nLet us read only the first 5 rows using head()\n\n```python\nprint(df.head()) # give five rows we can increase the number of rows by passing argument to the head() method\n```\n\n\n
\n \n
\n
\n
Gender
\n
Height
\n
Weight
\n
\n \n \n
\n
0
\n
Male
\n
73.847017
\n
241.893563
\n
\n
\n
1
\n
Male
\n
68.781904
\n
162.310473
\n
\n
\n
2
\n
Male
\n
74.110105
\n
212.740856
\n
\n
\n
3
\n
Male
\n
71.730978
\n
220.042470
\n
\n
\n
4
\n
Male
\n
69.881796
\n
206.349801
\n
\n \n
\n\nLet us also explore the last recordings of the dataframe using the tail() methods.\n\n```python\nprint(df.tail()) # tails give the last five rows, we can increase the rows by passing argument to tail method\n```\n\n
\n \n
\n
\n
Gender
\n
Height
\n
Weight
\n
\n \n \n
\n
9995
\n
Female
\n
66.172652
\n
136.777454
\n
\n
\n
9996
\n
Female
\n
67.067155
\n
170.867906
\n
\n
\n
9997
\n
Female
\n
63.867992
\n
128.475319
\n
\n
\n
9998
\n
Female
\n
69.034243
\n
163.852461
\n
\n
\n
9999
\n
Female
\n
61.944246
\n
113.649103
\n
\n \n
\n\nAs you can see the csv file has three rows: Gender, Height and Weight. If the DataFrame would have a long rows, it would be hard to know all the columns. Therefore, we should use a method to know the columns. we do not know the number of rows. Let's use shape method.\n\n```python\nprint(df.shape) # as you can see 10000 rows and three columns\n```\n\n (10000, 3)\n\nLet us get all the columns using columns.\n\n```python\nprint(df.columns)\n```\n\n Index(['Gender', 'Height', 'Weight'], dtype='object')\n\nNow, let us get a specific column using the column key\n\n```python\nheights = df['Height'] # this is now a series\n```\n\n```python\nprint(heights)\n```\n\n```sh\n 0 73.847017\n 1 68.781904\n 2 74.110105\n 3 71.730978\n 4 69.881796\n ...\n 9995 66.172652\n 9996 67.067155\n 9997 63.867992\n 9998 69.034243\n 9999 61.944246\n Name: Height, Length: 10000, dtype: float64\n```\n\n```python\nweights = df['Weight'] # this is now a series\n```\n\n```python\nprint(weights)\n```\n\n```sh\n 0 241.893563\n 1 162.310473\n 2 212.740856\n 3 220.042470\n 4 206.349801\n ...\n 9995 136.777454\n 9996 170.867906\n 9997 128.475319\n 9998 163.852461\n 9999 113.649103\n Name: Weight, Length: 10000, dtype: float64\n```\n\n```python\nprint(len(heights) == len(weights))\n```\n\n True\n\nThe describe() method provides a descriptive statistical values of a dataset.\n\n```python\nprint(heights.describe()) # give statistical information about height data\n```\n\n```sh\n count 10000.000000\n mean 66.367560\n std 3.847528\n min 54.263133\n 25% 63.505620\n 50% 66.318070\n 75% 69.174262\n max 78.998742\n Name: Height, dtype: float64\n```\n\n```python\nprint(weights.describe())\n```\n\n```sh\n count 10000.000000\n mean 161.440357\n std 32.108439\n min 64.700127\n 25% 135.818051\n 50% 161.212928\n 75% 187.169525\n max 269.989699\n Name: Weight, dtype: float64\n```\n\n```python\nprint(df.describe()) # describe can also give statistical information from a dataFrame\n```\n\n
\n \n
\n
\n
Height
\n
Weight
\n
\n \n \n
\n
count
\n
10000.000000
\n
10000.000000
\n
\n
\n
mean
\n
66.367560
\n
161.440357
\n
\n
\n
std
\n
3.847528
\n
32.108439
\n
\n
\n
min
\n
54.263133
\n
64.700127
\n
\n
\n
25%
\n
63.505620
\n
135.818051
\n
\n
\n
50%
\n
66.318070
\n
161.212928
\n
\n
\n
75%
\n
69.174262
\n
187.169525
\n
\n
\n
max
\n
78.998742
\n
269.989699
\n
\n \n
\n\nSimilar to describe(), the info() method also give information about the dataset.\n\n## Modifying a DataFrame\n\nModifying a DataFrame:\n * We can create a new DataFrame\n * We can create a new column and add it to the DataFrame,\n * we can remove an existing column from a DataFrame,\n * we can modify an existing column in a DataFrame,\n * we can change the data type of column values in the DataFrame\n\n### Creating a DataFrame\n\nAs always, first we import the necessary packages. Now, lets import pandas and numpy, two best friends ever.\n\n```python\nimport pandas as pd\nimport numpy as np\ndata = [\n {\"Name\": \"Asabeneh\", \"Country\":\"Finland\",\"City\":\"Helsinki\"},\n {\"Name\": \"David\", \"Country\":\"UK\",\"City\":\"London\"},\n {\"Name\": \"John\", \"Country\":\"Sweden\",\"City\":\"Stockholm\"}]\ndf = pd.DataFrame(data)\nprint(df)\n```\n\n
\n \n
\n
\n
Name
\n
Country
\n
City
\n
\n \n \n
\n
0
\n
Asabeneh
\n
Finland
\n
Helsinki
\n
\n
\n
1
\n
David
\n
UK
\n
London
\n
\n
\n
2
\n
John
\n
Sweden
\n
Stockholm
\n
\n \n
\n\nAdding a column to a DataFrame is like adding a key to a dictionary.\n\nFirst let's use the previous example to create a DataFrame. After we create the DataFrame, we will start modifying the columns and column values.\n\n### Adding a New Column\n\nLet's add a weight column in the DataFrame\n\n```python\nweights = [74, 78, 69]\ndf['Weight'] = weights\ndf\n```\n\n
\n \n
\n
\n
Name
\n
Country
\n
City
\n
Weight
\n
\n \n \n
\n
0
\n
Asabeneh
\n
Finland
\n
Helsinki
\n
74
\n
\n
\n
1
\n
David
\n
UK
\n
London
\n
78
\n
\n
\n
2
\n
John
\n
Sweden
\n
Stockholm
\n
69
\n
\n \n
\n\nLet's add a height column into the DataFrame aswell\n\n```python\nheights = [173, 175, 169]\ndf['Height'] = heights\nprint(df)\n```\n\n
\n \n
\n
\n
Name
\n
Country
\n
City
\n
Weight
\n
Height
\n
\n \n \n
\n
0
\n
Asabeneh
\n
Finland
\n
Helsinki
\n
74
\n
173
\n
\n
\n
1
\n
David
\n
UK
\n
London
\n
78
\n
175
\n
\n
\n
2
\n
John
\n
Sweden
\n
Stockholm
\n
69
\n
169
\n
\n \n
\n\nAs you can see in the DataFrame above, we did add new columns, Weight and Height. Let's add one additional column called BMI(Body Mass Index) by calculating their BMI using thier mass and height. BMI is mass divided by height squared (in meters) - Weight/Height * Height.\n\nAs you can see, the height is in centimeters, so we shoud change it to meters. Let's modify the height row.\n\n### Modifying column values\n\n```python\ndf['Height'] = df['Height'] * 0.01\ndf\n```\n\n
\n \n
\n
\n
Name
\n
Country
\n
City
\n
Weight
\n
Height
\n
\n \n \n
\n
0
\n
Asabeneh
\n
Finland
\n
Helsinki
\n
74
\n
1.73
\n
\n
\n
1
\n
David
\n
UK
\n
London
\n
78
\n
1.75
\n
\n
\n
2
\n
John
\n
Sweden
\n
Stockholm
\n
69
\n
1.69
\n
\n \n
\n\n```python\n# Using functions makes our code clean, but you can calculate the bmi without one\ndef calculate_bmi ():\n weights = df['Weight']\n heights = df['Height']\n bmi = []\n for w,h in zip(weights, heights):\n b = w/(h*h)\n bmi.append(b)\n return bmi\n\nbmi = calculate_bmi()\n\n```\n\n\n```python\ndf['BMI'] = bmi\ndf\n```\n\n
\n \n
\n
\n
Name
\n
Country
\n
City
\n
Weight
\n
Height
\n
BMI
\n
\n \n \n
\n
0
\n
Asabeneh
\n
Finland
\n
Helsinki
\n
74
\n
1.73
\n
24.725183
\n
\n
\n
1
\n
David
\n
UK
\n
London
\n
78
\n
1.75
\n
25.469388
\n
\n
\n
2
\n
John
\n
Sweden
\n
Stockholm
\n
69
\n
1.69
\n
24.158818
\n
\n \n
\n\n### Formatting DataFrame columns\n\nThe BMI column values of the DataFrame are float with many significant digits after decimal. Let's change it to one significant digit after point.\n\n```python\ndf['BMI'] = round(df['BMI'], 1)\nprint(df)\n```\n\n
\n \n
\n
\n
Name
\n
Country
\n
City
\n
Weight
\n
Height
\n
BMI
\n
\n \n \n
\n
0
\n
Asabeneh
\n
Finland
\n
Helsinki
\n
74
\n
1.73
\n
24.7
\n
\n
\n
1
\n
David
\n
UK
\n
London
\n
78
\n
1.75
\n
25.5
\n
\n
\n
2
\n
John
\n
Sweden
\n
Stockholm
\n
69
\n
1.69
\n
24.2
\n
\n \n
\n\nThe information in the DataFrame seems not yet complete, let's add birth year and current year columns.\n\n```python\nbirth_year = ['1769', '1985', '1990']\ncurrent_year = pd.Series(2020, index=[0, 1,2])\ndf['Birth Year'] = birth_year\ndf['Current Year'] = current_year\ndf\n```\n\n
\n \n
\n
\n
Name
\n
Country
\n
City
\n
Weight
\n
Height
\n
BMI
\n
Birth Year
\n
Current Year
\n
\n \n \n
\n
0
\n
Asabeneh
\n
Finland
\n
Helsinki
\n
74
\n
1.73
\n
24.7
\n
1769
\n
2020
\n
\n
\n
1
\n
David
\n
UK
\n
London
\n
78
\n
1.75
\n
25.5
\n
1985
\n
2020
\n
\n
\n
2
\n
John
\n
Sweden
\n
Stockholm
\n
69
\n
1.69
\n
24.2
\n
1990
\n
2020
\n
\n \n
\n\n## Checking data types of Column values\n\n```python\nprint(df.Weight.dtype)\n```\n\n```sh\n dtype('int64')\n```\n\n```python\ndf['Birth Year'].dtype # it gives string object , we should change this to number\n\n```\n\n```python\ndf['Birth Year'] = df['Birth Year'].astype('int')\nprint(df['Birth Year'].dtype) # let's check the data type now\n```\n\n```sh\n dtype('int32')\n```\n\nNow same for the current year:\n\n```python\ndf['Current Year'] = df['Current Year'].astype('int')\ndf['Current Year'].dtype\n```\n\n```sh\n dtype('int32')\n```\n\nNow, the column values of birth year and current year are integers. We can calculate the age.\n\n```python\nages = df['Current Year'] - df['Birth Year']\nages\n```\n\n 0 251\n 1 35\n 2 30\n dtype: int32\n\n```python\ndf['Ages'] = ages\nprint(df)\n```\n\n
\n \n
\n
\n
Name
\n
Country
\n
City
\n
Weight
\n
Height
\n
BMI
\n
Birth Year
\n
Current Year
\n
Ages
\n
\n \n \n
\n
0
\n
Asabeneh
\n
Finland
\n
Helsinki
\n
74
\n
1.73
\n
24.7
\n
1769
\n
2019
\n
250
\n
\n
\n
1
\n
David
\n
UK
\n
London
\n
78
\n
1.75
\n
25.5
\n
1985
\n
2019
\n
34
\n
\n
\n
2
\n
John
\n
Sweden
\n
Stockholm
\n
69
\n
1.69
\n
24.2
\n
1990
\n
2019
\n
29
\n
\n \n
\n\nThe person in the first row lived so far for 251 years. It is unlikely for someone to live so long. Either it is a typo or the data is cooked. So lets fill that data with average of the columns without including outlier.\n\nmean = (35 + 30)/ 2\n\n```python\nmean = (35 + 30)/ 2\nprint('Mean: ',mean)\t#it is good to add some description to the output, so we know what is what\n```\n\n```sh\n Mean: 32.5\n```\n\n### Boolean Indexing\n\n```python\nprint(df[df['Ages'] > 120])\n```\n\n
\n\n## Exercises: Day 25\n\n1. Read the hacker_news.csv file from data directory\n1. Get the first five rows\n1. Get the last five rows\n1. Get the title column as pandas series\n1. Count the number of rows and columns\n - Filter the titles which contain python\n - Filter the titles which contain JavaScript\n - Explore the data and make sense of it\n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 24](../24_Day_Statistics/24_statistics.md) | [Day 26 >>](../26_Day_Python_web/26_python_web.md)\n"
},
{
"path": "26_Day_Python_web/26_python_web.md",
"content": "
\n\n\n[<< Day 25 ](../25_Day_Pandas/25_pandas.md) | [Day 27 >>](../27_Day_Python_with_mongodb/27_python_with_mongodb.md)\n\n\n\n- [📘 Day 26](#-day-26)\n - [Python for Web](#python-for-web)\n - [Flask](#flask)\n - [Folder structure](#folder-structure)\n - [Setting up your project directory](#setting-up-your-project-directory)\n - [Creating routes](#creating-routes)\n - [Creating templates](#creating-templates)\n - [Python Script](#python-script)\n - [Navigation](#navigation)\n - [Creating a layout](#creating-a-layout)\n - [Serving Static File](#serving-static-file)\n - [Deployment](#deployment)\n - [Creating Heroku account](#creating-heroku-account)\n - [Login to Heroku](#login-to-heroku)\n - [Create requirements and Procfile](#create-requirements-and-procfile)\n - [Pushing project to heroku](#pushing-project-to-heroku)\n - [Exercises: Day 26](#exercises-day-26)\n\n# 📘 Day 26\n\n## Python for Web\n\nPython is a general purpose programming language and it can be used for many places. In this section, we will see how we use Python for the web. There are many Python web frame works. Django and Flask are the most popular ones. Today, we will see how to use Flask for web development.\n\n### Flask\n\nFlask is a web development framework written in Python. Flask uses Jinja2 template engine. Flask can be also used with other modern front libraries such as React.\n\nIf you did not install the virtualenv package yet install it first. Virtual environment will allows to isolate project dependencies from the local machine dependencies.\n\n#### Folder structure\n\nAfter completing all the step, your project file structure should look like this:\n\n```sh\n\n├── Procfile\n├── app.py\n├── env\n│ ├── bin\n├── requirements.txt\n├── static\n│ └── css\n│ └── main.css\n└── templates\n ├── about.html\n ├── home.html\n ├── layout.html\n ├── post.html\n └── result.html\n```\n\n### Setting up your project directory\n\nFollow the following steps to get started with Flask.\n\nStep 1: install virtualenv using the following command.\n\n```sh\npip install virtualenv\n```\n\nStep 2:\n\n```sh\nasabeneh@Asabeneh:~/Desktop$ mkdir python_for_web\nasabeneh@Asabeneh:~/Desktop$ cd python_for_web/\nasabeneh@Asabeneh:~/Desktop/python_for_web$ virtualenv venv\nasabeneh@Asabeneh:~/Desktop/python_for_web$ source venv/bin/activate\n(env) asabeneh@Asabeneh:~/Desktop/python_for_web$ pip freeze\n(env) asabeneh@Asabeneh:~/Desktop/python_for_web$ pip install Flask\n(env) asabeneh@Asabeneh:~/Desktop/python_for_web$ pip freeze\nClick==7.0\nFlask==1.1.1\nitsdangerous==1.1.0\nJinja2==2.10.3\nMarkupSafe==1.1.1\nWerkzeug==0.16.0\n(env) asabeneh@Asabeneh:~/Desktop/python_for_web$\n```\n\nWe created a project director named python_for_web. Inside the project we created a virtual environment *venv* which could be any name but I prefer to call it _venv_. Then we activated the virtual environment. We used pip freeze to check the installed packages in the project directory. The result of pip freeze was empty because a package was not installed yet.\n\nNow, let's create app.py file in the project directory and write the following code. The app.py file will be the main file in the project. The following code has flask module, os module.\n\n### Creating routes\n\nThe home route.\n\n```py\n# let's import the flask\nfrom flask import Flask\nimport os # importing operating system module\n\napp = Flask(__name__)\n\n@app.route('/') # this decorator create the home route\ndef home ():\n return '
Welcome
'\n\nif __name__ == '__main__':\n # for deployment we use the environ\n # to make it work for both production and development\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\nTo run the flask application, write python app.py in the main flask application directory.\n\nAfter you run _python app.py_ check local host 5000.\n\nLet us add additional route.\nCreating about route\n\n```py\n# let's import the flask\nfrom flask import Flask\nimport os # importing operating system module\n\napp = Flask(__name__)\n\n@app.route('/') # this decorator create the home route\ndef home ():\n return '
'\n\nif __name__ == '__main__':\n # for deployment we use the environ\n # to make it work for both production and development\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\nNow, we added the about route in the above code. How about if we want to render an HTML file instead of string? It is possible to render HTML file using the function *render_template*. Let us create a folder called templates and create home.html and about.html in the project directory. Let us also import the *render_template* function from flask.\n\n### Creating templates\n\nCreate the HTML files inside templates folder.\n\nhome.html\n\n```html\n\n\n \n \n \n Home\n \n\n \n
\n \n\n```\n\n### Python Script\n\napp.py\n\n```py\n# let's import the flask\nfrom flask import Flask, render_template\nimport os # importing operating system module\n\napp = Flask(__name__)\n\n@app.route('/') # this decorator create the home route\ndef home ():\n return render_template('home.html')\n\n@app.route('/about')\ndef about():\n return render_template('about.html')\n\nif __name__ == '__main__':\n # for deployment we use the environ\n # to make it work for both production and development\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\nAs you can see to go to different pages or to navigate we need a navigation. Let's add a link to each page or let's create a layout which we use to every page.\n\n### Navigation\n\n```html\n
\n```\n\nNow, we can navigate between the pages using the above link. Let us create additional page which handle form data. You can call it any name, I like to call it post.html.\n\nWe can inject data to the HTML files using Jinja2 template engine.\n\n```py\n# let's import the flask\nfrom flask import Flask, render_template, request, redirect, url_for\nimport os # importing operating system module\n\napp = Flask(__name__)\n\n@app.route('/') # this decorator create the home route\ndef home ():\n techs = ['HTML', 'CSS', 'Flask', 'Python']\n name = '30 Days Of Python Programming'\n return render_template('home.html', techs=techs, name = name, title = 'Home')\n\n@app.route('/about')\ndef about():\n name = '30 Days Of Python Programming'\n return render_template('about.html', name = name, title = 'About Us')\n\n@app.route('/post')\ndef post():\n name = 'Text Analyzer'\n return render_template('post.html', name = name, title = name)\n\n\nif __name__ == '__main__':\n # for deployment\n # to make it work for both production and development\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\nLet's see the templates too:\n\nhome.html\n\n```html\n\n\n \n \n \n Home\n \n\n \n
\n \n\n```\n\n### Creating a layout\n\nIn the template files, there are lots of repeated codes, we can write a layout and we can remove the repetition. Let's create layout.html inside the templates folder.\nAfter we create the layout we will import to every file.\n\n#### Serving Static File\n\nCreate a static folder in your project directory. Inside the static folder create CSS or styles folder and create a CSS stylesheet. We use the *url_for* module to serve the static file. \n\nlayout.html\n\n```html\n\n\n \n \n \n \n \n {% if title %}\n 30 Days of Python - {{ title}}\n {% else %}\n 30 Days of Python\n {% endif %}\n \n\n \n \n
\n \n \n {% block content %} {% endblock %}\n \n \n\n```\n\nNow, lets remove all the repeated code in the other template files and import the layout.html. The href is using _url_for_ function with the name of the route function to connect each navigation route.\n\nhome.html\n\n```html\n{% extends 'layout.html' %} {% block content %}\n
\n
Welcome to {{name}}
\n
\n This application clean texts and analyse the number of word, characters and\n most frequent words in the text. Check it out by click text analyzer at the\n menu. You need the following technologies to build this web application:\n
\n\n{% endblock %}\n```\n\nRequest methods, there are different request methods(GET, POST, PUT, DELETE) are the common request methods which allow us to do CRUD(Create, Read, Update, Delete) operation.\n\nIn the post, route we will use GET and POST method alternative depending on the type of request, check how it looks in the code below. The request method is a function to handle request methods and also to access form data.\napp.py\n\n```py\n# let's import the flask\nfrom flask import Flask, render_template, request, redirect, url_for\nimport os # importing operating system module\n\napp = Flask(__name__)\n# to stop caching static file\napp.config['SEND_FILE_MAX_AGE_DEFAULT'] = 0\n\n\n\n@app.route('/') # this decorator create the home route\ndef home ():\n techs = ['HTML', 'CSS', 'Flask', 'Python']\n name = '30 Days Of Python Programming'\n return render_template('home.html', techs=techs, name = name, title = 'Home')\n\n@app.route('/about')\ndef about():\n name = '30 Days Of Python Programming'\n return render_template('about.html', name = name, title = 'About Us')\n\n@app.route('/result')\ndef result():\n return render_template('result.html')\n\n@app.route('/post', methods= ['GET','POST'])\ndef post():\n name = 'Text Analyzer'\n if request.method == 'GET':\n return render_template('post.html', name = name, title = name)\n if request.method =='POST':\n content = request.form['content']\n print(content)\n return redirect(url_for('result'))\n\nif __name__ == '__main__':\n # for deployment\n # to make it work for both production and development\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\nSo far, we have seen how to use template and how to inject data to template, how to a common layout.\nNow, lets handle static file. Create a folder called static in the project director and create a folder called css. Inside css folder create main.css. Your main. css file will be linked to the layout.html.\n\nYou don't have to write the css file, copy and use it. Let's move on to deployment.\n\n### Deployment\n\n#### Creating Heroku account\n\nHeroku provides a free deployment service for both front end and fullstack applications. Create an account on [heroku](https://www.heroku.com/) and install the heroku [CLI](https://devcenter.heroku.com/articles/heroku-cli) for you machine.\nAfter installing heroku write the following command\n\n#### Login to Heroku\n\n```sh\nasabeneh@Asabeneh:~$ heroku login\nheroku: Press any key to open up the browser to login or q to exit:\n```\n\nLet's see the result by clicking any key from the keyboard. When you press any key from you keyboard it will open the heroku login page and click the login page. Then you will local machine will be connected to the remote heroku server. If you are connected to remote server, you will see this.\n\n```sh\nasabeneh@Asabeneh:~$ heroku login\nheroku: Press any key to open up the browser to login or q to exit:\nOpening browser to https://cli-auth.heroku.com/auth/browser/be12987c-583a-4458-a2c2-ba2ce7f41610\nLogging in... done\nLogged in as asabeneh@gmail.com\nasabeneh@Asabeneh:~$\n```\n\n#### Create requirements and Procfile\n\nBefore we push our code to remote server, we need requirements\n\n- requirements.txt\n- Procfile\n\n```sh\n(env) asabeneh@Asabeneh:~/Desktop/python_for_web$ pip freeze\nClick==7.0\nFlask==1.1.1\nitsdangerous==1.1.0\nJinja2==2.10.3\nMarkupSafe==1.1.1\nWerkzeug==0.16.0\n(env) asabeneh@Asabeneh:~/Desktop/python_for_web$ touch requirements.txt\n(env) asabeneh@Asabeneh:~/Desktop/python_for_web$ pip freeze > requirements.txt\n(env) asabeneh@Asabeneh:~/Desktop/python_for_web$ cat requirements.txt\nClick==7.0\nFlask==1.1.1\nitsdangerous==1.1.0\nJinja2==2.10.3\nMarkupSafe==1.1.1\nWerkzeug==0.16.0\n(env) asabeneh@Asabeneh:~/Desktop/python_for_web$ touch Procfile\n(env) asabeneh@Asabeneh:~/Desktop/python_for_web$ ls\nProcfile env/ static/\napp.py requirements.txt templates/\n(env) asabeneh@Asabeneh:~/Desktop/python_for_web$\n```\n\nThe Procfile will have the command which run the application in the web server in our case on Heroku.\n\n```sh\nweb: python app.py\n```\n\n#### Pushing project to heroku\n\nNow, it is ready to be deployed. Steps to deploy the application on heroku\n\n1. git init\n2. git add .\n3. git commit -m \"commit message\"\n4. heroku create 'name of the app as one word'\n5. git push heroku master\n6. heroku open(to launch the deployed application)\n\nAfter this step you will get an application like [this](http://thirdaysofpython-practice.herokuapp.com/)\n\n## Exercises: Day 26\n\n1. You will build [this application](https://thirtydaysofpython-v1-final.herokuapp.com/). Only the text analyser part is left\n\n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 25 ](../25_Day_Pandas/25_pandas.md) | [Day 27 >>](../27_Day_Python_with_mongodb/27_python_with_mongodb.md)\n"
},
{
"path": "27_Day_Python_with_mongodb/27_python_with_mongodb.md",
"content": "
\n\n[<< Day 26](../26_Day_Python_web/26_python_web.md) | [Day 28 >>](../28_Day_API/28_API.md)\n\n\n\n- [📘 Day 27](#-day-27)\n- [Python with MongoDB](#python-with-mongodb)\n - [MongoDB](#mongodb)\n - [SQL versus NoSQL](#sql-versus-nosql)\n - [Getting Connection String(MongoDB URI)](#getting-connection-stringmongodb-uri)\n - [Connecting Flask application to MongoDB Cluster](#connecting-flask-application-to-mongodb-cluster)\n - [Creating a database and collection](#creating-a-database-and-collection)\n - [Inserting many documents to collection](#inserting-many-documents-to-collection)\n - [MongoDB Find](#mongodb-find)\n - [Find with Query](#find-with-query)\n - [Find query with modifier](#find-query-with-modifier)\n - [Limiting documents](#limiting-documents)\n - [Find with sort](#find-with-sort)\n - [Update with query](#update-with-query)\n - [Delete Document](#delete-document)\n - [Drop a collection](#drop-a-collection)\n - [💻 Exercises: Day 27](#-exercises-day-27)\n\n# 📘 Day 27\n\n# Python with MongoDB\n\nPython is a backend technology and it can be connected with different data base applications. It can be connected to both SQL and noSQL databases. In this section, we connect Python with MongoDB database which is noSQL database. \n\n## MongoDB\n\nMongoDB is a NoSQL database. MongoDB stores data in a JSON like document which make MongoDB very flexible and scalable. Let us see the different terminologies of SQL and NoSQL databases. The following table will make the difference between SQL versus NoSQL databases.\n\n### SQL versus NoSQL\n\n\n\nIn this section, we will focus on a NoSQL database MongoDB. Lets sign up on [mongoDB](https://www.mongodb.com/) by click on the sign in button then click register on the next page.\n\n\n\nComplete the fields and click continue\n\n\n\nSelect the free plan\n\n\n\nChoose the proximate free region and give any name for you cluster.\n\n\n\nNow, a free sandbox is created\n\n\n\nAll local host access\n\n\n\nAdd user and password\n\n\n\nCreate a mongoDB uri link\n\n\n\nSelect Python 3.6 or above driver\n\n\n\n### Getting Connection String(MongoDB URI)\n\nCopy the connection string link and you will get something like this:\n\n```sh\nmongodb+srv://asabeneh:@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority\n```\n\nDo not worry about the url, it is a means to connect your application with mongoDB.\nLet us replace the password placeholder with the password you used to add a user.\n\n**Example:**\n\n```sh\nmongodb+srv://asabeneh:123123123@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority\n```\n\nNow, I replaced everything and the password is 123123 and the name of the database is *thirty_days_python*. This is just an example, your password must be stronger than the example password.\n\nPython needs a mongoDB driver to access mongoDB database. We will use _pymongo_ with _dnspython_ to connect our application with mongoDB base . Inside your project directory install pymongo and dnspython.\n\n```sh\npip install pymongo dnspython\n```\n\nThe \"dnspython\" module must be installed to use mongodb+srv:// URIs. The dnspython is a DNS toolkit for Python. It supports almost all record types.\n\n### Connecting Flask application to MongoDB Cluster\n\n```py\n# let's import the flask\nfrom flask import Flask, render_template\nimport os # importing operating system module\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\nprint(client.list_database_names())\n\napp = Flask(__name__)\nif __name__ == '__main__':\n # for deployment we use the environ\n # to make it work for both production and development\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n\n```\n\nWhen we run the above code we get the default mongoDB databases.\n\n```sh\n['admin', 'local']\n```\n\n### Creating a database and collection\n\nLet us create a database, database and collection in mongoDB will be created if it doesn't exist. Let's create a data base name *thirty_days_of_python* and *students* collection.\n\nTo create a database:\n\n```sh\ndb = client.name_of_databse # we can create a database like this or the second way\ndb = client['name_of_database']\n```\n\n```py\n# let's import the flask\nfrom flask import Flask, render_template\nimport os # importing operating system module\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\n# Creating database\ndb = client.thirty_days_of_python\n# Creating students collection and inserting a document\ndb.students.insert_one({'name': 'Asabeneh', 'country': 'Finland', 'city': 'Helsinki', 'age': 250})\nprint(client.list_database_names())\n\napp = Flask(__name__)\nif __name__ == '__main__':\n # for deployment we use the environ\n # to make it work for both production and development\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\nAfter we create a database, we also created a students collection and we used *insert_one()* method to insert a document.\nNow, the database *thirty_days_of_python* and *students* collection have been created and the document has been inserted.\nCheck your mongoDB cluster and you will see both the database and the collection. Inside the collection, there will be a document.\n\n```sh\n['thirty_days_of_python', 'admin', 'local']\n```\n\nIf you see this on the mongoDB cluster, it means you have successfully created a database and a collection.\n\n\n\nIf you have seen on the figure, the document has been created with a long id which acts as a primary key. Every time we create a document mongoDB create and unique id for it.\n\n### Inserting many documents to collection\n\nThe *insert_one()* method inserts one item at a time if we want to insert many documents at once either we use *insert_many()* method or for loop.\nWe can use for loop to inset many documents at once.\n\n```py\n# let's import the flask\nfrom flask import Flask, render_template\nimport os # importing operating system module\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\n\nstudents = [\n {'name':'David','country':'UK','city':'London','age':34},\n {'name':'John','country':'Sweden','city':'Stockholm','age':28},\n {'name':'Sami','country':'Finland','city':'Helsinki','age':25},\n ]\nfor student in students:\n db.students.insert_one(student)\n\n\napp = Flask(__name__)\nif __name__ == '__main__':\n # for deployment we use the environ\n # to make it work for both production and development\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\n### MongoDB Find\n\nThe *find()* and *findOne()* methods are common method to find data in a collection in mongoDB database. It is similar to the SELECT statement in a MySQL database.\nLet us use the _find_one()_ method to get a document in a database collection.\n\n- \\*find_one({\"\\_id\": ObjectId(\"id\"}): Gets the first occurrence if an id is not provided\n\n```py\n# let's import the flask\nfrom flask import Flask, render_template\nimport os # importing operating system module\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # accessing the database\nstudent = db.students.find_one()\nprint(student)\n\n\napp = Flask(__name__)\nif __name__ == '__main__':\n # for deployment we use the environ\n # to make it work for both production and development\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n\n```\n\n```sh\n{'_id': ObjectId('5df68a21f106fe2d315bbc8b'), 'name': 'Asabeneh', 'country': 'Helsinki', 'city': 'Helsinki', 'age': 250}\n```\n\nThe above query returns the first entry but we can target specific document using specific \\_id. Let us do one example, use David's id to get David object.\n'\\_id':ObjectId('5df68a23f106fe2d315bbc8c')\n\n```py\n# let's import the flask\nfrom flask import Flask, render_template\nimport os # importing operating system module\nfrom bson.objectid import ObjectId # id object\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # accessing the database\nstudent = db.students.find_one({'_id':ObjectId('5df68a23f106fe2d315bbc8c')})\nprint(student)\n\napp = Flask(__name__)\nif __name__ == '__main__':\n # for deployment we use the environ\n # to make it work for both production and development\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\n```sh\n{'_id': ObjectId('5df68a23f106fe2d315bbc8c'), 'name': 'David', 'country': 'UK', 'city': 'London', 'age': 34}\n```\n\nWe have seen, how to use _find_one()_ using the above examples. Let's move one to _find()_\n\n- _find()_: returns all the occurrence from a collection if we don't pass a query object. The object is pymongo.cursor object.\n\n```py\n# let's import the flask\nfrom flask import Flask, render_template\nimport os # importing operating system module\n\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # accessing the database\nstudents = db.students.find()\nfor student in students:\n print(student)\n\napp = Flask(__name__)\nif __name__ == '__main__':\n # for deployment we use the environ\n # to make it work for both production and development\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\n```sh\n{'_id': ObjectId('5df68a21f106fe2d315bbc8b'), 'name': 'Asabeneh', 'country': 'Finland', 'city': 'Helsinki', 'age': 250}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8c'), 'name': 'David', 'country': 'UK', 'city': 'London', 'age': 34}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8d'), 'name': 'John', 'country': 'Sweden', 'city': 'Stockholm', 'age': 28}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8e'), 'name': 'Sami', 'country': 'Finland', 'city': 'Helsinki', 'age': 25}\n```\n\nWe can specify which fields to return by passing second object in the _find({}, {})_. 0 means not include and 1 means include but we can not mix 0 and 1, except for \\_id.\n\n```py\n# let's import the flask\nfrom flask import Flask, render_template\nimport os # importing operating system module\n\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # accessing the database\nstudents = db.students.find({}, {\"_id\":0, \"name\": 1, \"country\":1}) # 0 means not include and 1 means include\nfor student in students:\n print(student)\n\napp = Flask(__name__)\nif __name__ == '__main__':\n # for deployment we use the environ\n # to make it work for both production and development\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\n```sh\n{'name': 'Asabeneh', 'country': 'Finland'}\n{'name': 'David', 'country': 'UK'}\n{'name': 'John', 'country': 'Sweden'}\n{'name': 'Sami', 'country': 'Finland'}\n```\n\n### Find with Query\n\nIn mongoDB find take a query object. We can pass a query object and we can filter the documents we like to filter out.\n\n```py\n# let's import the flask\nfrom flask import Flask, render_template\nimport os # importing operating system module\n\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # accessing the database\n\nquery = {\n \"country\":\"Finland\"\n}\nstudents = db.students.find(query)\n\nfor student in students:\n print(student)\n\n\napp = Flask(__name__)\nif __name__ == '__main__':\n # for deployment we use the environ\n # to make it work for both production and development\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\n```sh\n{'_id': ObjectId('5df68a21f106fe2d315bbc8b'), 'name': 'Asabeneh', 'country': 'Finland', 'city': 'Helsinki', 'age': 250}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8e'), 'name': 'Sami', 'country': 'Finland', 'city': 'Helsinki', 'age': 25}\n```\n\nQuery with modifiers\n\n```py\n# let's import the flask\nfrom flask import Flask, render_template\nimport os # importing operating system module\nimport pymongo\n\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # accessing the database\n\nquery = {\n \"city\":\"Helsinki\"\n}\nstudents = db.students.find(query)\nfor student in students:\n print(student)\n\n\napp = Flask(__name__)\nif __name__ == '__main__':\n # for deployment we use the environ\n # to make it work for both production and development\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\n```sh\n{'_id': ObjectId('5df68a21f106fe2d315bbc8b'), 'name': 'Asabeneh', 'country': 'Finland', 'city': 'Helsinki', 'age': 250}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8e'), 'name': 'Sami', 'country': 'Finland', 'city': 'Helsinki', 'age': 25}\n```\n\n### Find query with modifier\n\n```py\n# let's import the flask\nfrom flask import Flask, render_template\nimport os # importing operating system module\nimport pymongo\n\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # accessing the database\nquery = {\n \"country\":\"Finland\",\n \"city\":\"Helsinki\"\n}\nstudents = db.students.find(query)\nfor student in students:\n print(student)\n\n\napp = Flask(__name__)\nif __name__ == '__main__':\n # for deployment we use the environ\n # to make it work for both production and development\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\n```sh\n{'_id': ObjectId('5df68a21f106fe2d315bbc8b'), 'name': 'Asabeneh', 'country': 'Finland', 'city': 'Helsinki', 'age': 250}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8e'), 'name': 'Sami', 'country': 'Finland', 'city': 'Helsinki', 'age': 25}\n```\n\nQuery with modifiers\n\n```py\n# let's import the flask\nfrom flask import Flask, render_template\nimport os # importing operating system module\nimport pymongo\n\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # accessing the database\nquery = {\"age\":{\"$gt\":30}}\nstudents = db.students.find(query)\nfor student in students:\n print(student)\n\napp = Flask(__name__)\nif __name__ == '__main__':\n # for deployment we use the environ\n # to make it work for both production and development\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\n```sh\n{'_id': ObjectId('5df68a21f106fe2d315bbc8b'), 'name': 'Asabeneh', 'country': 'Finland', 'city': 'Helsinki', 'age': 250}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8c'), 'name': 'David', 'country': 'UK', 'city': 'London', 'age': 34}\n```\n\n```py\n# let's import the flask\nfrom flask import Flask, render_template\nimport os # importing operating system module\nimport pymongo\n\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # accessing the database\nquery = {\"age\":{\"$gt\":30}}\nstudents = db.students.find(query)\nfor student in students:\n print(student)\n```\n\n```sh\n{'_id': ObjectId('5df68a23f106fe2d315bbc8d'), 'name': 'John', 'country': 'Sweden', 'city': 'Stockholm', 'age': 28}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8e'), 'name': 'Sami', 'country': 'Finland', 'city': 'Helsinki', 'age': 25}\n```\n\n### Limiting documents\n\nWe can limit the number of documents we return using the _limit()_ method.\n\n```py\n# let's import the flask\nfrom flask import Flask, render_template\nimport os # importing operating system module\nimport pymongo\n\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # accessing the database\ndb.students.find().limit(3)\n```\n\n### Find with sort\n\nBy default, sort is in ascending order. We can change the sorting to descending order by adding -1 parameter.\n\n```py\n# let's import the flask\nfrom flask import Flask, render_template\nimport os # importing operating system module\nimport pymongo\n\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # accessing the database\nstudents = db.students.find().sort('name')\nfor student in students:\n print(student)\n\n\nstudents = db.students.find().sort('name',-1)\nfor student in students:\n print(student)\n\nstudents = db.students.find().sort('age')\nfor student in students:\n print(student)\n\nstudents = db.students.find().sort('age',-1)\nfor student in students:\n print(student)\n\napp = Flask(__name__)\nif __name__ == '__main__':\n # for deployment we use the environ\n # to make it work for both production and development\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\nAscending order\n\n```sh\n{'_id': ObjectId('5df68a21f106fe2d315bbc8b'), 'name': 'Asabeneh', 'country': 'Finland', 'city': 'Helsinki', 'age': 250}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8c'), 'name': 'David', 'country': 'UK', 'city': 'London', 'age': 34}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8d'), 'name': 'John', 'country': 'Sweden', 'city': 'Stockholm', 'age': 28}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8e'), 'name': 'Sami', 'country': 'Finland', 'city': 'Helsinki', 'age': 25}\n```\n\nDescending order\n\n```sh\n{'_id': ObjectId('5df68a23f106fe2d315bbc8e'), 'name': 'Sami', 'country': 'Finland', 'city': 'Helsinki', 'age': 25}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8d'), 'name': 'John', 'country': 'Sweden', 'city': 'Stockholm', 'age': 28}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8c'), 'name': 'David', 'country': 'UK', 'city': 'London', 'age': 34}\n{'_id': ObjectId('5df68a21f106fe2d315bbc8b'), 'name': 'Asabeneh', 'country': 'Finland', 'city': 'Helsinki', 'age': 250}\n```\n\n### Update with query\n\nWe will use *update_one()* method to update one item. It takes two object one is a query and the second is the new object.\nThe first person, Asabeneh got a very implausible age. Let us update Asabeneh's age.\n\n```py\n# let's import the flask\nfrom flask import Flask, render_template\nimport os # importing operating system module\nimport pymongo\n\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # accessing the database\n\nquery = {'age':250}\nnew_value = {'$set':{'age':38}}\n\ndb.students.update_one(query, new_value)\n# lets check the result if the age is modified\nfor student in db.students.find():\n print(student)\n\n\napp = Flask(__name__)\nif __name__ == '__main__':\n # for deployment we use the environ\n # to make it work for both production and development\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\n```sh\n{'_id': ObjectId('5df68a21f106fe2d315bbc8b'), 'name': 'Asabeneh', 'country': 'Finland', 'city': 'Helsinki', 'age': 38}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8c'), 'name': 'David', 'country': 'UK', 'city': 'London', 'age': 34}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8d'), 'name': 'John', 'country': 'Sweden', 'city': 'Stockholm', 'age': 28}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8e'), 'name': 'Sami', 'country': 'Finland', 'city': 'Helsinki', 'age': 25}\n```\n\nWhen we want to update many documents at once we use *upate_many()* method.\n\n### Delete Document\n\nThe method *delete_one()* deletes one document. The *delete_one()* takes a query object parameter. It only removes the first occurrence.\nLet us remove one John from the collection.\n\n```py\n# let's import the flask\nfrom flask import Flask, render_template\nimport os # importing operating system module\nimport pymongo\n\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # accessing the database\n\nquery = {'name':'John'}\ndb.students.delete_one(query)\n\nfor student in db.students.find():\n print(student)\n# lets check the result if the age is modified\nfor student in db.students.find():\n print(student)\n\n\napp = Flask(__name__)\nif __name__ == '__main__':\n # for deployment we use the environ\n # to make it work for both production and development\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\n```sh\n{'_id': ObjectId('5df68a21f106fe2d315bbc8b'), 'name': 'Asabeneh', 'country': 'Finland', 'city': 'Helsinki', 'age': 38}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8c'), 'name': 'David', 'country': 'UK', 'city': 'London', 'age': 34}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8e'), 'name': 'Sami', 'country': 'Finland', 'city': 'Helsinki', 'age': 25}\n```\n\nAs you can see John has been removed from the collection.\n\nWhen we want to delete many documents we use *delete_many()* method, it takes a query object. If we pass an empty query object to *delete_many({})* it will delete all the documents in the collection.\n\n### Drop a collection\n\nUsing the _drop()_ method we can delete a collection from a database.\n\n```py\n# let's import the flask\nfrom flask import Flask, render_template\nimport os # importing operating system module\nimport pymongo\n\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # accessing the database\ndb.students.drop()\n```\n\nNow, we have deleted the students collection from the database.\n\n## 💻 Exercises: Day 27\n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 26](../26_Day_Python_web/26_python_web.md) | [Day 28 >>](../28_Day_API/28_API.md)\n"
},
{
"path": "28_Day_API/28_API.md",
"content": "
\n\n\n[<< Day 27](../27_Day_Python_with_mongodb/27_python_with_mongodb.md) | [Day 29 >>](../29_Day_Building_API/29_building_API.md)\n\n\n\n- [📘 Day 28](#-day-28)\n- [Application Programming Interface(API)](#application-programming-interfaceapi)\n - [API](#api)\n - [Building API](#building-api)\n - [HTTP(Hypertext Transfer Protocol)](#httphypertext-transfer-protocol)\n - [Structure of HTTP](#structure-of-http)\n - [Initial Request Line(Status Line)](#initial-request-linestatus-line)\n - [Initial Response Line(Status Line)](#initial-response-linestatus-line)\n - [Header Fields](#header-fields)\n - [The message body](#the-message-body)\n - [Request Methods](#request-methods)\n - [💻 Exercises: Day 28](#-exercises-day-28)\n\n# 📘 Day 28\n\n# Application Programming Interface(API)\n\n## API\n\nAPI stands for Application Programming Interface. The kind of API we will cover in this section is going to be Web APIs.\nWeb APIs are the defined interfaces through which interactions happen between an enterprise and applications that use its assets, which also is a Service Level Agreement (SLA) to specify the functional provider and expose the service path or URL for its API users.\n\nIn the context of web development, an API is defined as a set of specifications, such as Hypertext Transfer Protocol (HTTP) request messages, along with a definition of the structure of response messages, usually in an XML or a JavaScript Object Notation (JSON) format.\n\nWeb API has been moving away from Simple Object Access Protocol (SOAP) based web services and service-oriented architecture (SOA) towards more direct representational state transfer (REST) style web resources.\n\nSocial media services, web APIs have allowed web communities to share content and data between communities and different platforms. \n\nUsing API, content that is created in one place dynamically can be posted and updated to multiple locations on the web.\n\nFor example, Twitter's REST API allows developers to access core Twitter data and the Search API provides methods for developers to interact with Twitter Search and trends data.\n\nMany applications provide API end points. Some examples of API such as the countries [API](https://restcountries.eu/rest/v2/all), [cat's breed API](https://api.thecatapi.com/v1/breeds).\n\nIn this section, we will cover a RESTful API that uses HTTP request methods to GET, PUT, POST and DELETE data.\n\n## Building API\n\nRESTful API is an application program interface (API) that uses HTTP requests to GET, PUT, POST and DELETE data. In the previous sections, we have learned about python, flask and mongoDB. We will use the knowledge we acquire to develop a RESTful API using Python flask and mongoDB database. Every application which has CRUD(Create, Read, Update, Delete) operation has an API to create data, to get data, to update data or to delete data from a database.\n\nTo build an API, it is good to understand HTTP protocol and HTTP request and response cycle.\n\n## HTTP(Hypertext Transfer Protocol)\n\nHTTP is an established communication protocol between a client and a server. A client in this case is a browser and server is the place where you access data. HTTP is a network protocol used to deliver resources which could be files on the World Wide Web, whether they are HTML files, image files, query results, scripts, or other file types.\n\nA browser is an HTTP client because it sends requests to an HTTP server (Web server), which then sends responses back to the client.\n\n## Structure of HTTP\n\nHTTP uses client-server model. An HTTP client opens a connection and sends a request message to an HTTP server and the HTTP server returns response message which is the requested resources. When the request response cycle completes the server closes the connection.\n\n\n\nThe format of the request and response messages are similar. Both kinds of messages have\n\n- an initial line,\n- zero or more header lines,\n- a blank line (i.e. a CRLF by itself), and\n- an optional message body (e.g. a file, or query data, or query output).\n\nLet us an example of request and response messages by navigating this site:https://thirtydaysofpython-v1-final.herokuapp.com/. This site has been deployed on Heroku free dyno and in some months may not work because of high request. Support this work to make the server run all the time. \n\n\n\n## Initial Request Line(Status Line)\n\nThe initial request line is different from the response.\nA request line has three parts, separated by spaces:\n\n- method name(GET, POST, HEAD)\n- path of the requested resource,\n- the version of HTTP being used. eg GET / HTTP/1.1\n\nGET is the most common HTTP that helps to get or read resource and POST is a common request method to create resource.\n\n### Initial Response Line(Status Line)\n\nThe initial response line, called the status line, also has three parts separated by spaces:\n\n- HTTP version\n- Response status code that gives the result of the request, and a reason which describes the status code. Example of status lines are:\n HTTP/1.0 200 OK\n or\n HTTP/1.0 404 Not Found\n Notes:\n\nThe most common status codes are:\n200 OK: The request succeeded, and the resulting resource (e.g. file or script output) is returned in the message body.\n500 Server Error\nA complete list of HTTP status code can be found [here](https://httpstatuses.com/). It can be also found [here](https://httpstatusdogs.com/).\n\n### Header Fields\n\nAs you have seen in the above screenshot, header lines provide information about the request or response, or about the object sent in the message body.\n\n```sh\nGET / HTTP/1.1\nHost: thirtydaysofpython-v1-final.herokuapp.com\nConnection: keep-alive\nPragma: no-cache\nCache-Control: no-cache\nUpgrade-Insecure-Requests: 1\nUser-Agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_14_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/79.0.3945.79 Safari/537.36\nSec-Fetch-User: ?1\nAccept: text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.9\nSec-Fetch-Site: same-origin\nSec-Fetch-Mode: navigate\nReferer: https://thirtydaysofpython-v1-final.herokuapp.com/post\nAccept-Encoding: gzip, deflate, br\nAccept-Language: en-GB,en;q=0.9,fi-FI;q=0.8,fi;q=0.7,en-CA;q=0.6,en-US;q=0.5,fr;q=0.4\n```\n\n### The message body\n\nAn HTTP message may have a body of data sent after the header lines. In a response, this is where the requested resource is returned to the client (the most common use of the message body), or perhaps explanatory text if there's an error. In a request, this is where user-entered data or uploaded files are sent to the server.\n\nIf an HTTP message includes a body, there are usually header lines in the message that describe the body. In particular,\n\nThe Content-Type: header gives the MIME-type of the data in the body(text/html, application/json, text/plain, text/css, image/gif).\nThe Content-Length: header gives the number of bytes in the body.\n\n### Request Methods\n\nThe GET, POST, PUT and DELETE are the HTTP request methods which we are going to implement an API or a CRUD operation application.\n\n1. GET: GET method is used to retrieve and get information from the given server using a given URI. Requests using GET should only retrieve data and should have no other effect on the data.\n\n2. POST: POST request is used to create data and send data to the server, for example, creating a new post, file upload, etc. using HTML forms.\n\n3. PUT: Replaces all current representations of the target resource with the uploaded content and we use it modify or update data.\n\n4. DELETE: Removes data\n\n## 💻 Exercises: Day 28\n\n1. Read about API and HTTP\n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 27](../27_Day_Python_with_mongodb/27_python_with_mongodb.md) | [Day 29 >>](../29_Day_Building_API/29_building_API.md)\n"
},
{
"path": "29_Day_Building_API/29_building_API.md",
"content": "
\n\n[<< Day 28](../28_Day_API/28_API.md) | [Day 29 >>](../30_Day_Conclusions/30_conclusions.md)\n\n\n\n- [Day 29](#day-29)\n- [Building API](#building-api)\n - [Structure of an API](#structure-of-an-api)\n - [Retrieving data using get](#retrieving-data-using-get)\n - [Getting a document by id](#getting-a-document-by-id)\n - [Creating data using POST](#creating-data-using-post)\n - [Updating using PUT](#updating-using-put)\n - [Deleting a document using Delete](#deleting-a-document-using-delete)\n- [💻 Exercises: Day 29](#-exercises-day-29)\n\n## Day 29\n\n## Building API\n\n\nIn this section, we will cove a RESTful API that uses HTTP request methods to GET, PUT, POST and DELETE data.\n\nRESTful API is an application program interface (API) that uses HTTP requests to GET, PUT, POST and DELETE data. In the previous sections, we have learned about python, flask and mongoDB. We will use the knowledge we acquire to develop a RESTful API using python flask and mongoDB. Every application which has CRUD(Create, Read, Update, Delete) operation has an API to create data, to get data, to update data or to delete data from database.\n\nThe browser can handle only get request. Therefore, we have to have a tool which can help us to handle all request methods(GET, POST, PUT, DELETE).\n\nExamples of API\n\n- Countries API: https://restcountries.eu/rest/v2/all\n- Cats breed API: https://api.thecatapi.com/v1/breeds\n\n[Postman](https://www.getpostman.com/) is a very popular tool when it comes to API development. So, if you like to do this section you need to [download postman](https://www.getpostman.com/). An alternative of Postman is [Insomnia](https://insomnia.rest/download).\n\n\n\n### Structure of an API\n\nAn API end point is a URL which can help to retrieve, create, update or delete a resource. The structure looks like this:\nExample:\nhttps://api.twitter.com/1.1/lists/members.json\nReturns the members of the specified list. Private list members will only be shown if the authenticated user owns the specified list.\nThe name of the company name followed by version followed by the purpose of the API.\nThe methods:\nHTTP methods & URLs\n\nThe API uses the following HTTP methods for object manipulation:\n\n```sh\nGET Used for object retrieval\nPOST Used for object creation and object actions\nPUT Used for object update\nDELETE Used for object deletion\n```\n\nLet us build an API which collects information about 30DaysOfPython students. We will collect the name, country, city, date of birth, skills and bio.\n\nTo implement this API, we will use:\n\n- Postman\n- Python\n- Flask\n- MongoDB\n\n### Retrieving data using get\n\nIn this step, let us use dummy data and return it as a json. To return it as json, will use json module and Response module.\n\n```py\n# let's import the flask\n\nfrom flask import Flask, Response\nimport json\nimport os\n\napp = Flask(__name__)\n\n@app.route('/api/v1.0/students', methods = ['GET'])\ndef students ():\n student_list = [\n {\n 'name':'Asabeneh',\n 'country':'Finland',\n 'city':'Helsinki',\n 'skills':['HTML', 'CSS','JavaScript','Python']\n },\n {\n 'name':'David',\n 'country':'UK',\n 'city':'London',\n 'skills':['Python','MongoDB']\n },\n {\n 'name':'John',\n 'country':'Sweden',\n 'city':'Stockholm',\n 'skills':['Java','C#']\n }\n ]\n return Response(json.dumps(student_list), mimetype='application/json')\n\n\nif __name__ == '__main__':\n # for deployment\n # to make it work for both production and development\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\nWhen you request the http://localhost:5000/api/v1.0/students url on the browser you will get this:\n\n\n\nWhen you request the http://localhost:5000/api/v1.0/students url on the browser you will get this:\n\n\n\nIn stead of displaying dummy data let us connect the flask application with MongoDB and get data from mongoDB database.\n\n```py\n# let's import the flask\n\nfrom flask import Flask, Response\nimport json\nimport pymongo\nimport os\n\napp = Flask(__name__)\n\n#\nMONGODB_URI='mongodb+srv://asabeneh:your_password@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # accessing the database\n\n@app.route('/api/v1.0/students', methods = ['GET'])\ndef students ():\n\n return Response(json.dumps(student), mimetype='application/json')\n\n\nif __name__ == '__main__':\n # for deployment\n # to make it work for both production and development\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\nBy connecting the flask, we can fetch students collection data from the thirty_days_of_python database.\n\n```sh\n[\n {\n \"_id\": {\n \"$oid\": \"5df68a21f106fe2d315bbc8b\"\n },\n \"name\": \"Asabeneh\",\n \"country\": \"Finland\",\n \"city\": \"Helsinki\",\n \"age\": 38\n },\n {\n \"_id\": {\n \"$oid\": \"5df68a23f106fe2d315bbc8c\"\n },\n \"name\": \"David\",\n \"country\": \"UK\",\n \"city\": \"London\",\n \"age\": 34\n },\n {\n \"_id\": {\n \"$oid\": \"5df68a23f106fe2d315bbc8e\"\n },\n \"name\": \"Sami\",\n \"country\": \"Finland\",\n \"city\": \"Helsinki\",\n \"age\": 25\n }\n]\n```\n\n### Getting a document by id\n\nWe can access single document using an id, let's access Asabeneh using his id.\nhttp://localhost:5000/api/v1.0/students/5df68a21f106fe2d315bbc8b\n\n```py\n# let's import the flask\n\nfrom flask import Flask, Response\nimport json\nfrom bson.objectid import ObjectId\nimport json\nfrom bson.json_util import dumps\nimport pymongo\nimport os\n\napp = Flask(__name__)\n\n#\nMONGODB_URI='mongodb+srv://asabeneh:your_password@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # accessing the database\n\n@app.route('/api/v1.0/students', methods = ['GET'])\ndef students ():\n\n return Response(json.dumps(student), mimetype='application/json')\n@app.route('/api/v1.0/students/', methods = ['GET'])\ndef single_student (id):\n student = db.students.find({'_id':ObjectId(id)})\n return Response(dumps(student), mimetype='application/json')\n\nif __name__ == '__main__':\n # for deployment\n # to make it work for both production and development\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\n```sh\n[\n {\n \"_id\": {\n \"$oid\": \"5df68a21f106fe2d315bbc8b\"\n },\n \"name\": \"Asabeneh\",\n \"country\": \"Finland\",\n \"city\": \"Helsinki\",\n \"age\": 38\n }\n]\n```\n\n### Creating data using POST\n\nWe use the POST request method to create data\n\n```py\n# let's import the flask\n\nfrom flask import Flask, Response\nimport json\nfrom bson.objectid import ObjectId\nimport json\nfrom bson.json_util import dumps\nimport pymongo\nfrom datetime import datetime\nimport os\n\napp = Flask(__name__)\n\n#\nMONGODB_URI='mongodb+srv://asabeneh:your_password@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # accessing the database\n\n@app.route('/api/v1.0/students', methods = ['GET'])\ndef students ():\n\n return Response(json.dumps(student), mimetype='application/json')\n@app.route('/api/v1.0/students/', methods = ['GET'])\ndef single_student (id):\n student = db.students.find({'_id':ObjectId(id)})\n return Response(dumps(student), mimetype='application/json')\n@app.route('/api/v1.0/students', methods = ['POST'])\ndef create_student ():\n name = request.form['name']\n country = request.form['country']\n city = request.form['city']\n skills = request.form['skills'].split(', ')\n bio = request.form['bio']\n birthyear = request.form['birthyear']\n created_at = datetime.now()\n student = {\n 'name': name,\n 'country': country,\n 'city': city,\n 'birthyear': birthyear,\n 'skills': skills,\n 'bio': bio,\n 'created_at': created_at\n\n }\n db.students.insert_one(student)\n return ;\ndef update_student (id):\nif __name__ == '__main__':\n # for deployment\n # to make it work for both production and development\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\n### Updating using PUT\n\n```py\n# let's import the flask\n\nfrom flask import Flask, Response\nimport json\nfrom bson.objectid import ObjectId\nimport json\nfrom bson.json_util import dumps\nimport pymongo\nfrom datetime import datetime\nimport os\n\napp = Flask(__name__)\n\n#\nMONGODB_URI='mongodb+srv://asabeneh:your_password@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # accessing the database\n\n@app.route('/api/v1.0/students', methods = ['GET'])\ndef students ():\n\n return Response(json.dumps(student), mimetype='application/json')\n@app.route('/api/v1.0/students/', methods = ['GET'])\ndef single_student (id):\n student = db.students.find({'_id':ObjectId(id)})\n return Response(dumps(student), mimetype='application/json')\n@app.route('/api/v1.0/students', methods = ['POST'])\ndef create_student ():\n name = request.form['name']\n country = request.form['country']\n city = request.form['city']\n skills = request.form['skills'].split(', ')\n bio = request.form['bio']\n birthyear = request.form['birthyear']\n created_at = datetime.now()\n student = {\n 'name': name,\n 'country': country,\n 'city': city,\n 'birthyear': birthyear,\n 'skills': skills,\n 'bio': bio,\n 'created_at': created_at\n\n }\n db.students.insert_one(student)\n return\n@app.route('/api/v1.0/students/', methods = ['PUT']) # this decorator create the home route\ndef update_student (id):\n query = {\"_id\":ObjectId(id)}\n name = request.form['name']\n country = request.form['country']\n city = request.form['city']\n skills = request.form['skills'].split(', ')\n bio = request.form['bio']\n birthyear = request.form['birthyear']\n created_at = datetime.now()\n student = {\n 'name': name,\n 'country': country,\n 'city': city,\n 'birthyear': birthyear,\n 'skills': skills,\n 'bio': bio,\n 'created_at': created_at\n\n }\n db.students.update_one(query, student)\n # return Response(dumps({\"result\":\"a new student has been created\"}), mimetype='application/json')\n return\ndef update_student (id):\nif __name__ == '__main__':\n # for deployment\n # to make it work for both production and development\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\n### Deleting a document using Delete\n\n```py\n# let's import the flask\n\nfrom flask import Flask, Response\nimport json\nfrom bson.objectid import ObjectId\nimport json\nfrom bson.json_util import dumps\nimport pymongo\nfrom datetime import datetime\nimport os\n\napp = Flask(__name__)\n\n#\nMONGODB_URI='mongodb+srv://asabeneh:your_password@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # accessing the database\n\n@app.route('/api/v1.0/students', methods = ['GET'])\ndef students ():\n\n return Response(json.dumps(student), mimetype='application/json')\n@app.route('/api/v1.0/students/', methods = ['GET'])\ndef single_student (id):\n student = db.students.find({'_id':ObjectId(id)})\n return Response(dumps(student), mimetype='application/json')\n@app.route('/api/v1.0/students', methods = ['POST'])\ndef create_student ():\n name = request.form['name']\n country = request.form['country']\n city = request.form['city']\n skills = request.form['skills'].split(', ')\n bio = request.form['bio']\n birthyear = request.form['birthyear']\n created_at = datetime.now()\n student = {\n 'name': name,\n 'country': country,\n 'city': city,\n 'birthyear': birthyear,\n 'skills': skills,\n 'bio': bio,\n 'created_at': created_at\n\n }\n db.students.insert_one(student)\n return\n@app.route('/api/v1.0/students/', methods = ['PUT']) # this decorator create the home route\ndef update_student (id):\n query = {\"_id\":ObjectId(id)}\n name = request.form['name']\n country = request.form['country']\n city = request.form['city']\n skills = request.form['skills'].split(', ')\n bio = request.form['bio']\n birthyear = request.form['birthyear']\n created_at = datetime.now()\n student = {\n 'name': name,\n 'country': country,\n 'city': city,\n 'birthyear': birthyear,\n 'skills': skills,\n 'bio': bio,\n 'created_at': created_at\n\n }\n db.students.update_one(query, student)\n # return Response(dumps({\"result\":\"a new student has been created\"}), mimetype='application/json')\n return\n@app.route('/api/v1.0/students/', methods = ['PUT']) # this decorator create the home route\ndef update_student (id):\n query = {\"_id\":ObjectId(id)}\n name = request.form['name']\n country = request.form['country']\n city = request.form['city']\n skills = request.form['skills'].split(', ')\n bio = request.form['bio']\n birthyear = request.form['birthyear']\n created_at = datetime.now()\n student = {\n 'name': name,\n 'country': country,\n 'city': city,\n 'birthyear': birthyear,\n 'skills': skills,\n 'bio': bio,\n 'created_at': created_at\n\n }\n db.students.update_one(query, student)\n # return Response(dumps({\"result\":\"a new student has been created\"}), mimetype='application/json')\n return ;\n@app.route('/api/v1.0/students/', methods = ['DELETE'])\ndef delete_student (id):\n db.students.delete_one({\"_id\":ObjectId(id)})\n return\nif __name__ == '__main__':\n # for deployment\n # to make it work for both production and development\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\n## 💻 Exercises: Day 29\n\n1. Implement the above example and develop [this](https://thirtydayofpython-api.herokuapp.com/)\n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 28](../28_Day_API/28_API.md) | [Day 30 >>](../30_Day_Conclusions/30_conclusions.md)\n"
},
{
"path": "30_Day_Conclusions/30_conclusions.md",
"content": "
\n\n[<< Day 29](../29_Day_Building_API/29_building_API.md)\n\n\n- [Day 30](#day-30)\n - [Conclusions](#conclusions)\n - [Testimony](#testimony)\n\n# Day 30\n\n\n## Conclusions\n\nIn the process of preparing this material I have learned quite a lot and you have inspired me to do more. Congratulations for making it to this level. If you have done all the exercise and the projects, now you are capable to go to a data analysis, data science, machine learning or web development paths. [Support the author for more educational materials](https://www.paypal.com/paypalme/asabeneh).\n\n## Testimony\nNow it is time to express your thoughts about the Author and 30DaysOfPython. You can leave your testimonial on this [link](https://www.asabeneh.com/testimonials)\n\nGIVE FEEDBACK:\nhttp://thirtydayofpython-api.herokuapp.com/feedback\n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 29](../29_Day_Building_API/29_building_API.md)\n"
},
{
"path": "Chinese/02_variables_builtin_functions.md",
"content": "
\n\n\n[<< 第 14 天](../14_Day_Higher_order_functions/14_higher_order_functions.md) | [第 16 天 >>](../16_Day_Python_date_time/16_python_datetime.md)\n\n\n\n- [📘 第 15 天](#-第15天)\n - [Python 错误类型](#python错误类型)\n - [SyntaxError](#syntaxerror)\n - [NameError](#nameerror)\n - [IndexError](#indexerror)\n - [ModuleNotFoundError](#modulenotfounderror)\n - [AttributeError](#attributeerror)\n - [KeyError](#keyerror)\n - [TypeError](#typeerror)\n - [ImportError](#importerror)\n - [ValueError](#valueerror)\n - [ZeroDivisionError](#zerodivisionerror)\n - [💻 练习: 第 15 天](#练习-第15天)\n\n# 📘 第 15 天\n\n## Python 错误类型\n\n当我们编写代码时，很常见会打错字或出现其他一些常见错误。如果我们的代码不能运行，Python 解释器会显示一条信息，包含关于问题发生在哪里以及错误类型的反馈信息。它有时还会给我们提供可能的修复建议。理解编程语言中的不同类型的错误将有助于我们快速调试代码，同时也会使我们在工作中变得更优秀。\n\n让我们逐个来看最常见的错误类型。首先让我们打开 Python 交互式 Shell。打开电脑终端，输入‘python’，将会打开 Python 交互式 Shell。\n\n### SyntaxError\n\n**示例 1: SyntaxError**\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> print 'hello world'\n File \"\", line 1\n print 'hello world'\n ^\nSyntaxError: Missing parentheses in call to 'print'. Did you mean print('hello world')?\n>>>\n```\n\n如你所见，我们犯了一个语法错误，因为我们忘了用括号包裹字符串，Python 已经建议了解决办法。让我们修复它。\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> print 'hello world'\n File \"\", line 1\n print 'hello world'\n ^\nSyntaxError: Missing parentheses in call to 'print'. Did you mean print('hello world')?\n>>> print('hello world')\nhello world\n>>>\n```\n\n错误类型是*SyntaxError*。修复之后我们的代码顺利执行了。让我们看看更多的错误类型。\n\n### NameError\n\n**示例 1: NameError**\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> print(age)\nTraceback (most recent call last):\n File \"\", line 1, in \nNameError: name 'age' is not defined\n>>>\n```\n\n如你所见，消息显示年龄变量未定义。确实，我们没有定义年龄变量，但我们试图打印它。现在，让我们通过定义并赋值它来修复它。\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> print(age)\nTraceback (most recent call last):\n File \"\", line 1, in \nNameError: name 'age' is not defined\n>>> age = 25\n>>> print(age)\n25\n>>>\n```\n\n错误类型是*NameError*。我们通过定义变量名调试了错误。\n\n### IndexError\n\n**示例 1: IndexError**\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> numbers = [1, 2, 3, 4, 5]\n>>> numbers[5]\nTraceback (most recent call last):\n File \"\", line 1, in \nIndexError: list index out of range\n>>>\n```\n\n在上面的例子中，Python 引发了 IndexError，因为列表只有 0 到 4 的索引，因此超出了范围。\n\n### ModuleNotFoundError\n\n**示例 1: ModuleNotFoundError**\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> import maths\nTraceback (most recent call last):\n File \"\", line 1, in \nModuleNotFoundError: No module named 'maths'\n>>>\n```\n\n在上面的例子中，我故意在 math 后面多加了一个 s，所以引发了*ModuleNotFoundError*。让我们通过去掉多余的 s 来修复它。\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> import maths\nTraceback (most recent call last):\n File \"\", line 1, in \nModuleNotFoundError: No module named 'maths'\n>>> import math\n>>>\n```\n\n我们修复了它，让我们使用 math 模块中的一些函数。\n\n### AttributeError\n\n**示例 1: AttributeError**\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> import maths\nTraceback (最\n澘會末呼つはゃす尽ﾙル귀행세뿌府ぐ\n<|vq_10375|> File \"\", line 1, in \nModuleNotFoundError: No module named 'maths'\n>>> import math\n>>> math.PI\nTraceback (most recent call last):\n File \"\", line 1, in \nAttributeError: module 'math' has no attribute 'PI'\n>>>\n```\n\n如你所见，我又犯了一个错误！我试图从 math 模块调用 PI 函数，但实际上它是 pi。它引发了属性错误，意味着该函数在模块中不存在。让我们通过将 PI 改为 pi 来修复它。\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> import maths\nTraceback (most recent call last):\n File \"\", line 1, in \nModuleNotFoundError: No module named 'maths'\n>>> import math\n>>> math.PI\nTraceback (most recent call last):\n File \"\", line 1, in \nAttributeError: module 'math' has no attribute 'PI'\n>>> math.pi\n3.141592653589793\n>>>\n```\n\n现在，当我们从 math 模块调用 pi 时得到了结果。\n\n### KeyError\n\n**示例 1: KeyError**\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> users = {'name':'Asab', 'age':250, 'country':'Finland'}\n>>> users['name']\n'Asab'\n>>> users['county']\nTraceback (most recent call last):\n File \"\", line 1, in \nKeyError: 'county'\n>>>\n```\n\n如你所见，用于获取字典值的键存在拼写错误。这是一个 key error，修复非常简单。让我们做一下！\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> user = {'name':'Asab', 'age':250, 'country':'Finland'}\n>>> user['name']\n'Asab'\n>>> user['county']\nTraceback (most recent call last):\n File \"\", line 1, in \nKeyError: 'county'\n>>> user['country']\n'Finland'\n>>>\n```\n\n我们调试了错误，代码运行并获取了值。\n\n### TypeError\n\n**示例 1: TypeError**\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> 4 + '3'\nTraceback (most recent call last):\n File \"\", line 1, in \nTypeError: unsupported operand type(s) for +: 'int' and 'str'\n>>>\n```\n\n在上面的例子中，引发了 TypeError，因为我们不能将数字和字符串相加。第一个解决方法是将字符串转换为 int 或 float。另一种解决方法是将数字转换为字符串（结果将是'43'）。让我们跟随第一种解决方案。\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> 4 + '3'\nTraceback (most recent call last):\n File \"\", line 1, in \nTypeError: unsupported operand type(s) for +: 'int' and 'str'\n>>> 4 + int('3')\n7\n>>> 4 + float('3')\n7.0\n>>>\n```\n\n错误消除，我们得到了期望的结果。\n\n### ImportError\n\n**示例 1: TypeError**\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> from math import power\nTraceback (most recent call last):\n File \"\", line 1, in \nImportError: cannot import name 'power' from 'math'\n>>>\n```\n\n数学模块中没有函数叫做 power，它是以另一个名字存在: _pow_。让我们纠正它：\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> from math import power\nTraceback (most recent call last):\n File \"\", line 1, in \nImportError: cannot import name 'power' from 'math'\n>>> from math import pow\n>>> pow(2,3)\n8.0\n>>>\n```\n\n### ValueError\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> int('12a')\nTraceback (most recent call last):\n File \"\", line 1, in \nValueError: invalid literal for int() with base 10: '12a'\n>>>\n```\n\n在这种情况下，我们无法将给定字符串更改为数字，因为它包含了'a'字母。\n\n### ZeroDivisionError\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> 1/0\nTraceback (most recent call last):\n File \"\", line 1, in \nZeroDivisionError: division by zero\n>>>\n```\n\n我们不能将一个数除以零。\n\n我们已经涵盖了一些 Python 错误类型，如果你想了解更多，请查看 Python 文档中的 Python 错误类型。\n如果你能够很好地阅读错误类型，你将能够快速修复你的 bug，并且你也会成为一个更优秀的程序员。\n\n🌕 你正在不断进步。你已经走到了通往卓越的半程。现在来一些锻炼大脑和肌肉的练习吧。\n\n## 💻 练习: 第 15 天\n\n1. 打开你 Python 的交互式 Shell，尝试本节中涵盖的所有示例。\n\n🎉 恭喜！ 🎉\n\n[<< 第 14 天](../14_Day_Higher_order_functions/14_higher_order_functions.md) | [第 16 天 >>](../16_Day_Python_date_time/16_python_datetime.md)\n"
},
{
"path": "Chinese/15_python_type_errors_cn.md",
"content": "# 30天Python编程挑战：第15天 - Python类型错误\n\n- [Day 15](#day-15)\n - [Python错误类型](#python错误类型)\n - [SyntaxError (语法错误)](#syntaxerror-语法错误)\n - [NameError (名称错误)](#nameerror-名称错误)\n - [IndexError (索引错误)](#indexerror-索引错误)\n - [ModuleNotFoundError (模块未找到错误)](#modulenotfounderror-模块未找到错误)\n - [AttributeError (属性错误)](#attributeerror-属性错误)\n - [KeyError (键错误)](#keyerror-键错误)\n - [TypeError (类型错误)](#typeerror-类型错误)\n - [ImportError (导入错误)](#importerror-导入错误)\n - [ValueError (值错误)](#valueerror-值错误)\n - [ZeroDivisionError (零除错误)](#zerodivisionerror-零除错误)\n - [💻 练习 - 第15天](#-练习---第15天)\n\n# 📘 Day 15\n\n## Python错误类型\n\n当我们编写代码时，常常会出现打字错误或其他常见错误。如果我们的代码运行失败，Python解释器会显示一条消息，提供有关问题发生位置和错误类型的反馈信息。有时它还会给我们提供可能的修复建议。了解编程语言中不同类型的错误将帮助我们快速调试代码，并使我们在编程技能上有所提高。\n\n让我们一一查看最常见的错误类型。首先，让我们打开Python交互式shell。转到你的计算机终端并输入'python'。Python交互式shell将会被打开。\n\n### SyntaxError (语法错误)\n\n**示例1: SyntaxError**\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> print 'hello world'\n File \"\", line 1\n print 'hello world'\n ^\nSyntaxError: Missing parentheses in call to 'print'. Did you mean print('hello world')?\n>>>\n```\n\n如你所见，我们犯了一个语法错误，因为我们忘记用括号括起字符串，而Python已经提出了解决方案。让我们修复它。\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> print 'hello world'\n File \"\", line 1\n print 'hello world'\n ^\nSyntaxError: Missing parentheses in call to 'print'. Did you mean print('hello world')?\n>>> print('hello world')\nhello world\n>>>\n```\n\n错误是一个_SyntaxError_。修复后，我们的代码顺利执行。让我们看看更多的错误类型。\n\n### NameError (名称错误)\n\n**示例1: NameError**\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> print(age)\nTraceback (most recent call last):\n File \"\", line 1, in \nNameError: name 'age' is not defined\n>>>\n```\n\n从上面的消息可以看出，名称age没有被定义。是的，确实如此，我们没有定义age变量，但我们试图像已经声明了一样打印它。现在，让我们通过声明变量并为其赋值来修复这个问题。\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> print(age)\nTraceback (most recent call last):\n File \"\", line 1, in \nNameError: name 'age' is not defined\n>>> age = 25\n>>> print(age)\n25\n>>>\n```\n\n错误类型是_NameError_。我们通过定义变量名来调试了错误。\n\n### IndexError (索引错误)\n\n**示例1: IndexError**\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> numbers = [1, 2, 3, 4, 5]\n>>> numbers[5]\nTraceback (most recent call last):\n File \"\", line 1, in \nIndexError: list index out of range\n>>>\n```\n\n在上面的例子中，Python抛出了一个_IndexError_，因为列表的索引只有0到4，所以索引5超出了范围。\n\n### ModuleNotFoundError (模块未找到错误)\n\n**示例1: ModuleNotFoundError**\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> import maths\nTraceback (most recent call last):\n File \"\", line 1, in \nModuleNotFoundError: No module named 'maths'\n>>>\n```\n\n在上面的例子中，我故意在math后面添加了一个多余的s，结果抛出了_ModuleNotFoundError_。让我们通过从math中删除多余的s来修复它。\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> import maths\nTraceback (most recent call last):\n File \"\", line 1, in \nModuleNotFoundError: No module named 'maths'\n>>> import math\n>>>\n```\n\n我们修复了它，所以让我们使用math模块中的一些函数。\n\n### AttributeError (属性错误)\n\n**示例1: AttributeError**\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> import maths\nTraceback (most recent call last):\n File \"\", line 1, in \nModuleNotFoundError: No module named 'maths'\n>>> import math\n>>> math.PI\nTraceback (most recent call last):\n File \"\", line 1, in \nAttributeError: module 'math' has no attribute 'PI'\n>>>\n```\n\n如你所见，我又犯了一个错误！我试图从math模块调用PI函数，而不是pi。这抛出了一个属性错误，表示该函数在模块中不存在。让我们通过将PI更改为pi来修复它。\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> import maths\nTraceback (most recent call last):\n File \"\", line 1, in \nModuleNotFoundError: No module named 'maths'\n>>> import math\n>>> math.PI\nTraceback (most recent call last):\n File \"\", line 1, in \nAttributeError: module 'math' has no attribute 'PI'\n>>> math.pi\n3.141592653589793\n>>>\n```\n\n现在，当我们从math模块调用pi时，我们得到了结果。\n\n### KeyError (键错误)\n\n**示例1: KeyError**\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> users = {'name':'Asab', 'age':250, 'country':'Finland'}\n>>> users['name']\n'Asab'\n>>> users['county']\nTraceback (most recent call last):\n File \"\", line 1, in \nKeyError: 'county'\n>>>\n```\n\n如你所见，在用于获取字典值的键中有一个拼写错误。这是一个键错误，修复方法很简单。让我们来做这个！\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> user = {'name':'Asab', 'age':250, 'country':'Finland'}\n>>> user['name']\n'Asab'\n>>> user['county']\nTraceback (most recent call last):\n File \"\", line 1, in \nKeyError: 'county'\n>>> user['country']\n'Finland'\n>>>\n```\n\n我们调试了错误，我们的代码运行并得到了结果。\n\n### TypeError (类型错误)\n\n**示例1: TypeError**\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> 4 + '3'\nTraceback (most recent call last):\n File \"\", line 1, in \nTypeError: unsupported operand type(s) for +: 'int' and 'str'\n>>>\n```\n\n在上面的例子中，出现了TypeError，因为我们不能将数字与字符串相加。第一个解决方案是将字符串转换为int或float。另一个解决方案是将数字转换为字符串（那么结果将是'43'）。让我们采用第一种修复方式。\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> 4 + '3'\nTraceback (most recent call last):\n File \"\", line 1, in \nTypeError: unsupported operand type(s) for +: 'int' and 'str'\n>>> 4 + int('3')\n7\n>>> 4 + float('3')\n7.0\n>>>\n```\n\n错误已消除，我们得到了预期的结果。\n\n### ImportError (导入错误)\n\n**示例1: ImportError**\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> from math import power\nTraceback (most recent call last):\n File \"\", line 1, in \nImportError: cannot import name 'power' from 'math'\n>>>\n```\n\nmath模块中没有名为power的函数，它的名字是不同的：_pow_。让我们纠正它：\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> from math import power\nTraceback (most recent call last):\n File \"\", line 1, in \nImportError: cannot import name 'power' from 'math'\n>>> from math import pow\n>>> pow(2,3)\n8.0\n>>>\n```\n\n### ValueError (值错误)\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> int('12a')\nTraceback (most recent call last):\n File \"\", line 1, in \nValueError: invalid literal for int() with base 10: '12a'\n>>>\n```\n\n在这种情况下，我们无法将给定的字符串转换为数字，因为其中有字母'a'。\n\n### ZeroDivisionError (零除错误)\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> 1/0\nTraceback (most recent call last):\n File \"\", line 1, in \nZeroDivisionError: division by zero\n>>>\n```\n\n我们不能用零去除一个数字。\n\n我们已经介绍了一些Python错误类型，如果你想了解更多，请查看Python文档中关于Python错误类型的内容。\n如果你擅长阅读错误类型，那么你将能够快速修复你的bug，你也将成为一个更好的程序员。\n\n🌕 你正在进步。你已经完成了一半的道路，正走向伟大。现在做一些练习来锻炼你的大脑和肌肉。\n\n## 💻 练习 - 第15天\n\n1. 打开你的Python交互式shell，尝试本节中介绍的所有示例。\n\n🎉 恭喜！🎉\n\n[<< 第 14 天](./14_higher_order_functions.md) | [第 16 天 >>](./16_python_datetime_cn.md) "
},
{
"path": "Chinese/16_python_datetime.md",
"content": "
\n\n[<< Day 1](../readme.md) | [Day 3 >>](../03_Day_Operators/03_operators.md)\n\n\n\n- [📘 Day 2](#-day-2)\n - [내장 함수](#내장-함수)\n - [변수](#변수)\n - [한 줄로 여러개의 변수 선언](#한-줄로-여러개의-변수-선언)\n - [자료형](#자료형)\n - [자료형 확인 및 형변환](#자료형-확인-및-형변환)\n - [숫자](#숫자)\n - [💻 Exercises - Day 2](#-exercises---day-2)\n - [Exercises: Level 1](#exercises-level-1)\n - [Exercises: Level 2](#exercises-level-2)\n\n# 📘 Day 2\n\n## 내장 함수\n\n파이썬에는 수많은 내장 함수가 있습니다. 내장 함수는 전역에서 사용 가능하고 그건 importing 이나 configuring없이 내장 함수를 사용 가능하다는 뜻입니다. 다음은 가장 자주 사용되는 파이썬 내장함수들 중 몇가지입니다: _print()_, _len()_, _type()_, _int()_, _float()_, _str()_, _input()_, _list()_, _dict()_, _min()_, _max()_, _sum()_, _sorted()_, _open()_, _file()_, _help()_, and _dir()_. 밑의 표에서 [파이썬 공식문서](https://docs.python.org/3.9/library/functions.html) 에 쓰여진 파이썬 내장 함수의 전체 목록을 볼 수 있습니다.\n\n\n\n파이썬 쉘을 열고 가장 자주 사용되는 내장 함수를 사용해봅시다.\n\n\n\n다른 내장 함수를 사용해 더 연습해봅시다.\n\n\n\n위의 터미널에서 볼 수 있듯이, 파이썬에는 reserved word가 있습니다. reserved word는 변수나 함수를 선언할때 사용되지 않습니다. 변수에 관해서는 다음 장에서 다룰것입니다.\n\n이제 당신은 내장 함수에 익숙해졌을 것이라 믿습니다. 한번 더 내장 함수의 연습을 하고 다음 장으로 넘어갑시다.\n\n\n## 변수\n\n변수는 컴퓨터 메모리에 정보를 저장합니다. Mnemonic 변수는 많은 프로그래밍 언어에서 사용하도록 권장됩니다. Mnemonic 변수는 쉽게 기억하고 연관지을 수 있는 변수 이름입니다. 한 변수는 정보가 저장되어있는 메모리 주소를 참조합니다.\n변수 이름을 지정할 때는 시작 부분의 숫자, 특수 문자, 하이픈을 사용할 수 없습니다. 변수는 짧은 이름(예: x, y, z)을 가질 수 있지만 더 변수에 대한 설명을 담은 이름(이름, 성, 나이, 국가)을 사용하는 것을 추천합니다.\n\n파이썬 변수 이름 규칙\n\n- 변수 이름은 문자 또는 밑줄 문자로 시작해야 합니다\n- 변수 이름은 숫자로 시작할 수 없습니다 \n- 변수 이름에는 알파벳과 숫자와 밑줄(A-z, 0-9 및 \\_)만 사용할 수 있습니다 \n- 변수 이름은 대소문자를 구분합니다(firstname, Firstname, FirstName, FIRSTNAME은 서로 다른 변수)\n\n사용가능한 변수 이름들을 살펴봅시다\n\n```shell\nfirstname\nlastname\nage\ncountry\ncity\nfirst_name\nlast_name\ncapital_city\n_if # reserved word를 변수 이름으로 사용하고 싶은 경우\nyear_2021\nyear2021\ncurrent_year_2021\nbirth_year\nnum1\nnum2\n```\n\n사용할 수 없는 변수 이름들\n\n```shell\nfirst-name\nfirst@name\nfirst$name\nnum-1\n1num\n```\n\n우리는 많은 파이썬 개발자들이 채택한 표준 파이썬 변수 명명 방식을 사용할 것입니다. 파이썬 개발자들은 스네이크 케이스(snake_case) 변수 명명 규칙을 사용합니다. 우리는 두 개 이상의 단어를 포함하는 변수에 대해 각 단어 뒤에 밑줄 문자를 사용합니다(예: first_name, last_name, engine_rotation_speed). 아래 예제는 변수의 표준 명명 예제이며, 변수 이름이 둘 이상의 단어일 경우 밑줄이 필요합니다.\n\n변수에 특정 데이터 유형을 할당할 때 이를 변수 선언이라고 합니다. 예를 들어 아래 예제에서 내 이름은 first_name 변수에 할당됩니다. 등호 기호는 할당 연산자입니다. 할당은 변수에 데이터를 저장하는 것을 의미합니다. 파이썬에서 등호 기호는 수학에서의 등호가 아닙니다.\n\n_Example:_\n\n```py\n# Variables in Python\nfirst_name = 'Asabeneh'\nlast_name = 'Yetayeh'\ncountry = 'Finland'\ncity = 'Helsinki'\nage = 250\nis_married = True\nskills = ['HTML', 'CSS', 'JS', 'React', 'Python']\nperson_info = {\n 'firstname':'Asabeneh',\n 'lastname':'Yetayeh',\n 'country':'Finland',\n 'city':'Helsinki'\n }\n```\n\n내장 함수인 _print()_ 와 _len()_ 을 사용해봅시다. Print 함수는 인자의 수에 제한이 없습니다. 인자는 함수 괄호 안에 넣어 전달할 수 있는 값입니다. 아래 예제를 봅시다.\n\n**Example:**\n\n```py\nprint('Hello, World!') # Hello, World! 라는 글이 하나의 인자입니다\nprint('Hello',',', 'World','!') # 여러개의 인자를 받을 수 있습니다, 네개의 인자가 넘겨졌습니다 \nprint(len('Hello, World!')) # 하나의 인자만을 받습니다\n```\n\n위에서 정의된 변수들을 찍어보고 길이를 찾아봅시다:\n\n**Example:**\n\n```py\n# 변수에 저장된 값 찍기\n\nprint('First name:', first_name)\nprint('First name length:', len(first_name))\nprint('Last name: ', last_name)\nprint('Last name length: ', len(last_name))\nprint('Country: ', country)\nprint('City: ', city)\nprint('Age: ', age)\nprint('Married: ', is_married)\nprint('Skills: ', skills)\nprint('Person information: ', person_info)\n```\n\n### 한 줄로 여러개의 변수 선언\n\n하나의 줄에서 여러개의 변수를 선언할 수도 있습니다:\n\n**Example:**\n\n```py\nfirst_name, last_name, country, age, is_married = 'Asabeneh', 'Yetayeh', 'Helsink', 250, True\n\nprint(first_name, last_name, country, age, is_married)\nprint('First name:', first_name)\nprint('Last name: ', last_name)\nprint('Country: ', country)\nprint('Age: ', age)\nprint('Married: ', is_married)\n```\n\n내장 함수 _input()_ 을 사용해 사용자의 입력 받기. 사용자로부터 받은 정보를 first_name과 age 변수에 할당해봅시다.\n**Example:**\n\n```py\nfirst_name = input('What is your name: ')\nage = input('How old are you? ')\n\nprint(first_name)\nprint(age)\n```\n\n## 자료형\n\n파이썬에는 몇 가지 자료형이 있습니다. 자료형을 식별하기 위해 내장 함수 _type()_ 을 사용합니다. 서로 다른 자료형을 잘 이해하는 데 집중해 주시기를 부탁드립니다. 프로그래밍에서 모든것은 자료형과 관련이 있습니다. 처음에 자료형을 소개했지만 모든 주제가 자료형과 관련이 있기 때문에 다시 나옵니다. 자료형에 대해서는 각 섹션에서 자세히 설명하겠습니다.\n\n## 자료형 확인 및 형변환\n\n- 자료형 확인: 특정 정보/변수의 자료형을 확인하기위해 우리는 _type()_ 을 사용합니다\n **Example:**\n\n```py\n# 다양한 파이썬 자료형\n# 다양한 자료형의 변수들을 선언해 봅시다.\n\nfirst_name = 'Asabeneh' # str\nlast_name = 'Yetayeh' # str\ncountry = 'Finland' # str\ncity= 'Helsinki' # str\nage = 250 # int, 제 실제 나이가 아닙니다, 걱정마세요\n\n# Printing out types\nprint(type('Asabeneh')) # str\nprint(type(first_name)) # str\nprint(type(10)) # int\nprint(type(3.14)) # float\nprint(type(1 + 1j)) # complex\nprint(type(True)) # bool\nprint(type([1, 2, 3, 4])) # list\nprint(type({'name':'Asabeneh','age':250, 'is_married':250})) # dict\nprint(type((1,2))) # tuple\nprint(type(zip([1,2],[3,4]))) # set\n```\n\n- 형변환: 하나의 자료형을 다른 자료형으로 변환합니다. _int()_, _float()_, _str()_, _list_, _set_ 를 사용합니다.\n 산술 연산을 수행할 때 문자열 숫자들을 먼저 int 나 float로 변환해야 합니다. 그렇지 않으면 오류가 반환됩니다. 만약 숫자를 문자열과 결합한다면, 그 숫자는 먼저 문자열로 변환되어야 합니다. 결합에 대해서는 String 섹션에서 설명하겠습니다.\n\n **Example:**\n\n```py\n# int to float\nnum_int = 10\nprint('num_int',num_int) # 10\nnum_float = float(num_int)\nprint('num_float:', num_float) # 10.0\n\n# float to int\ngravity = 9.81\nprint(int(gravity)) # 9\n\n# int to str\nnum_int = 10\nprint(num_int) # 10\nnum_str = str(num_int)\nprint(num_str) # '10'\n\n# str to int or float\nnum_str = '10.6'\nprint('num_int', int(num_str)) # 10\nprint('num_float', float(num_str)) # 10.6\n\n# str to list\nfirst_name = 'Asabeneh'\nprint(first_name) # 'Asabeneh'\nfirst_name_to_list = list(first_name)\nprint(first_name_to_list) # ['A', 's', 'a', 'b', 'e', 'n', 'e', 'h']\n```\n\n## 숫자\n\n파이썬의 숫자 자료형:\n\n1. Integers: 정수(음수, 0 , 양수) \n 예:\n ... -3, -2, -1, 0, 1, 2, 3 ...\n\n2. 부동 소수점 숫자(10진수)\n 예:\n ... -3.5, -2.25, -1.0, 0.0, 1.1, 2.2, 3.5 ...\n\n3. 복소수\n 예:\n 1 + j, 2 + 4j, 1 - 1j\n\n🌕 당신은 정말 멋집니다. 여러분은 이제 막 2일차 도전을 마쳤고 위대함으로 가는 길에 두 걸음 앞서 있습니다. 이제 여러분의 뇌와 근육을 위한 운동을 하세요.\n\n## 💻 Exercises - Day 2\n\n### Exercises: Level 1\n\n1. 30DaysOfPython 내에 day_2라는 폴더를 생성하세요. 그 폴더 내에 variables.py 라는 파일을 생성하세요.\n2. 'Day 2: 30 Days of python programming'이라는 파이썬 주석을 작성합니다.\n3. first name 변수를 선언하고 변수에 값을 할당합니다.\n4. last name 변수를 선언하고 변수에 값을 할당합니다.\n5. full name 변수를 선언하고 변수에 값을 할당합니다.\n6. country 변수를 선언하고 값을 할당합니다.\n7. city 변수를 선언하고 값을 할당합니다.\n8. age 변수를 선언하고 값을 할당합니다.\n9. year 변수를 선언하고 값을 할당합니다.\n10. is_married 변수를 선언하고 값을 할당합니다.\n11. is_true 변수를 선언하고 값을 할당합니다.\n12. is_light_on 변수를 선언하고 값을 할당합니다.\n13. 한 줄에 여러개의 변수를 선언합니다.\n\n### Exercises: Level 2\n\n1. Check the data type of all your variables using type() built-in function\n1. Using the _len()_ built-in function, find the length of your first name\n1. Compare the length of your first name and your last name\n1. Declare 5 as num_one and 4 as num_two\n 1. Add num_one and num_two and assign the value to a variable total\n 2. Subtract num_two from num_one and assign the value to a variable diff\n 3. Multiply num_two and num_one and assign the value to a variable product\n 4. Divide num_one by num_two and assign the value to a variable division\n 5. Use modulus division to find num_two divided by num_one and assign the value to a variable remainder\n 6. Calculate num_one to the power of num_two and assign the value to a variable exp\n 7. Find floor division of num_one by num_two and assign the value to a variable floor_division\n1. The radius of a circle is 30 meters.\n 1. Calculate the area of a circle and assign the value to a variable name of _area_of_circle_\n 2. Calculate the circumference of a circle and assign the value to a variable name of _circum_of_circle_\n 3. Take radius as user input and calculate the area.\n1. Use the built-in input function to get first name, last name, country and age from a user and store the value to their corresponding variable names\n1. Run help('keywords') in Python shell or in your file to check for the Python reserved words or keywords\n\n1. type() 내장 함수를 사용하여 모든 변수의 자료형을 확인합니다.\n1. _len()_ 내장 함수를 사용하여 당신의 first name 의 길이를 찾습니다.\n1. 당신의 first name 과 last name 의 길이를 비교합니다.\n1. 5를 num_1로, 4를 num_2로 선언합니다.\n 1. num_one과 num_two를 더하고 그 값을 변수 total 에 할당합니다.\n 2. num_1에서 num_2를 빼고 그 값을 변수 diff 에 할당합니다.\n 3. num_two와 num_one을 곱하여 그 값을 변수 product 에 할당합니다.\n 4. num_one을 num_two로 나누고 그 값을 변수 division 에 할당합니다.\n 5. 나머지 연산을 사용하여 num_two를 num_one으로 나눈 값을 찾고 변수 remainder 에 할당합니다.\n 6. num_one을 num_two의 거듭제곱으로 계산하고 그 값을 변수 exp 에 할당합니다.\n 7. num_one을 num_two로 나누고 소숫값은 버린 정수 값을 구하고 변수 floor_division 에 값을 할당합니다.\n1. 원의 반지름은 30미터입니다.\n 1. 원의 면적을 계산하여 _area_of_circle_ 이라는 이름의 변수에 값을 할당합니다.\n 2. 원의 둘레를 계산하여 _circum_of_circum_ 이라는 이름의 변수에 값을 할당합니다.\n 3. 반경을 사용자 입력으로 받아서 면적을 계산합니다.\n1. 내장 함수 input을 사용하여 사용자로부터 이름, 성, 국가 및 나이를 얻고 해당 변수 이름에 값을 저장합니다.\n1. Python 셸 또는 파일에서 help('keywords')을 실행하여 파이썬의 reserved words 또는 키워드를 확인합니다.\n\n🎉 축하합니다 ! 🎉\n\n[<< Day 1](../readme.md) | [Day 3 >>](../03_Day_Operators/03_operators.md)\n"
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"path": "Korean/04_strings_ko.md",
"content": "
\n\n\n[<< Day 3](../03_Day_Operators/03_operators.md) | [Day 5 >>](../05_Day_Lists/05_lists.md)\n\n\n\n- [Day 4](#day-4)\n - [문자열](#strings)\n - [문자열 만들기](#문자열-만들기)\n - [문자열 연결](#문자열-연결)\n - [문자열의 이스케이프 시퀀스](#문자열의-이스케이프-시퀀스)\n - [문자열 포매팅](#문자열-포매팅)\n - [올드 스타일 문자열 포매팅(% 연산자)](#올드-스타일-문자열-포매팅%-연산자)\n - [새로운 스타일 문자열 포매팅(str.format)](#새로운-스타일-문자열-포매팅str.format)\n - [문자열 Interpolation / f-Strings (Python 3.6+)](#string-interpolation--f-strings-python-36)\n - [문자 시퀀스로서의 Python 문자열](#문자-시퀀스로서의-Python-문자열)\n - [언패킹 문자](#언패킹-문자)\n - [인덱스로 문자열의 문자에 액세스](#인덱스로-문자열의-문자에-액세스)\n - [파이썬 문자열 슬라이싱](#파이썬-문자열-슬라이싱)\n - [문자열 리버스](#문자열-리버스)\n - [슬라이싱하는 동안 문자 건너뛰기](#슬라이싱하는-동안-문자-건너뛰기)\n - [문자열 메서드](#문자열-메서드)\n - [💻 Exercises - Day 4](#-exercises---day-4)\n\n# Day 4\n\n## 문자열\n\n텍스트는 문자열 데이터 유형입니다. 텍스트로 작성된 모든 데이터 유형은 문자열입니다. 작은따옴표, 큰따옴표 또는 삼중따옴표 아래의 모든 데이터는 문자열입니다. 문자열 데이터 유형을 처리하기 위한 다양한 문자열 메서드와 내장 함수가 있습니다. 문자열의 길이를 확인하려면 len() 메서드를 사용하십시오.\n\n### 문자열 만들기\n\n```py\nletter = 'P' # A string could be a single character or a bunch of texts\nprint(letter) # P\nprint(len(letter)) # 1\ngreeting = 'Hello, World!' # String could be made using a single or double quote,\"Hello, World!\"\nprint(greeting) # Hello, World!\nprint(len(greeting)) # 13\nsentence = \"I hope you are enjoying 30 days of Python Challenge\"\nprint(sentence)\n```\n\n여러 줄 문자열은 세 개의 작은따옴표(''') 또는 세 개의 큰따옴표(\"\"\")를 사용하여 생성됩니다. 아래 예를 참조하십시오.\n\n```py\nmultiline_string = '''I am a teacher and enjoy teaching.\nI didn't find anything as rewarding as empowering people.\nThat is why I created 30 days of python.'''\nprint(multiline_string)\n\n# Another way of doing the same thing\nmultiline_string = \"\"\"I am a teacher and enjoy teaching.\nI didn't find anything as rewarding as empowering people.\nThat is why I created 30 days of python.\"\"\"\nprint(multiline_string)\n```\n\n### 문자열 연결\n\n문자열을 함께 연결할 수 있습니다. 문자열을 병합하거나 연결하는 것을 연결이라고 합니다. 아래 예를 참조하십시오.\n\n```py\nfirst_name = 'Asabeneh'\nlast_name = 'Yetayeh'\nspace = ' '\nfull_name = first_name + space + last_name\nprint(full_name) # Asabeneh Yetayeh\n# Checking the length of a string using len() built-in function\nprint(len(first_name)) # 8\nprint(len(last_name)) # 7\nprint(len(first_name) > len(last_name)) # True\nprint(len(full_name)) # 16\n```\n\n### 문자열의 이스케이프 시퀀스\n\nPython 및 기타 프로그래밍 언어에서 \\ 다음에 오는 문자는 이스케이프 시퀀스입니다. 가장 일반적인 이스케이프 문자를 살펴보겠습니다.\n\n- \\n: 새로운 라인\n- \\t: 탭은(8칸)을 의미합니다.\n- \\\\: 백슬래시\n- \\': 작은따옴표(')\n- \\\": 큰따옴표(\")\n\n이제 위의 이스케이프 시퀀스를 예제와 함께 사용하는 방법을 살펴보겠습니다.\n\n```py\nprint('I hope everyone is enjoying the Python Challenge.\\nAre you ?') # line break\nprint('Days\\tTopics\\tExercises') # adding tab space or 4 spaces\nprint('Day 1\\t3\\t5')\nprint('Day 2\\t3\\t5')\nprint('Day 3\\t3\\t5')\nprint('Day 4\\t3\\t5')\nprint('This is a backslash symbol (\\\\)') # To write a backslash\nprint('In every programming language it starts with \\\"Hello, World!\\\"') # to write a double quote inside a single quote\n\n# output\nI hope every one is enjoying the Python Challenge.\nAre you ?\nDays\tTopics\tExercises\nDay 1\t5\t 5\nDay 2\t6\t 20\nDay 3\t5\t 23\nDay 4\t1\t 35\nThis is a backslash symbol (\\)\nIn every programming language it starts with \"Hello, World!\"\n```\n\n### 문자열 포매팅\n\n#### 올드 스타일 문자열 형식화(% 연산자)\n\nPython에는 문자열 형식을 지정하는 여러 가지 방법이 있습니다. 이 섹션에서는 그 중 일부를 다룰 것입니다. \"%\" 연산자는 \"인수 지정자\", \"%s\"와 같은 특수 기호와 함께 일반 텍스트를 포함하는 형식 문자열과 함께 \"튜플\"(고정 크기 목록)로 묶인 변수 세트의 형식을 지정하는 데 사용됩니다. , \"%d\", \"%f\", \"%. 자릿수 f\".\n\n- %s - 문자열(또는 숫자와 같은 문자열 표현이 있는 모든 객체)\n- %d - 정수\n- %f - 부동 소수점 숫자\n- \"%. number of digits f\" - 정밀도가 고정된 부동 소수점 숫자\n\n```py\n# Strings only\nfirst_name = 'Asabeneh'\nlast_name = 'Yetayeh'\nlanguage = 'Python'\nformated_string = 'I am %s %s. I teach %s' %(first_name, last_name, language)\nprint(formated_string)\n\n# Strings and numbers\nradius = 10\npi = 3.14\narea = pi * radius ** 2\nformated_string = 'The area of circle with a radius %d is %.2f.' %(radius, area) # 2 refers the 2 significant digits after the point\n\npython_libraries = ['Django', 'Flask', 'NumPy', 'Matplotlib','Pandas']\nformated_string = 'The following are python libraries:%s' % (python_libraries)\nprint(formated_string) # \"The following are python libraries:['Django', 'Flask', 'NumPy', 'Matplotlib','Pandas']\"\n```\n\n#### 새로운스타일 문자열 형식화(str.format)\n\n이 형식은 Python 버전 3에서 도입되었습니다.\n\n```py\n\nfirst_name = 'Asabeneh'\nlast_name = 'Yetayeh'\nlanguage = 'Python'\nformated_string = 'I am {} {}. I teach {}'.format(first_name, last_name, language)\nprint(formated_string)\na = 4\nb = 3\n\nprint('{} + {} = {}'.format(a, b, a + b))\nprint('{} - {} = {}'.format(a, b, a - b))\nprint('{} * {} = {}'.format(a, b, a * b))\nprint('{} / {} = {:.2f}'.format(a, b, a / b)) # limits it to two digits after decimal\nprint('{} % {} = {}'.format(a, b, a % b))\nprint('{} // {} = {}'.format(a, b, a // b))\nprint('{} ** {} = {}'.format(a, b, a ** b))\n\n# output\n4 + 3 = 7\n4 - 3 = 1\n4 * 3 = 12\n4 / 3 = 1.33\n4 % 3 = 1\n4 // 3 = 1\n4 ** 3 = 64\n\n# Strings and numbers\nradius = 10\npi = 3.14\narea = pi * radius ** 2\nformated_string = 'The area of a circle with a radius {} is {:.2f}.'.format(radius, area) # 2 digits after decimal\nprint(formated_string)\n\n```\n\n#### 문자열 Interpolation / f-Strings (Python 3.6+)\n\n또 다른 새로운 문자열 형식화는 문자열 보간법인 f-문자열입니다. 문자열은 f로 시작하고 해당 위치에 데이터를 주입할 수 있습니다.\n\n```py\na = 4\nb = 3\nprint(f'{a} + {b} = {a +b}')\nprint(f'{a} - {b} = {a - b}')\nprint(f'{a} * {b} = {a * b}')\nprint(f'{a} / {b} = {a / b:.2f}')\nprint(f'{a} % {b} = {a % b}')\nprint(f'{a} // {b} = {a // b}')\nprint(f'{a} ** {b} = {a ** b}')\n```\n\n### 문자 시퀀스로서의 Python 문자열\n\nPython 문자열은 문자 시퀀스이며, 기본 액세스 방법을 다른 Python 순서 객체 시퀀스(목록 및 튜플)와 공유합니다. 문자열(및 모든 시퀀스의 개별 멤버)에서 단일 문자를 추출하는 가장 간단한 방법은 해당 변수로 압축을 푸는 것입니다.\n\n#### 언패킹 문자\n\n```\nlanguage = 'Python'\na,b,c,d,e,f = language # unpacking sequence characters into variables\nprint(a) # P\nprint(b) # y\nprint(c) # t\nprint(d) # h\nprint(e) # o\nprint(f) # n\n```\n\n#### 인덱스로 문자열의 문자에 액세스\n\n프로그래밍에서 카운팅은 0부터 시작합니다. 따라서 문자열의 첫 번째 문자는 인덱스가 0이고 문자열의 마지막 문자는 문자열의 길이에서 1을 뺀 값입니다.\n\n\n\n```py\nlanguage = 'Python'\nfirst_letter = language[0]\nprint(first_letter) # P\nsecond_letter = language[1]\nprint(second_letter) # y\nlast_index = len(language) - 1\nlast_letter = language[last_index]\nprint(last_letter) # n\n```\n\n오른쪽 끝에서 시작하려면 음수 인덱싱을 사용할 수 있습니다. -1은 마지막 인덱스입니다.\n\n```py\nlanguage = 'Python'\nlast_letter = language[-1]\nprint(last_letter) # n\nsecond_last = language[-2]\nprint(second_last) # o\n```\n\n#### 파이썬 문자열 슬라이싱\n\n파이썬에서는 문자열을 하위 문자열로 슬라이스할 수 있습니다.\n\n```py\nlanguage = 'Python'\nfirst_three = language[0:3] # starts at zero index and up to 3 but not include 3\nprint(first_three) #Pyt\nlast_three = language[3:6]\nprint(last_three) # hon\n# Another way\nlast_three = language[-3:]\nprint(last_three) # hon\nlast_three = language[3:]\nprint(last_three) # hon\n```\n\n#### 문자열 리버스\n\n파이썬에서 문자열을 쉽게 뒤집을 수 있습니다.\n\n```py\ngreeting = 'Hello, World!'\nprint(greeting[::-1]) # !dlroW ,olleH\n```\n\n#### 슬라이싱하는 동안 문자 건너뛰기\n\n슬라이스 메소드에 단계 인수를 전달하여 슬라이스하는 동안 문자를 건너뛸 수 있습니다.\n\n```py\nlanguage = 'Python'\npto = language[0:6:2] #\nprint(pto) # Pto\n```\n\n### 문자열 메서드\n\n문자열을 형식화할 수 있는 많은 문자열 메서드가 있습니다. 다음 예제에서 일부 문자열 메서드를 참조하십시오.\n\n- capitalize(): 문자열의 첫 번째 문자를 대문자로 변환\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.capitalize()) # 'Thirty days of python'\n```\n\n- count(): 문자열에서 하위 문자열의 발생을 반환합니다. count(substring, start=.., end=..). 시작은 카운트를 위한 시작 인덱싱이고 끝은 카운트할 마지막 인덱스입니다.\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.count('y')) # 3\nprint(challenge.count('y', 7, 14)) # 1,\nprint(challenge.count('th')) # 2`\n```\n\n- endswith(): 문자열이 지정된 끝으로 끝나는지 확인합니다.\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.endswith('on')) # True\nprint(challenge.endswith('tion')) # False\n```\n\n- expandtabs(): 탭 문자를 공백으로 바꿉니다. 기본 탭 크기는 8입니다. 탭 크기 인수를 사용합니다.\n\n```py\nchallenge = 'thirty\\tdays\\tof\\tpython'\nprint(challenge.expandtabs()) # 'thirty days of python'\nprint(challenge.expandtabs(10)) # 'thirty days of python'\n```\n\n- find(): 하위 문자열이 처음 나타나는 인덱스를 반환합니다. 찾을 수 없으면 -1을 반환합니다.\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.count('y')) # 3\nprint(challenge.count('y', 7, 14)) # 1,\nprint(challenge.count('th')) # 2`\n```\n\n- rfind(): 하위 문자열이 마지막으로 나타나는 인덱스를 반환합니다. 찾을 수 없으면 -1을 반환합니다.\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.rfind('y')) # 5\nprint(challenge.rfind('th')) # 1\n```\n\n- format(): 문자열을 더 나은 출력으로 포맷합니다. 문자열 형식에 대한 자세한 내용은 이 [링크](https://www.programiz.com/python-programming/methods/string/format) 를 확인하세요.\n\n```py\nfirst_name = 'Asabeneh'\nlast_name = 'Yetayeh'\nage = 250\njob = 'teacher'\ncountry = 'Finland'\nsentence = 'I am {} {}. I am a {}. I am {} years old. I live in {}.'.format(first_name, last_name, age, job, country)\nprint(sentence) # I am Asabeneh Yetayeh. I am 250 years old. I am a teacher. I live in Finland.\n\nradius = 10\npi = 3.14\narea = pi * radius ** 2\nresult = 'The area of a circle with radius {} is {}'.format(str(radius), str(area))\nprint(result) # The area of a circle with radius 10 is 314\n```\n\n- index(): 하위 문자열의 가장 낮은 색인을 반환하고 추가 인수는 시작 및 끝 색인을 나타냅니다(기본값 0 및 문자열 길이 - 1). 하위 문자열을 찾을 수 없으면 valueError가 발생합니다.\n\n```py\nchallenge = 'thirty days of python'\nsub_string = 'da'\nprint(challenge.index(sub_string)) # 7\nprint(challenge.index(sub_string, 9)) # error\n```\n\n- rindex(): 하위 문자열의 가장 높은 색인을 반환합니다. 추가 인수는 시작 및 끝 색인을 나타냅니다(기본값 0 및 문자열 길이 - 1).\n\n```py\nchallenge = 'thirty days of python'\nsub_string = 'da'\nprint(challenge.rindex(sub_string)) # 8\nprint(challenge.rindex(sub_string, 9)) # error\n```\n\n- isalnum(): 영숫자 확인\n\n```py\nchallenge = 'ThirtyDaysPython'\nprint(challenge.isalnum()) # True\n\nchallenge = '30DaysPython'\nprint(challenge.isalnum()) # True\n\nchallenge = 'thirty days of python'\nprint(challenge.isalnum()) # False, space is not an alphanumeric character\n\nchallenge = 'thirty days of python 2019'\nprint(challenge.isalnum()) # False\n```\n\n- isalpha(): 모든 문자열 요소가 알파벳 문자(az 및 AZ)인지 확인합니다.\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.isalpha()) # False, space is once again excluded\nchallenge = 'ThirtyDaysPython'\nprint(challenge.isalpha()) # True\nnum = '123'\nprint(num.isalpha()) # False\n```\n\n- isdecimal(): 문자열의 모든 문자가 십진수(0-9)인지 확인합니다.\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.isdecimal()) # False\nchallenge = '123'\nprint(challenge.isdecimal()) # True\nchallenge = '\\u00B2'\nprint(challenge.isdigit()) # False\nchallenge = '12 3'\nprint(challenge.isdecimal()) # False, space not allowed\n```\n\n- isdigit(): 문자열의 모든 문자가 숫자인지 확인합니다(숫자는 0-9 및 일부 다른 유니코드 문자).\n\n```py\nchallenge = 'Thirty'\nprint(challenge.isdigit()) # False\nchallenge = '30'\nprint(challenge.isdigit()) # True\nchallenge = '\\u00B2'\nprint(challenge.isdigit()) # True\n```\n\n- isnumeric(): 문자열의 모든 문자가 숫자인지 또는 숫자와 관련된 것인지 확인합니다(isdigit()와 마찬가지로 ½과 같은 더 많은 기호를 허용합니다).\n\n```py\nnum = '10'\nprint(num.isnumeric()) # True\nnum = '\\u00BD' # ½\nprint(num.isnumeric()) # True\nnum = '10.5'\nprint(num.isnumeric()) # False\n```\n\n- isidentifier(): 유효한 식별자를 확인합니다. 문자열이 유효한 변수 이름인지 확인합니다.\n\n```py\nchallenge = '30DaysOfPython'\nprint(challenge.isidentifier()) # False, because it starts with a number\nchallenge = 'thirty_days_of_python'\nprint(challenge.isidentifier()) # True\n```\n\n- islower(): 문자열의 모든 알파벳 문자가 소문자인지 확인\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.islower()) # True\nchallenge = 'Thirty days of python'\nprint(challenge.islower()) # False\n```\n\n- islower(): 문자열의 모든 알파벳 문자가 소문자인지 확인\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.isupper()) # False\nchallenge = 'THIRTY DAYS OF PYTHON'\nprint(challenge.isupper()) # True\n```\n\n- join(): 연결된 문자열을 반환합니다.\n\n```py\nweb_tech = ['HTML', 'CSS', 'JavaScript', 'React']\nresult = ' '.join(web_tech)\nprint(result) # 'HTML CSS JavaScript React'\n```\n\n```py\nweb_tech = ['HTML', 'CSS', 'JavaScript', 'React']\nresult = '# '.join(web_tech)\nprint(result) # 'HTML# CSS# JavaScript# React'\n```\n\n- strip(): 문자열의 시작과 끝에서 시작하여 주어진 모든 문자를 제거합니다.\n\n```py\nchallenge = 'thirty days of pythoonnn'\nprint(challenge.strip('noth')) # 'irty days of py'\n```\n\n- replace(): 하위 문자열을 주어진 문자열로 대체합니다.\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.replace('python', 'coding')) # 'thirty days of coding'\n```\n\n- split(): 주어진 문자열 또는 공백을 구분 기호로 사용하여 문자열을 분할합니다.\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.split()) # ['thirty', 'days', 'of', 'python']\nchallenge = 'thirty, days, of, python'\nprint(challenge.split(', ')) # ['thirty', 'days', 'of', 'python']\n```\n\n- title(): 제목 케이스 문자열을 반환합니다.\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.title()) # Thirty Days Of Python\n```\n\n- swapcase(): 모든 대문자를 소문자로, 모든 소문자를 대문자로 변환\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.swapcase()) # THIRTY DAYS OF PYTHON\nchallenge = 'Thirty Days Of Python'\nprint(challenge.swapcase()) # tHIRTY dAYS oF pYTHON\n```\n\n- startswith(): 문자열이 지정된 문자열로 시작하는지 확인\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.startswith('thirty')) # True\n\nchallenge = '30 days of python'\nprint(challenge.startswith('thirty')) # False\n```\n\n🌕 당신은 특별한 사람이고 놀라운 잠재력을 가지고 있습니다. 당신은 방금 4일 차 도전을 완료했고 당신은 위대함을 향한 당신의 길에 4걸음 남았습니다. 이제 뇌와 근육을 위한 몇 가지 훈련을 하십시오.\n\n## 💻 Exercises - Day 4\n\n1. 문자열 'Thirty', 'Days', 'Of', 'Python'을 단일 문자열 'Thirty Days Of Python'에 연결합니다.\n2. 문자열 'Coding', 'For' , 'All'을 단일 문자열 'Coding For All'에 연결합니다.\n3. company라는 변수를 선언하고 초기 값 \"Coding For All\"에 할당합니다.\n4. *print()* 를 사용하여 회사 변수를 인쇄합니다.\n5. *len()* 메서드와 *print()* 를 사용하여 회사 문자열의 길이를 인쇄합니다.\n6. *upper()* 메서드를 사용하여 모든 문자를 대문자로 변경합니다.\n7. *lower()* 메서드를 사용하여 모든 문자를 소문자로 변경합니다.\n8. 문자열 *Coding For All* 의 값을 형식화하려면 capitalize(), title(), swapcase() 메소드를 사용하십시오.\n9. *Coding For All* 문자열의 첫 번째 단어를 잘라냅니다.\n10. Index, find 또는 기타 방법을 사용하여 *Coding For All* 문자열에 단어 Coding이 포함되어 있는지 확인합니다.\n11. 문자열 'Coding For All'의 코딩이라는 단어를 Python으로 바꿉니다.\n12. replace 메서드 또는 기타 메서드를 사용하여 모두를 위한 Python을 모두를 위한 Python으로 변경합니다.\n13. 공백을 구분 기호로 사용하여 문자열 'Coding For All'을 분할합니다(split()).\n14. \"Facebook, Google, Microsoft, Apple, IBM, Oracle, Amazon\"은 쉼표에서 문자열을 나눕니다.\n15. 문자열 *Coding For All* 에서 인덱스 0에 있는 문자는 무엇입니까?\n16. 문자열 *Coding For All* 에서 인덱스 0에 있는 문자는 무엇입니까?\n17. \"Coding For All\" 문자열에서 인덱스 10에 있는 문자는 무엇입니까?\n18. 'Python For Everyone'이라는 이름의 약어 또는 약어를 만듭니다.\n19. 'Coding For All'이라는 이름의 약어 또는 약어를 만듭니다.\n20. Index를 사용하여 Coding For All에서 C가 처음 나타나는 위치를 결정합니다.\n21. Index를 사용하여 Coding For All에서 F가 처음 나타나는 위치를 결정합니다.\n22. Coding For All People에서 l이 마지막으로 나타나는 위치를 결정하려면 rfind를 사용하십시오.\n23. 색인 또는 찾기를 사용하여 다음 문장에서 'because'라는 단어가 처음 나타나는 위치를 찾습니다.\n24. 색인 또는 찾기를 사용하여 다음 문장에서 'because'라는 단어가 처음 나타나는 위치를 찾습니다.\n25. 색인 또는 찾기를 사용하여 다음 문장에서 'because'라는 단어가 처음 나타나는 위치를 찾습니다.\n26. 색인 또는 찾기를 사용하여 다음 문장에서 'because'라는 단어가 처음 나타나는 위치를 찾습니다.\n27. 다음 문장에서 'because because because'라는 구문을 잘라냅니다.\n28. 'Coding For All'은 하위 문자열 *Coding* 으로 시작합니까?\n29. 'Coding For All'은 하위 문자열 *코딩* 으로 끝납니까?\n30. ' Coding For All ' , 주어진 문자열에서 왼쪽 및 오른쪽 후행 공백을 제거합니다.\n31. 다음 변수 중 isidentifier() 메서드를 사용할 때 True를 반환하는 변수는 무엇입니까?\n - 30DaysOfPython\n - thirty_days_of_python\n32. 다음 목록에는 일부 파이썬 라이브러리의 이름이 포함되어 있습니다: ['Django', 'Flask', 'Bottle', 'Pyramid', 'Falcon']. 공백 문자열이 있는 해시로 목록에 가입하십시오.\n33. 새 줄 이스케이프 시퀀스를 사용하여 다음 문장을 구분합니다.\n ```py\n I am enjoying this challenge.\n I just wonder what is next.\n ```\n34. 새 줄 이스케이프 시퀀스를 사용하여 다음 문장을 구분합니다.\n ```py\n Name Age Country City\n Asabeneh 250 Finland Helsinki\n ```\n35. 문자열 형식 지정 방법을 사용하여 다음을 표시합니다:\n\n```sh\nradius = 10\narea = 3.14 * radius ** 2\nThe area of a circle with radius 10 is 314 meters square.\n```\n\n1. 문자열 형식화 방법을 사용하여 다음을 작성하십시오:\n\n```sh\n8 + 6 = 14\n8 - 6 = 2\n8 * 6 = 48\n8 / 6 = 1.33\n8 % 6 = 2\n8 // 6 = 1\n8 ** 6 = 262144\n```\n\n🎉 축하합니다! 🎉\n\n[<< Day 3](../03_Day_Operators/03_operators.md) | [Day 5 >>](../05_Day_Lists/05_lists.md)\n"
},
{
"path": "Korean/05_Day_Lists/05_lists.md",
"content": "
\n\n[<< Day 4](../04_Day_Strings/04_strings.md) | [Day 6 >>](../06_Day_Tuples/06_tuples.md)\n\n\n\n- [Day 5](#day-5)\n - [Lists](#lists)\n - [How to Create a List](#how-to-create-a-list)\n - [Accessing List Items Using Positive Indexing](#accessing-list-items-using-positive-indexing)\n - [Accessing List Items Using Negative Indexing](#accessing-list-items-using-negative-indexing)\n - [Unpacking List Items](#unpacking-list-items)\n - [Slicing Items from a List](#slicing-items-from-a-list)\n - [Modifying Lists](#modifying-lists)\n - [Checking Items in a List](#checking-items-in-a-list)\n - [Adding Items to a List](#adding-items-to-a-list)\n - [Inserting Items into a List](#inserting-items-into-a-list)\n - [Removing Items from a List](#removing-items-from-a-list)\n - [Removing Items Using Pop](#removing-items-using-pop)\n - [Removing Items Using Del](#removing-items-using-del)\n - [Clearing List Items](#clearing-list-items)\n - [Copying a List](#copying-a-list)\n - [Joining Lists](#joining-lists)\n - [Counting Items in a List](#counting-items-in-a-list)\n - [Finding Index of an Item](#finding-index-of-an-item)\n - [Reversing a List](#reversing-a-list)\n - [Sorting List Items](#sorting-list-items)\n - [💻 Exercises: Day 5](#-exercises-day-5)\n - [Exercises: Level 1](#exercises-level-1)\n - [Exercises: Level 2](#exercises-level-2)\n\n# Day 5\n\n## Lists\n\n파이썬에는 네 가지 컬렉션 자료형이 있습니다.\n\n- List: 정렬되고 변경 가능(수정 가능)한 컬렉션입니다. 중복 값을 허용합니다.\n- Tuple: 정렬되고 변경 불가능하거나 수정 불가능한(불변) 컬렉션입니다. 중복 값을 허용합니다.\n- Set: 순서가 지정되지 않고 인덱스가 없고 수정할 수 없는 컬렉션이지만 새 아이템을 추가할 수 있습니다. 중복 값은 허용되지 않습니다.\n- Dictionary: 정렬되지 않고 변경 가능(수정 가능)하며 인덱스가 있는 컬렉션입니다. 중복 값이 없습니다.\n\n리스트는 정렬되고 수정(변경) 가능한 다양한 자료형의 컬렉션입니다. 목록은 비어 있거나 다른 자료형 아이템을 가질 수 있습니다.\n\n### How to Create a List\n\n파이썬에서 리스트는 두가지 방법으로 생성할 수 있습니다:\n\n- list 내장 함수를 사용\n\n```py\n# syntax\nlst = list()\n```\n\n```py\nempty_list = list() # 이건 빈 리스트 입니다, 리스트 안에 아무 값도 없습니다\nprint(len(empty_list)) # 0\n```\n\n- 대괄호 사용, []\n\n```py\n# syntax\nlst = []\n```\n\n```py\nempty_list = [] # 이건 빈 리스트 입니다, 리스트 안에 아무 값도 없습니다\nprint(len(empty_list)) # 0\n```\n\n초기 값이 있는 리스트입니다. _len()_ 을 사용하여 리스트의 길이를 찾습니다.\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon'] # list of fruits\nvegetables = ['Tomato', 'Potato', 'Cabbage','Onion', 'Carrot'] # list of vegetables\nanimal_products = ['milk', 'meat', 'butter', 'yoghurt'] # list of animal products\nweb_techs = ['HTML', 'CSS', 'JS', 'React','Redux', 'Node', 'MongDB'] # list of web technologies\ncountries = ['Finland', 'Estonia', 'Denmark', 'Sweden', 'Norway']\n\n# Print the lists and its length\nprint('Fruits:', fruits)\nprint('Number of fruits:', len(fruits))\nprint('Vegetables:', vegetables)\nprint('Number of vegetables:', len(vegetables))\nprint('Animal products:',animal_products)\nprint('Number of animal products:', len(animal_products))\nprint('Web technologies:', web_techs)\nprint('Number of web technologies:', len(web_techs))\nprint('Countries:', countries)\nprint('Number of countries:', len(countries))\n```\n\n```sh\noutput\nFruits: ['banana', 'orange', 'mango', 'lemon']\nNumber of fruits: 4\nVegetables: ['Tomato', 'Potato', 'Cabbage', 'Onion', 'Carrot']\nNumber of vegetables: 5\nAnimal products: ['milk', 'meat', 'butter', 'yoghurt']\nNumber of animal products: 4\nWeb technologies: ['HTML', 'CSS', 'JS', 'React', 'Redux', 'Node', 'MongDB']\nNumber of web technologies: 7\nCountries: ['Finland', 'Estonia', 'Denmark', 'Sweden', 'Norway']\nNumber of countries: 5\n```\n\n- 리스트는 서로 다른 자료형의 아이템을 가질 수 있습니다.\n\n```py\n lst = ['Asabeneh', 250, True, {'country':'Finland', 'city':'Helsinki'}] # 다른 자료형을 가진 리스트\n```\n\n### Accessing List Items Using Positive Indexing\n\n인덱스를 사용하여 리스트의 각 아이템에 액세스합니다. 리스트 인덱스는 0부터 시작합니다. 아래 그림은 인덱스가 시작되는 위치를 명확하게 보여줍니다.\n\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfirst_fruit = fruits[0] # 인덱스를 사용해 첫번째 아이템에 접근합니다\nprint(first_fruit) # banana\nsecond_fruit = fruits[1]\nprint(second_fruit) # orange\nlast_fruit = fruits[3]\nprint(last_fruit) # lemon\n# Last index\nlast_index = len(fruits) - 1\nlast_fruit = fruits[last_index]\n```\n\n### Accessing List Items Using Negative Indexing\n\n음수 인덱스는 끝에서 시작하는 것을 의미하며 -1은 마지막 아이템을, -2는 마지막에서 두번쨰 아이템을 의미합니다.\n\n\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfirst_fruit = fruits[-4]\nlast_fruit = fruits[-1]\nsecond_last = fruits[-2]\nprint(first_fruit) # banana\nprint(last_fruit) # lemon\nprint(second_last) # mango\n```\n\n### Unpacking List Items\n\n```py\nlst = ['item','item2','item3', 'item4', 'item5']\nfirst_item, second_item, third_item, *rest = lst\nprint(first_item) # item1\nprint(second_item) # item2\nprint(third_item) # item3\nprint(rest) # ['item4', 'item5']\n\n```\n\n```py\n# First Example\nfruits = ['banana', 'orange', 'mango', 'lemon','lime','apple']\nfirst_fruit, second_fruit, third_fruit, *rest = lst\nprint(first_fruit) # banana\nprint(second_fruit) # orange\nprint(third_fruit) # mango\nprint(rest) # ['lemon','lime','apple']\n# Second Example about unpacking list\nfirst, second, third,*rest, tenth = [1,2,3,4,5,6,7,8,9,10]\nprint(first) # 1\nprint(second) # 2\nprint(third) # 3\nprint(rest) # [4,5,6,7,8,9]\nprint(tenth) # 10\n# Third Example about unpacking list\ncountries = ['Germany', 'France','Belgium','Sweden','Denmark','Finland','Norway','Iceland','Estonia']\ngr, fr, bg, sw, *scandic, es = countries\nprint(gr)\nprint(fr)\nprint(bg)\nprint(sw)\nprint(scandic)\nprint(es)\n```\n\n### Slicing Items from a List\n\n- 양수 인덱싱: start, end 및 step을 지정하여 양수 인덱스 범위를 지정할 수 있습니다. 반환 값은 새 리스트가 됩니다. (start의 디폴트값 = 0, end = len(lst) - 1 (마지막 아이템), step = 1)\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nall_fruits = fruits[0:4] # 모든 fruits를 반환합니다\n# 이것또한 위와 같은 값을 반환합니다\nall_fruits = fruits[0:] # 우리가 어디서 멈출 지 설정하지 않으면, 모든 것을 포함합니다\norange_and_mango = fruits[1:3] # 첫번째 인덱스를 포함하지 않습니다\norange_mango_lemon = fruits[1:]\norange_and_lemon = fruits[::2] # 여기서 세번째 인자인 step을 사용했습니다. 모든 두번째 아이템을 포함합니다 - ['banana', 'mango']\n```\n\n- 음수 인덱싱: start, end 및 step을 지정하여 음수 인덱스의 범위를 지정할 수 있습니다. 반환 값은 새 리스트가 됩니다.\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nall_fruits = fruits[-4:] # 모든 fruits를 반환합니다\norange_and_mango = fruits[-3:-1] # 마지막 인덱스를 포함하지 않습니다,['orange', 'mango']\norange_mango_lemon = fruits[-3:] # 이것은 -3 부터 시작하여 끝까지의 값을 줍니다,['orange', 'mango', 'lemon']\nreverse_fruits = fruits[::-1] # 음수의 step은 리스트를 역순으로 가집니다,['lemon', 'mango', 'orange', 'banana']\n```\n\n### Modifying Lists\n\n리스트는 변경 가능하거나 수정 가능한 순서가 있는 아이템들의 컬렉션입니다. 과일 리스트를 수정해봅시다.\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits[0] = 'avocado'\nprint(fruits) # ['avocado', 'orange', 'mango', 'lemon']\nfruits[1] = 'apple'\nprint(fruits) # ['avocado', 'apple', 'mango', 'lemon']\nlast_index = len(fruits) - 1\nfruits[last_index] = 'lime'\nprint(fruits) # ['avocado', 'apple', 'mango', 'lime']\n```\n\n### Checking Items in a List\n\n*in* 연산자를 사용하여 아이템이 리스트의 구성원인지 확인합니다. 아래 예시를 봅시다.\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\ndoes_exist = 'banana' in fruits\nprint(does_exist) # True\ndoes_exist = 'lime' in fruits\nprint(does_exist) # False\n```\n\n### Adding Items to a List\n\n기존 리스트의 끝에 아이템을 추가하려면 *append()* 메서드를 사용합니다.\n\n```py\n# syntax\nlst = list()\nlst.append(item)\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits.append('apple')\nprint(fruits) # ['banana', 'orange', 'mango', 'lemon', 'apple']\nfruits.append('lime') # ['banana', 'orange', 'mango', 'lemon', 'apple', 'lime']\nprint(fruits)\n```\n\n### Inserting Items into a List\n\n*insert()* 메서드를 사용하여 목록의 지정된 인덱스에 하나의 아이템을 삽입할 수 있습니다. 다른 아이템들은 오른쪽으로 이동한다는 것에 주의합시다. *insert()* 메서드는 인덱스와 삽입할 아이템이라는 두 가지 인자를 가집니다.\n\n```py\n# syntax\nlst = ['item1', 'item2']\nlst.insert(index, item)\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits.insert(2, 'apple') # orange와 mango 사이에 apple을 삽입\nprint(fruits) # ['banana', 'orange', 'apple', 'mango', 'lemon']\nfruits.insert(3, 'lime') # ['banana', 'orange', 'apple', 'lime', 'mango', 'lemon']\nprint(fruits)\n```\n\n### Removing Items from a List\n\nremove 메서드는 리스트에서 지정된 아이템을 삭제합니다.\n\n```py\n# syntax\nlst = ['item1', 'item2']\nlst.remove(item)\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon', 'banana']\nfruits.remove('banana')\nprint(fruits) # ['orange', 'mango', 'lemon', 'banana'] - 이 메서드는 리스트에서 첫번째로 존재하는 아이템을 삭제합니다\nfruits.remove('lemon')\nprint(fruits) # ['orange', 'mango', 'banana']\n```\n\n### Removing Items Using Pop\n\n*pop()* 메서드는 지정된 인덱스를 제거합니다(또는 인덱스가 지정되지 않은 경우 마지막 아이템):\n\n```py\n# syntax\nlst = ['item1', 'item2']\nlst.pop() # 마지막 아이템\nlst.pop(index)\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits.pop()\nprint(fruits) # ['banana', 'orange', 'mango']\n\nfruits.pop(0)\nprint(fruits) # ['orange', 'mango']\n```\n\n### Removing Items Using Del\n\n*del* 키워드는 지정된 인덱스를 삭제하며 인덱스 범위 내의 아이템을 삭제하는 데도 사용할 수 있습니다. 또한 리스트를 완전히 삭제할 수도 있습니다.\n\n```py\n# syntax\nlst = ['item1', 'item2']\ndel lst[index] # 하니의 아이템\ndel lst # 리스트를 완전히 삭제\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon', 'kiwi', 'lime']\ndel fruits[0]\nprint(fruits) # ['orange', 'mango', 'lemon', 'kiwi', 'lime']\ndel fruits[1]\nprint(fruits) # ['orange', 'lemon', 'kiwi', 'lime']\ndel fruits[1:3] # 이것은 주어진 인덱스 사이의 아이템을 삭제합니다, 그러므로 인덱스가 3인 아이템은 삭제되지 않습니다!\nprint(fruits) # ['orange', 'lime']\ndel fruits\nprint(fruits) # NameError: name 'fruits' is not defined 가 발생해야합니다\n```\n\n### Clearing List Items\n\n*clear()* 메서드를 사용해 리스트 비우기:\n\n```py\n# syntax\nlst = ['item1', 'item2']\nlst.clear()\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits.clear()\nprint(fruits) # []\n```\n\n### Copying a List\n\n다음의 방법으로 새 변수에 재할당하여 리스트를 복사할 수 있습니다:list2 = list1. 이제 list2는 list1의 참조이며, list2에서 변경한 내용은 원본 list1도 수정합니다. 하지만 원본을 수정하고 싶지 않고 다른 사본을 갖고 싶어하는 경우가 많습니다. 위의 문제를 피하는 한 가지 방법은 _copy()_ 를 사용하는 것입니다.\n\n```py\n# syntax\nlst = ['item1', 'item2']\nlst_copy = lst.copy()\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits_copy = fruits.copy()\nprint(fruits_copy) # ['banana', 'orange', 'mango', 'lemon']\n```\n\n### Joining Lists\n\n파이썬에서 두 개 이상의 목록을 결합하거나 연결하는 방법은 여러 가지가 있습니다.\n\n- 플러스 연산자 (+)\n\n```py\n# syntax\nlist3 = list1 + list2\n```\n\n```py\npositive_numbers = [1, 2, 3, 4, 5]\nzero = [0]\nnegative_numbers = [-5,-4,-3,-2,-1]\nintegers = negative_numbers + zero + positive_numbers\nprint(integers) # [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5]\nfruits = ['banana', 'orange', 'mango', 'lemon']\nvegetables = ['Tomato', 'Potato', 'Cabbage', 'Onion', 'Carrot']\nfruits_and_vegetables = fruits + vegetables\nprint(fruits_and_vegetables ) # ['banana', 'orange', 'mango', 'lemon', 'Tomato', 'Potato', 'Cabbage', 'Onion', 'Carrot']\n```\n\n- extend() 메서드를 사용하여 연결\n *extend()* 메서드를 사용하면 리스트에 리스트를 추가할 수 있습니다. 아래 예를 참조합시다.\n\n```py\n# syntax\nlist1 = ['item1', 'item2']\nlist2 = ['item3', 'item4', 'item5']\nlist1.extend(list2)\n```\n\n```py\nnum1 = [0, 1, 2, 3]\nnum2= [4, 5, 6]\nnum1.extend(num2)\nprint('Numbers:', num1) # Numbers: [0, 1, 2, 3, 4, 5, 6]\nnegative_numbers = [-5,-4,-3,-2,-1]\npositive_numbers = [1, 2, 3,4,5]\nzero = [0]\n\nnegative_numbers.extend(zero)\nnegative_numbers.extend(positive_numbers)\nprint('Integers:', negative_numbers) # Integers: [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5]\nfruits = ['banana', 'orange', 'mango', 'lemon']\nvegetables = ['Tomato', 'Potato', 'Cabbage', 'Onion', 'Carrot']\nfruits.extend(vegetables)\nprint('Fruits and vegetables:', fruits ) # Fruits and vegetables: ['banana', 'orange', 'mango', 'lemon', 'Tomato', 'Potato', 'Cabbage', 'Onion', 'Carrot']\n```\n\n### Counting Items in a List\n\n*count()* 메서드는 리스트에 아이템이 나타나는 횟수를 반환합니다:\n\n```py\n# syntax\nlst = ['item1', 'item2']\nlst.count(item)\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nprint(fruits.count('orange')) # 1\nages = [22, 19, 24, 25, 26, 24, 25, 24]\nprint(ages.count(24)) # 3\n```\n\n### Finding Index of an Item\n\n*index()* 메서드는 리스트에 있는 아이템의 인덱스를 반환합니다:\n\n```py\n# syntax\nlst = ['item1', 'item2']\nlst.index(item)\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nprint(fruits.index('orange')) # 1\nages = [22, 19, 24, 25, 26, 24, 25, 24]\nprint(ages.index(24)) # 2, 처음 만난 것\n```\n\n### Reversing a List\n\n*reverse()* 메서드는 리스트의 순서를 거꾸로 합니다.\n\n```py\n# syntax\nlst = ['item1', 'item2']\nlst.reverse()\n\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits.reverse()\nprint(fruits) # ['lemon', 'mango', 'orange', 'banana']\nages = [22, 19, 24, 25, 26, 24, 25, 24]\nages.reverse()\nprint(ages) # [24, 25, 24, 26, 25, 24, 19, 22]\n```\n\n### Sorting List Items\n\n리스트를 정렬하려면 _sort()_ 메서드 또는 _sorted()_ 내장 함수를 사용할 수 있습니다. _sort()_ 메서드는 리스트 아이템을 오름차순으로 정렬하고 원래 리스트를 수정합니다. 만약 _sort()_ 메서드의 reverse의 인자가 true라면, 그것은 목록을 내림차순으로 배열할 것입니다.\n\n- sort(): 이 메서드는 원래 리스트를 수정합니다\n\n ```py\n # syntax\n lst = ['item1', 'item2']\n lst.sort() # 오름차순\n lst.sort(reverse=True) # 내림차순\n ```\n\n **Example:**\n\n ```py\n fruits = ['banana', 'orange', 'mango', 'lemon']\n fruits.sort()\n print(fruits) # 알파벳순으로 정렬, ['banana', 'lemon', 'mango', 'orange']\n fruits.sort(reverse=True)\n print(fruits) # ['orange', 'mango', 'lemon', 'banana']\n ages = [22, 19, 24, 25, 26, 24, 25, 24]\n ages.sort()\n print(ages) # [19, 22, 24, 24, 24, 25, 25, 26]\n \n ages.sort(reverse=True)\n print(ages) # [26, 25, 25, 24, 24, 24, 22, 19]\n ```\n\n sorted(): 원래 리스트를 수정하지 않고 정렬된 리스트를 반환합니다\n **Example:**\n\n ```py\n fruits = ['banana', 'orange', 'mango', 'lemon']\n print(sorted(fruits)) # ['banana', 'lemon', 'mango', 'orange']\n # 역순\n fruits = ['banana', 'orange', 'mango', 'lemon']\n fruits = sorted(fruits,reverse=True)\n print(fruits) # ['orange', 'mango', 'lemon', 'banana']\n ```\n\n🌕 당신은 성실하고 이미 많은 것을 성취했습니다. 여러분은 이제 막 5일차 도전을 마쳤고 위대함을 향한 5걸음 앞에 있습니다. 이제 여러분의 뇌와 근육을 위한 운동을 하세요.\n\n## 💻 Exercises: Day 5\n\n### Exercises: Level 1\n\n1. 빈 리스트를 선언합니다\n2. 5개 이상의 아이템을 갖는 리스트를 선언합니다\n3. 당신의 리스트의 길이를 알아봅니다\n4. 리스트의 첫번째, 중간의, 마지막 아이템을 얻어봅니다\n5. mixed_data_types 라는 리스트를 선언하고, 당신의 이름, 나이, 키, 결혼 여부, 주소를 넣어봅시다\n6. it_companies 라는 이름의 목록 변수를 선언하고 초기 값에 Facebook, Google, Microsoft, Apple, IBM, Oracle 및 Amazon을 할당합니다\n7. _print()_ 를 사용하여 리스트를 프린트 합니다\n8. 리스트에 있는 기업 수를 프린트 합니다\n9. 첫번째, 중간, 마지막 기업을 프린트 합니다\n10. 기업 중 하나를 수정하고 리스트를 프린트 합니다\n11. it_companies 에 하나의 IT 기업을 추가합니다\n12. 회사 리스트 중간에 IT 기업을 추가합니다\n13. it_companies 이름 중 하나를 대문자로 변경합니다 (IBM 제외!)\n14. '#; ' 라는 문자열로 it_companies 에 연결합니다\n15. it_companies 리스트에 특정 기업이 존재하는 지 확인합니다\n16. sort() 메서드를 사용해 리스트를 정렬합니다\n17. reverse() 메서드를 사용하여 리스트를 내림차순으로 반전합니다\n18. 리스트에서 처음 3개의 기업을 잘라냅니다\n19. 리스트에서 마지막 3개의 기업을 잘라냅니다\n20. 리스트에서 중간의 IT 기업 또는 기업들을 잘라냅니다\n21. 리스트에서 첫번째 IT 기업을 삭제합니다\n22. 리스트에서 중간의 IT 기업 또는 기업들을 삭제합니다\n23. 리스트에서 마지막 IT 기업을 삭제합니다\n24. 리스트에서 모든 IT 기업을 삭제합니다\n25. IT 기업 리스트를 완전히 제거합니다\n26. 다음 리스트를 연결합니다:\n\n ```py\n front_end = ['HTML', 'CSS', 'JS', 'React', 'Redux']\n back_end = ['Node','Express', 'MongoDB']\n ```\n\n27. 26번 문제의 리스트를 연결한 후, 연결된 리스트를 복사해 full_stack 변수에 할당합니다. 그리고 Python, SQL, Redux를 삽입합니다.\n\n### Exercises: Level 2\n\n1. 다음은 10명의 학생의 나이 리스트입니다:\n\n```sh\nages = [19, 22, 19, 24, 20, 25, 26, 24, 25, 24]\n```\n\n- 리스트를 정렬하고 최소값 및 최대값 찾습니다\n- 리스트에 최소값 및 최대값을 다시 추가합니다\n- 나이의 중위값을 찾습니다(중간 아이템 하나 또는 중간 아이템 두 개를 2로 나눈 값)\n- 평균 나이를 구합니다(모든 아이템의 합을 개수로 나눈 값)\n- 나이의 범위를 구합니다(최대값 빼기 최소값)\n- (최소값 - 평균)과 (최대값 - 평균)의 값을 비교하고 _abs()_ 메서드를 사용합니다.\n\n1. [국가 목록](https://github.com/Asabeneh/30-Days-Of-Python/tree/master/data/countries.py) 에서 중간 국가를 찾습니다.\n1. 국가 리스트를 두개의 리스트로 나눕니다. 짝수라면 두개의 리스트의 크기가 갖게, 아니라면 앞의 리스트가 하나의 국가를 더 갖도록 합니다.\n1. ['China', 'Russia', 'USA', 'Finland', 'Sweden', 'Norway', 'Denmark']. 앞의 세개 국가와 나머지를 scandic countries로 unpack합니다.\n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 4](../04_Day_Strings/04_strings.md) | [Day 6 >>](../06_Day_Tuples/06_tuples.md)\n"
},
{
"path": "Korean/07_sets_ko.md",
"content": "
\n\n\n[<< Day 6](../06_Day_Tuples/06_tuples.md) | [Day 8 >>](../08_Day_Dictionaries/08_dictionaries.md)\n\n\n\n- [📘 Day 7](#-day-7)\n - [Sets](#sets)\n - [세트 만들기](#세트-만들기)\n - [세트의 길이 구하기](#세트의-길이-구하기)\n - [세트의 항목에 액세스](#세트의-항목에-엑세스)\n - [항목 확인](#항목-확인)\n - [세트에 항목 추가](#세트에-항목-추가)\n - [세트에서 항목 제거](#세트에서-항목-제거)\n - [세트의 항목 지우기](#세트의-항목-지우기)\n - [세트 삭제](#세트-삭제)\n - [목록을 집합으로 변환](#목록을-집합으로-변환)\n - [집합 결합](#집합-결합)\n - [교차 항목 찾기](#교차-항목-찾기)\n - [하위 집합 및 수퍼 집합 확인](#하위-집합-및-수퍼-집합-확인)\n - [두 세트 간의 차이 확인](#두-세트-간의-차이-확인)\n - [두 집합 간의 대칭적 차이 찾기](#두-집합-간의-대칭적-차이-찾기)\n - [집합 결합](#집합-결합)\n - [💻 Exercises: Day 7](#-exercises-day-7)\n - [Exercises: Level 1](#exercises-level-1)\n - [Exercises: Level 2](#exercises-level-2)\n - [Exercises: Level 3](#exercises-level-3)\n\n# 📘 Day 7\n\n## Sets\n\n세트는 항목의 모음입니다. 초등학교 또는 고등학교 수학 수업으로 돌아가겠습니다. 집합의 수학 정의는 Python에서도 적용될 수 있습니다. 집합은 순서가 지정되지 않고 인덱싱되지 않은 개별 요소의 모음입니다. Python에서 집합은 고유한 항목을 저장하는 데 사용되며 집합 간에 *합집합* , *교차* , *차이* , *대칭적 차이* , *하위 집합* , *상위 집합* 및 *분리 집합* 을 찾을 수 있습니다.\n\n### 세트 만들기\n\n중괄호 {}를 사용하여 세트 또는 *set()* 내장 함수를 생성합니다.\n\n- 빈 세트 만들기\n\n```py\n# syntax\nst = {}\n# or\nst = set()\n```\n\n- 초기 항목으로 세트 만들기\n\n```py\n# syntax\nst = {'item1', 'item2', 'item3', 'item4'}\n```\n\n**예시:**\n\n```py\n# syntax\nfruits = {'banana', 'orange', 'mango', 'lemon'}\n```\n\n### 세트의 길이 구하기\n\n**len()** 메서드를 사용하여 집합의 길이를 찾습니다.\n\n```py\n# syntax\nst = {'item1', 'item2', 'item3', 'item4'}\nlen(set)\n```\n\n**예시:**\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\nlen(fruits)\n```\n\n### 세트의 항목에 액세스\n\n루프를 사용하여 항목에 액세스합니다. 우리는 루프 섹션에서 이것을 볼 것입니다\n\n### 항목 확인\n\n목록에 항목이 있는지 확인하기 위해 멤버십 연산자 *에서* 사용합니다.\n\n```py\n# syntax\nst = {'item1', 'item2', 'item3', 'item4'}\nprint(\"Does set st contain item3? \", 'item3' in st) # Does set st contain item3? True\n```\n\n**예시:**\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\nprint('mango' in fruits ) # True\n```\n\n### 세트에 항목 추가\n\n세트가 생성되면 항목을 변경할 수 없으며 항목을 추가할 수도 있습니다.\n\n- *add()* 를 사용하여 하나의 항목 추가\n\n```py\n# syntax\nst = {'item1', 'item2', 'item3', 'item4'}\nst.add('item5')\n```\n\n**예시:**\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\nfruits.add('lime')\n```\n\n- *update()* 를 사용하여 여러 항목 추가 *update()* 를 사용하면 세트에 여러 항목을 추가할 수 있습니다. *update()* 는 목록 인수를 사용합니다.\n\n```py\n# syntax\nst = {'item1', 'item2', 'item3', 'item4'}\nst.update(['item5','item6','item7'])\n```\n\n**예시:**\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\nvegetables = ('tomato', 'potato', 'cabbage','onion', 'carrot')\nfruits.update(vegetables)\n```\n\n### 세트에서 항목 제거\n\n*remove()* 메서드를 사용하여 집합에서 항목을 제거할 수 있습니다. 항목을 찾을 수 없으면 *remove()* 메서드는 오류를 발생시키므로 해당 항목이 주어진 집합에 있는지 확인하는 것이 좋습니다. 그러나, *discard()* 메서드는 오류를 발생시키지 않습니다.\n\n```py\n# syntax\nst = {'item1', 'item2', 'item3', 'item4'}\nst.remove('item2')\n```\n\npop() 메서드는 목록에서 임의의 항목을 제거하고 제거된 항목을 반환합니다.\n\n**예시:**\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\nfruits.pop() # removes a random item from the set\n\n```\n\n제거된 항목에 관심이 있는 경우.\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\nremoved_item = fruits.pop()\n```\n\n### 세트의 항목 지우기\n\n세트를 지우거나 비우려면 *clear* 메소드를 사용합니다.\n\n```py\n# syntax\nst = {'item1', 'item2', 'item3', 'item4'}\nst.clear()\n```\n\n**예시:**\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\nfruits.clear()\nprint(fruits) # set()\n```\n\n### 세트 삭제\n\n세트 자체를 삭제하려면 *del* 연산자를 사용합니다.\n\n```py\n# syntax\nst = {'item1', 'item2', 'item3', 'item4'}\ndel st\n```\n\n**예시:**\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\ndel fruits\n```\n\n### 목록을 집합으로 변환\n\n리스트를 세트로, 세트를 리스트로 변환할 수 있습니다. 목록을 세트로 변환하면 중복 항목이 제거되고 고유한 항목만 예약됩니다.\n\n```py\n# syntax\nlst = ['item1', 'item2', 'item3', 'item4', 'item1']\nst = set(lst) # {'item2', 'item4', 'item1', 'item3'} - the order is random, because sets in general are unordered\n```\n\n**예시:**\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon','orange', 'banana']\nfruits = set(fruits) # {'mango', 'lemon', 'banana', 'orange'}\n```\n\n### 집합 결합\n\n*union()* 또는 *update()* 메서드를 사용하여 두 집합을 결합할 수 있습니다.\n\n- Union 이 메서드는 새 집합을 반환합니다.\n\n```py\n# syntax\nst1 = {'item1', 'item2', 'item3', 'item4'}\nst2 = {'item5', 'item6', 'item7', 'item8'}\nst3 = st1.union(st2)\n```\n\n**예시:**\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\nvegetables = {'tomato', 'potato', 'cabbage','onion', 'carrot'}\nprint(fruits.union(vegetables)) # {'lemon', 'carrot', 'tomato', 'banana', 'mango', 'orange', 'cabbage', 'potato', 'onion'}\n```\n\n- 업데이트 이 메서드는 주어진 집합에 집합을 삽입합니다.\n\n```py\n# syntax\nst1 = {'item1', 'item2', 'item3', 'item4'}\nst2 = {'item5', 'item6', 'item7', 'item8'}\nst1.update(st2) # st2 contents are added to st1\n```\n\n**예시:**\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\nvegetables = {'tomato', 'potato', 'cabbage','onion', 'carrot'}\nfruits.update(vegetables)\nprint(fruits) # {'lemon', 'carrot', 'tomato', 'banana', 'mango', 'orange', 'cabbage', 'potato', 'onion'}\n```\n\n### 교차 항목 찾기\n\nIntersection은 두 집합 모두에 있는 항목 집합을 반환합니다. 예를 참조하십시오\n\n```py\n# syntax\nst1 = {'item1', 'item2', 'item3', 'item4'}\nst2 = {'item3', 'item2'}\nst1.intersection(st2) # {'item3', 'item2'}\n```\n\n**예시:**\n\n```py\nwhole_numbers = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10}\neven_numbers = {0, 2, 4, 6, 8, 10}\nwhole_numbers.intersection(even_numbers) # {0, 2, 4, 6, 8, 10}\n\npython = {'p', 'y', 't', 'h', 'o','n'}\ndragon = {'d', 'r', 'a', 'g', 'o','n'}\npython.intersection(dragon) # {'o', 'n'}\n```\n\n### 하위 집합 및 수퍼 집합 확인\n\n집합은 다른 집합의 하위 집합 또는 상위 집합일 수 있습니다.\n\n- Subset: *issubset()*\n- Super set: *issuperset*\n\n```py\n# syntax\nst1 = {'item1', 'item2', 'item3', 'item4'}\nst2 = {'item2', 'item3'}\nst2.issubset(st1) # True\nst1.issuperset(st2) # True\n```\n\n**예시:**\n\n```py\nwhole_numbers = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10}\neven_numbers = {0, 2, 4, 6, 8, 10}\nwhole_numbers.issubset(even_numbers) # False, because it is a super set\nwhole_numbers.issuperset(even_numbers) # True\n\npython = {'p', 'y', 't', 'h', 'o','n'}\ndragon = {'d', 'r', 'a', 'g', 'o','n'}\npython.issubset(dragon) # False\n```\n\n### 두 세트 간의 차이 확인\n\n두 집합 간의 차이를 반환합니다.\n\n```py\n# syntax\nst1 = {'item1', 'item2', 'item3', 'item4'}\nst2 = {'item2', 'item3'}\nst2.difference(st1) # set()\nst1.difference(st2) # {'item1', 'item4'} => st1\\st2\n```\n\n**예시:**\n\n```py\nwhole_numbers = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10}\neven_numbers = {0, 2, 4, 6, 8, 10}\nwhole_numbers.difference(even_numbers) # {1, 3, 5, 7, 9}\n\npython = {'p', 'y', 't', 'o','n'}\ndragon = {'d', 'r', 'a', 'g', 'o','n'}\npython.difference(dragon) # {'p', 'y', 't'} - the result is unordered (characteristic of sets)\ndragon.difference(python) # {'d', 'r', 'a', 'g'}\n```\n\n### 두 집합 간의 대칭적 차이 찾기\n\n두 집합 간의 대칭 차이를 반환합니다. 수학적으로 두 세트에 있는 항목을 제외하고 두 세트의 모든 항목을 포함하는 세트를 리턴한다는 의미입니다. (A\\B) ∪ (B\\A)\n\n```py\n# syntax\nst1 = {'item1', 'item2', 'item3', 'item4'}\nst2 = {'item2', 'item3'}\n# it means (A\\B)∪(B\\A)\nst2.symmetric_difference(st1) # {'item1', 'item4'}\n```\n\n**예시:**\n\n```py\nwhole_numbers = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10}\nsome_numbers = {1, 2, 3, 4, 5}\nwhole_numbers.symmetric_difference(some_numbers) # {0, 6, 7, 8, 9, 10}\n\npython = {'p', 'y', 't', 'h', 'o','n'}\ndragon = {'d', 'r', 'a', 'g', 'o','n'}\npython.symmetric_difference(dragon) # {'r', 't', 'p', 'y', 'g', 'a', 'd', 'h'}\n```\n\n### 집합 결합\n\n두 세트에 공통 항목이 없으면 분리 세트라고 합니다. *isdisjoint()* 메서드를 사용하여 두 집합이 결합인지 분리인지 확인할 수 있습니다.\n\n```py\n# syntax\nst1 = {'item1', 'item2', 'item3', 'item4'}\nst2 = {'item2', 'item3'}\nst2.isdisjoint(st1) # False\n```\n\n**예시:**\n\n```py\neven_numbers = {0, 2, 4 ,6, 8}\neven_numbers = {1, 3, 5, 7, 9}\neven_numbers.isdisjoint(odd_numbers) # True, because no common item\n\npython = {'p', 'y', 't', 'h', 'o','n'}\ndragon = {'d', 'r', 'a', 'g', 'o','n'}\npython.isdisjoint(dragon) # False, there are common items {'o', 'n'}\n```\n\n🌕 당신은 떠오르는 별입니다. 당신은 방금 7일차 챌린지를 완료했으며 위대함을 향한 당신의 길에 7걸음 앞서 있습니다. 이제 뇌와 근육을 위한 몇 가지 훈련을 하십시오.\n\n## 💻 Exercises: Day 7\n\n```py\n# sets\nit_companies = {'Facebook', 'Google', 'Microsoft', 'Apple', 'IBM', 'Oracle', 'Amazon'}\nA = {19, 22, 24, 20, 25, 26}\nB = {19, 22, 20, 25, 26, 24, 28, 27}\nage = [22, 19, 24, 25, 26, 24, 25, 24]\n```\n\n### Exercises: Level 1\n\n1. 집합 it_companies의 길이 찾기\n2. it_companies에 'Twitter' 추가\n3. it_companies 집합에 여러 IT 회사를 한 번에 삽입\n4. it_companies 집합에서 회사 중 하나를 제거합니다.\n5. 제거하다와 버리다의 차이점은 무엇인가요?\n\n### Exercises: Level 2\n\n1. A와 B를 결합\n2. 교차 항목 찾기\n3. A는 B의 부분집합\n4. A와 B는 서로소 집합입니다.\n5. A는 B와, B는 A와 조인\n6. A와 B의 대칭 차이는 무엇입니까\n7. 세트를 완전히 삭제\n\n### Exercises: Level 3\n\n1. 연령을 세트로 변환하고 목록의 길이와 세트의 길이를 비교합니다. 어느 것이 더 큽니까?\n2. 문자열, 목록, 튜플 및 집합과 같은 데이터 유형의 차이점을 설명하십시오.\n3. *저는 교사이고 사람들에게 영감을 주고 가르치는 것을 좋아합니다.* 문장에 사용된 독특한 단어는 몇 개입니까? 분할 방법을 사용하고 고유한 단어를 가져오도록 설정합니다.\n\n🎉 축하합니다! 🎉\n\n[<< 6일차](../06_Day_Tuples/06_tuples.md) | [8일차 >>](../08_Day_Dictionaries/08_dictionaries.md)\n"
},
{
"path": "Korean/08_Day_Dictionaries/08_dictionaries.md",
"content": "
\n\n[<< Day 7 ](../07_Day_Sets/07_sets.md) | [Day 9 >>](../09_Day_Conditionals/09_conditionals.md)\n\n\n\n- [📘 Day 8](#-day-8)\n - [Dictionaries](#dictionaries)\n - [Creating a Dictionary](#creating-a-dictionary)\n - [Dictionary Length](#dictionary-length)\n - [Accessing Dictionary Items](#accessing-dictionary-items)\n - [Adding Items to a Dictionary](#adding-items-to-a-dictionary)\n - [Modifying Items in a Dictionary](#modifying-items-in-a-dictionary)\n - [Checking Keys in a Dictionary](#checking-keys-in-a-dictionary)\n - [Removing Key and Value Pairs from a Dictionary](#removing-key-and-value-pairs-from-a-dictionary)\n - [Changing Dictionary to a List of Items](#changing-dictionary-to-a-list-of-items)\n - [Clearing a Dictionary](#clearing-a-dictionary)\n - [Deleting a Dictionary](#deleting-a-dictionary)\n - [Copy a Dictionary](#copy-a-dictionary)\n - [Getting Dictionary Keys as a List](#getting-dictionary-keys-as-a-list)\n - [Getting Dictionary Values as a List](#getting-dictionary-values-as-a-list)\n - [💻 Exercises: Day 8](#-exercises-day-8)\n\n# 📘 Day 8\n\n## Dictionaries\n\nDictionary는 순서가 없는 수정(변형) 가능한 쌍(키: 값)의 자료형의 컬렉션입니다.\n\n### Creating a Dictionary\n\nDictionary를 만들려면 중괄호 {} 또는 *dict()* 내장 함수를 사용합니다.\n\n```py\n# syntax\nempty_dict = {}\n# Dictionary with data values\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\n```\n\n**Example:**\n\n```py\nperson = {\n 'first_name':'Asabeneh',\n 'last_name':'Yetayeh',\n 'age':250,\n 'country':'Finland',\n 'is_marred':True,\n 'skills':['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address':{\n 'street':'Space street',\n 'zipcode':'02210'\n }\n }\n```\n\n상단의 Dictionary는 값이 어떤 자료형일 수도 있다는 것을 보여줍니다:string, boolean, list, tuple, set 또는 dictionary.\n\n### Dictionary Length\n\ndictionary 내 'key: value' 쌍의 개수를 확인합니다.\n\n```py\n# syntax\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\nprint(len(dct)) # 4\n```\n\n**Example:**\n\n```py\nperson = {\n 'first_name':'Asabeneh',\n 'last_name':'Yetayeh',\n 'age':250,\n 'country':'Finland',\n 'is_marred':True,\n 'skills':['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address':{\n 'street':'Space street',\n 'zipcode':'02210'\n }\n }\nprint(len(person)) # 7\n\n```\n\n### Accessing Dictionary Items\n\n키의 이름을 통해 딕셔너리 아이템에 접근할 수 있습니다.\n\n```py\n# syntax\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\nprint(dct['key1']) # value1\nprint(dct['key4']) # value4\n```\n\n**Example:**\n\n```py\nperson = {\n 'first_name':'Asabeneh',\n 'last_name':'Yetayeh',\n 'age':250,\n 'country':'Finland',\n 'is_marred':True,\n 'skills':['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address':{\n 'street':'Space street',\n 'zipcode':'02210'\n }\n }\nprint(person['first_name']) # Asabeneh\nprint(person['country']) # Finland\nprint(person['skills']) # ['JavaScript', 'React', 'Node', 'MongoDB', 'Python']\nprint(person['skills'][0]) # JavaScript\nprint(person['address']['street']) # Space street\nprint(person['city']) # Error\n```\n\n존재하지 않는 키의 이름으로 아이템에 접근할 경우 에러가 발생할 수 있습니다. 이 에러를 피하기위해 우리는 우선 키가 존재하는지 확인해야합니다. 또는 _get_ 메서드를 사용할수 있습니다. get 메서드는 키가 존재하지 않을 경우, NoneType object 자료형인 None을 반환합니다.\n```py\nperson = {\n 'first_name':'Asabeneh',\n 'last_name':'Yetayeh',\n 'age':250,\n 'country':'Finland',\n 'is_marred':True,\n 'skills':['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address':{\n 'street':'Space street',\n 'zipcode':'02210'\n }\n }\nprint(person.get('first_name')) # Asabeneh\nprint(person.get('country')) # Finland\nprint(person.get('skills')) #['HTML','CSS','JavaScript', 'React', 'Node', 'MongoDB', 'Python']\nprint(person.get('city')) # None\n```\n\n### Adding Items to a Dictionary\n\n딕셔너리에 새로운 키와 값의 쌍을 추가할 수 있습니다.\n\n```py\n# syntax\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\ndct['key5'] = 'value5'\n```\n\n**Example:**\n\n```py\nperson = {\n 'first_name':'Asabeneh',\n 'last_name':'Yetayeh',\n 'age':250,\n 'country':'Finland',\n 'is_marred':True,\n 'skills':['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address':{\n 'street':'Space street',\n 'zipcode':'02210'\n }\n}\nperson['job_title'] = 'Instructor'\nperson['skills'].append('HTML')\nprint(person)\n```\n\n### Modifying Items in a Dictionary\n\n딕셔너리의 아이템을 수정할 수 있습니다\n\n```py\n# syntax\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\ndct['key1'] = 'value-one'\n```\n\n**Example:**\n\n```py\nperson = {\n 'first_name':'Asabeneh',\n 'last_name':'Yetayeh',\n 'age':250,\n 'country':'Finland',\n 'is_marred':True,\n 'skills':['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address':{\n 'street':'Space street',\n 'zipcode':'02210'\n }\n }\nperson['first_name'] = 'Eyob'\nperson['age'] = 252\n```\n\n### Checking Keys in a Dictionary\n\n딕셔너리에 키가 존재하는 지 확인하기 위해 _in_ 연산자를 사용합니다\n\n```py\n# syntax\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\nprint('key2' in dct) # True\nprint('key5' in dct) # False\n```\n\n### Removing Key and Value Pairs from a Dictionary\n\n- _pop(key)_: 특정 키 이름을 가진 아이템을 삭제합니다\n- _popitem()_: 마지막 아이템을 삭제합니다\n- _del_: 특정 키 이름을 가진 아이템을 삭제합니다\n\n```py\n# syntax\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\ndct.pop('key1') # removes key1 item\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\ndct.popitem() # removes the last item\ndel dct['key2'] # removes key2 item\n```\n\n**Example:**\n\n```py\nperson = {\n 'first_name':'Asabeneh',\n 'last_name':'Yetayeh',\n 'age':250,\n 'country':'Finland',\n 'is_marred':True,\n 'skills':['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address':{\n 'street':'Space street',\n 'zipcode':'02210'\n }\n }\nperson.pop('first_name') # Removes the firstname item\nperson.popitem() # Removes the address item\ndel person['is_married'] # Removes the is_married item\n```\n\n### Changing Dictionary to a List of Items\n\n_items()_ 메서드는 딕셔너리를 튜플의 리스트로 변환합니다.\n\n```py\n# syntax\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\nprint(dct.items()) # dict_items([('key1', 'value1'), ('key2', 'value2'), ('key3', 'value3'), ('key4', 'value4')])\n```\n\n### Clearing a Dictionary\n\n딕셔너리 내의 아이템을 원하지 않는다면 _clear()_ 메서드를 사용해 비울 수 있습니다\n\n```py\n# syntax\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\nprint(dct.clear()) # None\n```\n\n### Deleting a Dictionary\n\n딕셔너리를 사용하지않는다면 완전히 지울 수 있습니다\n\n```py\n# syntax\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\ndel dct\n```\n\n### Copy a Dictionary\n\n_copy()_ 메서드를 통해 딕셔너리를 복사할 수 있습니다. copy를 사용해 원래 딕셔너리의 변화를 막을 수 있습니다.\n\n```py\n# syntax\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\ndct_copy = dct.copy() # {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\n```\n\n### Getting Dictionary Keys as a List\n\n_keys()_ 메서드는 하나의 딕셔너리의 모든 키를 리스트로 줍니다.\n\n```py\n# syntax\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\nkeys = dct.keys()\nprint(keys) # dict_keys(['key1', 'key2', 'key3', 'key4'])\n```\n\n### Getting Dictionary Values as a List\n\n_values_ 메서드는 하나의 딕셔너리의 모든 값을 리스트로 줍니다.\n\n```py\n# syntax\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\nvalues = dct.values()\nprint(values) # dict_values(['value1', 'value2', 'value3', 'value4'])\n```\n\n🌕 당신은 정말 놀라워요. 이제, 여러분은 사전의 힘으로 완전히 충전되어 있습니다. 여러분은 이제 막 8일째의 도전을 마쳤고 위대함을 향해 8보 전진했습니다. 이제 여러분의 뇌와 근육을 위한 운동을 하세요.\n\n## 💻 Exercises: Day 8\n\n1. dog라는 이름의 빈 딕셔너리를 생성합니다\n2. dog 딕셔너리에 name, color, breed, legs, age 를 추가합니다\n3. student 딕셔너리를 생성하고 first_name, last_name, gender, age, marital status, skills, country, city 와 address 를 키로 추가합니다\n4. student 딕셔너리의 길이를 얻습니다\n5. skills 의 값을 얻고 자료형을 확인합니다, list 여야 합니다\n6. 한개나 두개를 추가해 skills의 값을 수정합니다\n7. 딕셔너리의 키를 리스트로 얻습니다\n8. 딕셔너리의 값을 리스트로 얻습니다\n9. _items()_ 메서드를 이용해 튜플의 리스트로 딕셔너리를 바꿉니다\n10. 딕셔너리의 아이템중 하나를 삭제합니다\n11. 딕셔너리 중 하나를 삭제합니다\n\n🎉 CONGRATULATIONS ! 🎉\n\n[<< Day 7 ](../07_Day_Sets/07_sets.md) | [Day 9 >>](../09_Day_Conditionals/09_conditionals.md)\n"
},
{
"path": "Korean/10_loops_ko.md",
"content": "
\n\n\n[<< Day 9](../09_Day_Conditionals/09_conditionals.md) | [Day 11 >>](../11_Day_Functions/11_functions.md)\n\n\n\n- [📘 Day 10](#-day-10)\n - [Loops](#loops)\n - [While 루프](#while-루프)\n - [Break 과 Continue - Part 1](#break-과-continue---part-1)\n - [For 루프](#for-루프)\n - [Break 과 Continue - Part 2](#break-과-continue---part-2)\n - [범위 기능](#범위-기능)\n - [중첩 For 루프](#중첩-for-루프)\n - [For Else](#for-else)\n - [Pass](#pass)\n - [💻 Exercises: Day 10](#-exercises-day-10)\n - [Exercises: Level 1](#exercises-level-1)\n - [Exercises: Level 2](#exercises-level-2)\n - [Exercises: Level 3](#exercises-level-3)\n\n# 📘 Day 10\n\n## Loops\n\n인생은 일상으로 가득 차 있습니다. 프로그래밍에서 우리는 또한 많은 반복 작업을 수행합니다. 반복 작업을 처리하기 위해 프로그래밍 언어는 루프를 사용합니다. Python 프로그래밍 언어는 또한 다음 유형의 두 루프를 제공합니다.\n\n1. while loop\n2. for loop\n\n### While 루프\n\n우리는 while 루프를 만들기 위해 예약어 *while* 을 사용합니다. 주어진 조건이 만족될 때까지 문 블록을 반복적으로 실행하는 데 사용됩니다. 조건이 거짓이 되면 루프 뒤의 코드 행이 계속 실행됩니다.\n\n```py\n # syntax\nwhile condition:\n code goes here\n```\n\n**예시:**\n\n```py\ncount = 0\nwhile count < 5:\n print(count)\n count = count + 1\n#prints from 0 to 4\n```\n\n위의 while 루프에서 count가 5일 때 조건이 false가 됩니다. 이때 루프가 중지됩니다. 조건이 더 이상 참이 아닐 때 코드 블록을 실행하고 싶다면 *else* 를 사용할 수 있습니다.\n\n```py\n # syntax\nwhile condition:\n code goes here\nelse:\n code goes here\n```\n\n**예시:**\n\n```py\ncount = 0\nwhile count < 5:\n print(count)\n count = count + 1\n#prints from 0 to 4\n```\n\n위의 루프 조건은 count가 5이고 루프가 중지되고 실행이 else 문을 시작하면 거짓이 됩니다. 결과적으로 5가 인쇄됩니다.\n\n### Break 과 Continue - Part 1\n\n- 중단: 루프에서 벗어나거나 중단하고 싶을 때 중단을 사용합니다.\n\n```py\n# syntax\nwhile condition:\n code goes here\n if another_condition:\n break\n```\n\n**예시:**\n\n```py\ncount = 0\nwhile count < 5:\n print(count)\n count = count + 1\n if count == 3:\n break\n```\n\n위의 while 루프는 0, 1, 2만 인쇄하지만 3에 도달하면 중지합니다.\n\n- 계속: continue 문을 사용하면 현재 반복을 건너뛰고 다음을 계속할 수 있습니다.\n\n```py\n # syntax\nwhile condition:\n code goes here\n if another_condition:\n continue\n```\n\n**예시:**\n\n```py\ncount = 0\nwhile count < 5:\n if count == 3:\n continue\n print(count)\n count = count + 1\n```\n\n위의 while 루프는 0, 1, 2 및 4만 인쇄합니다(3을 건너뜁니다).\n\n### For 루프\n\n*for* 키워드는 다른 프로그래밍 언어와 유사하지만 구문이 약간 다른 for 루프를 만드는 데 사용됩니다. 루프는 시퀀스(즉, 목록, 튜플, 사전, 집합 또는 문자열)를 반복하는 데 사용됩니다.\n\n- For loop with list\n\n```py\n# syntax\nfor iterator in lst:\n code goes here\n```\n\n**예시:**\n\n```py\nnumbers = [0, 1, 2, 3, 4, 5]\nfor number in numbers: # number is temporary name to refer to the list's items, valid only inside this loop\n print(number) # the numbers will be printed line by line, from 0 to 5\n```\n\n- For loop with string\n\n```py\n# syntax\nfor iterator in string:\n code goes here\n```\n\n**예시:**\n\n```py\nlanguage = 'Python'\nfor letter in language:\n print(letter)\n\n\nfor i in range(len(language)):\n print(language[i])\n```\n\n- For loop with tuple\n\n```py\n# syntax\nfor iterator in tpl:\n code goes here\n```\n\n**예시:**\n\n```py\nnumbers = (0, 1, 2, 3, 4, 5)\nfor number in numbers:\n print(number)\n```\n\n- 사전을 사용한 For 루프 사전을 통한 루프는 사전의 키를 제공합니다.\n\n```py\n # syntax\nfor iterator in dct:\n code goes here\n```\n\n**예시:**\n\n```py\nperson = {\n 'first_name':'Asabeneh',\n 'last_name':'Yetayeh',\n 'age':250,\n 'country':'Finland',\n 'is_marred':True,\n 'skills':['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address':{\n 'street':'Space street',\n 'zipcode':'02210'\n }\n}\nfor key in person:\n print(key)\n\nfor key, value in person.items():\n print(key, value) # this way we get both keys and values printed out\n```\n\n- Loops in set\n\n```py\n# syntax\nfor iterator in st:\n code goes here\n```\n\n**예시:**\n\n```py\nit_companies = {'Facebook', 'Google', 'Microsoft', 'Apple', 'IBM', 'Oracle', 'Amazon'}\nfor company in it_companies:\n print(company)\n```\n\n### Break 과 Continue - Part 2\n\n짧은 알림: *중단* : 루프가 완료되기 전에 중단하고 싶을 때 중단을 사용합니다.\n\n```py\n# syntax\nfor iterator in sequence:\n code goes here\n if condition:\n break\n```\n\n**예시:**\n\n```py\nnumbers = (0,1,2,3,4,5)\nfor number in numbers:\n print(number)\n if number == 3:\n break\n```\n\n위의 예에서 루프는 3에 도달하면 중지됩니다.\n\n계속: 루프 반복에서 일부 단계를 건너뛰고 싶을 때 계속을 사용합니다.\n\n```py\n # syntax\nfor iterator in sequence:\n code goes here\n if condition:\n continue\n```\n\n**예시:**\n\n```py\nnumbers = (0,1,2,3,4,5)\nfor number in numbers:\n print(number)\n if number == 3:\n continue\n print('Next number should be ', number + 1) if number != 5 else print(\"loop's end\") # for short hand conditions need both if and else statements\nprint('outside the loop')\n```\n\n위의 예에서 숫자가 3이면 조건 *다음* 단계(루프 내부)를 건너뛰고 반복이 남아 있으면 루프 실행이 계속됩니다.\n\n### 범위 기능\n\n*range()* 함수는 숫자 목록에 사용됩니다. *범위(시작, 끝, 단계)* 는 시작, 종료 및 증분의 세 가지 매개변수를 사용합니다. 기본적으로 0부터 시작하고 증분은 1입니다. 범위 시퀀스에는 최소 1개의 인수(종료)가 필요합니다. 범위를 사용하여 시퀀스 만들기\n\n```py\nlst = list(range(11))\nprint(lst) # [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\nst = set(range(1, 11)) # 2 arguments indicate start and end of the sequence, step set to default 1\nprint(st) # {1, 2, 3, 4, 5, 6, 7, 8, 9, 10}\n\nlst = list(range(0,11,2))\nprint(lst) # [0, 2, 4, 6, 8, 10]\nst = set(range(0,11,2))\nprint(st) # {0, 2, 4, 6, 8, 10}\n```\n\n```py\n# syntax\nfor iterator in range(start, end, step):\n```\n\n**예시:**\n\n```py\nfor number in range(11):\n print(number) # prints 0 to 10, not including 11\n```\n\n### 중첩 For 루프\n\n루프 안에 루프를 작성할 수 있습니다.\n\n```py\n# syntax\nfor x in y:\n for t in x:\n print(t)\n```\n\n**예시:**\n\n```py\nperson = {\n 'first_name': 'Asabeneh',\n 'last_name': 'Yetayeh',\n 'age': 250,\n 'country': 'Finland',\n 'is_marred': True,\n 'skills': ['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address': {\n 'street': 'Space street',\n 'zipcode': '02210'\n }\n}\nfor key in person:\n if key == 'skills':\n for skill in person['skills']:\n print(skill)\n```\n\n### For Else\n\n루프가 끝날 때 메시지를 실행하려면 else를 사용합니다.\n\n```py\n# syntax\nfor iterator in range(start, end, step):\n do something\nelse:\n print('The loop ended')\n```\n\n**예시:**\n\n```py\nfor number in range(11):\n print(number) # prints 0 to 10, not including 11\nelse:\n print('The loop stops at', number)\n```\n\n### Pass\n\nPython에서 when 문이 필요하지만(세미콜론 뒤에) 코드를 실행하는 것을 좋아하지 않으므로 오류를 피하기 위해 *pass* 라는 단어를 쓸 수 있습니다. 또한 향후 진술을 위해 자리 표시자로 사용할 수 있습니다.\n\n**예시:**\n\n```py\nfor number in range(6):\n pass\n```\n\n🌕 당신은 큰 이정표를 세웠고, 당신은 멈출 수 없습니다. 계속하세요! 10일차 챌린지를 방금 완료했으며 위대함을 향한 10단계를 앞두고 있습니다. 이제 뇌와 근육을 위한 몇 가지 운동을 하십시오.\n\n## 💻 Exercises: Day 10\n\n### Exercises: Level 1\n\n1. for 루프를 사용하여 0에서 10까지 반복하고 while 루프를 사용하여 동일한 작업을 수행합니다.\n\n2. for 루프를 사용하여 10에서 0까지 반복하고 while 루프를 사용하여 동일한 작업을 수행합니다.\n\n3. print()를 7번 호출하는 루프를 작성하여 다음 삼각형을 출력합니다.\n\n ```py\n #\n ##\n ###\n ####\n #####\n ######\n #######\n ```\n\n4. 중첩 루프를 사용하여 다음을 만듭니다.\n\n ```sh\n # # # # # # # #\n # # # # # # # #\n # # # # # # # #\n # # # # # # # #\n # # # # # # # #\n # # # # # # # #\n # # # # # # # #\n # # # # # # # #\n ```\n\n5. 다음 패턴을 인쇄합니다.\n\n ```sh\n 0 x 0 = 0\n 1 x 1 = 1\n 2 x 2 = 4\n 3 x 3 = 9\n 4 x 4 = 16\n 5 x 5 = 25\n 6 x 6 = 36\n 7 x 7 = 49\n 8 x 8 = 64\n 9 x 9 = 81\n 10 x 10 = 100\n ```\n\n6. for 루프를 사용하여 ['Python', 'Numpy','Pandas','Django', 'Flask'] 목록을 반복하고 항목을 출력합니다.\n\n7. for 루프를 사용하여 0에서 100까지 반복하고 짝수만 출력\n\n8. for 루프를 사용하여 0에서 100까지 반복하고 홀수만 출력\n\n### Exercises: Level 2\n\n1. for 루프를 사용하여 0에서 100까지 반복하고 모든 숫자의 합계를 인쇄합니다.\n\n```sh\nThe sum of all numbers is 5050.\n```\n\n1. for 루프를 사용하여 0에서 100까지 반복하고 모든 짝수의 합과 모든 승산의 합을 인쇄합니다.\n\n ```sh\n The sum of all evens is 2550. And the sum of all odds is 2500.\n ```\n\n### Exercises: Level 3\n\n1. 데이터 폴더로 이동하여 [countries.py](https://github.com/Asabeneh/30-Days-Of-Python/blob/master/data/countries.py) 파일을 사용합니다. 국가를 순환하고 단어 *land* 를 포함하는 모든 국가를 추출합니다.\n2. 이것은 과일 목록입니다. ['banana', 'orange', 'mango', 'lemon'] 루프를 사용하여 순서를 뒤집습니다.\n3. 데이터 폴더로 이동하여 [countries_data.py](https://github.com/Asabeneh/30-Days-Of-Python/blob/master/data/countries-data.py) 파일을 사용합니다.\n 1. 데이터의 총 언어 수는 얼마입니까?\n 2. 데이터에서 가장 많이 사용되는 10개 언어 찾기\n 3. 세계에서 인구가 가장 많은 10개 국가 찾기\n\n🎉 축하합니다! 🎉\n\n[<< Day 9](../09_Day_Conditionals/09_conditionals.md) | [Day 11 >>](../11_Day_Functions/11_functions.md)\n"
},
{
"path": "Korean/readme_ko.md",
"content": "# 🐍 30 Days Of Python\n\n|# Day | Topics |\n|------|:---------------------------------------------------------:|\n| 01 | [Introduction](./readme_ko.md)|\n| 02 | [Variables, Built-in Functions](../02_Day_Variables_builtin_functions/02_variables_builtin_functions.md)|\n| 03 | [Operators](../03_Day_Operators/03_operators.md)|\n| 04 | [Strings](../04_Day_Strings/04_strings.md)|\n| 05 | [Lists](../05_Day_Lists/05_lists.md)|\n| 06 | [Tuples](../06_Day_Tuples/06_tuples.md)|\n| 07 | [Sets](../07_Day_Sets/07_sets.md)|\n| 08 | [Dictionaries](../08_Day_Dictionaries/08_dictionaries.md)|\n| 09 | [Conditionals](../09_Day_Conditionals/09_conditionals.md)|\n| 10 | [Loops](../10_Day_Loops/10_loops.md)|\n| 11 | [Functions](../11_Day_Functions/11_functions.md)|\n| 12 | [Modules](../12_Day_Modules/12_modules.md)|\n| 13 | [List Comprehension](../13_Day_List_comprehension/13_list_comprehension.md)|\n| 14 | [Higher Order Functions](../14_Day_Higher_order_functions/14_higher_order_functions.md)|\n| 15 | [Python Type Errors](../15_Day_Python_type_errors/15_python_type_errors.md)|\n| 16 | [Python Date time](../16_Day_Python_date_time/16_python_datetime.md) |\n| 17 | [Exception Handling](../17_Day_Exception_handling/17_exception_handling.md)|\n| 18 | [Regular Expressions](../18_Day_Regular_expressions/18_regular_expressions.md)|\n| 19 | [File Handling](../19_Day_File_handling/19_file_handling.md)|\n| 20 | [Python Package Manager](../20_Day_Python_package_manager/20_python_package_manager.md)|\n| 21 | [Classes and Objects](../21_Day_Classes_and_objects/21_classes_and_objects.md)|\n| 22 | [Web Scraping](../22_Day_Web_scraping/22_web_scraping.md)|\n| 23 | [Virtual Environment](../23_Day_Virtual_environment/23_virtual_environment.md)|\n| 24 | [Statistics](../24_Day_Statistics/24_statistics.md)|\n| 25 | [Pandas](../25_Day_Pandas/25_pandas.md)|\n| 26 | [Python web](../26_Day_Python_web/26_python_web.md)|\n| 27 | [Python with MongoDB](../27_Day_Python_with_mongodb/27_python_with_mongodb.md)|\n| 28 | [API](../28_Day_API/28_API.md)|\n| 29 | [Building API](../29_Day_Building_API/29_building_API.md)|\n| 30 | [Conclusions](../30_Day_Conclusions/30_conclusions.md)|\n\n🧡🧡🧡 HAPPY CODING 🧡🧡🧡\n\n
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\n\n\n[Day 2 >>](../02_Day_Variables_builtin_functions/02_variables_builtin_functions.md)\n\n\n\n- [🐍 30 Days Of Python](#-30-days-of-python)\n- [📘 Day 1](#-day-1)\n - [환영합니다](#환영합니다)\n - [소개](#소개)\n - [왜 Python이느냐?](#왜-python이느냐?)\n - [환경 설정](#환경-설정)\n - [Python 설치](#python-설치)\n - [Python 셸](#python-셸)\n - [Visual Studio Code 설치](#visual-studio-code-설치)\n - [visual studio code를 사용하기](#visual-studio-code를-사용하기)\n - [Python 기본](#python-기본)\n - [Python 구문](#python-구문)\n - [Python 들여쓰기](#python-들여쓰기)\n - [주석](#주석)\n - [데이터 타입](#데이터-타입)\n - [Number](#number)\n - [String](#string)\n - [Booleans](#booleans)\n - [List](#list)\n - [Dictionary](#dictionary)\n - [Tuple](#tuple)\n - [Set](#set)\n - [데이터 타입 체크](#데이터-타입-체크)\n - [Python 파일](#python-파일)\n - [💻 Exercises - Day 1](#-exercises---day-1)\n - [Exercise: Level 1](#exercise-level-1)\n - [Exercise: Level 2](#exercise-level-2)\n - [Exercise: Level 3](#exercise-level-3)\n\n# 📘 Day 1\n\n## 환영합니다\n\n_30 days of Python_에 참여하기로 결정하신 것을 **축하드립니다**. 이 챌린지에서는 Python 프로그래머가 되기 위해 필요한 모든 것과 프로그래밍의 전체 개념을 배우게 됩니다. 챌린지가 끝나면 _30DaysOfPython_프로그래밍 챌린지 인증서를 받게 됩니다.\n\n챌린지에 적극적으로 참여하고 싶다면 [30DaysOfPython challenge](https://t.me/ThirtyDaysOfPython) 텔레그램 그룹에 가입할 수 있습니다.\n\n## 소개\n\nPython은 범용 프로그래밍을 위한 고급 프로그래밍 언어입니다. 오픈 소스, 인터프리터, 객체 지향 프로그래밍 언어입니다. Python은 네덜란드 프로그래머 Guido van Rossum이 만들었습니다. Python 프로그래밍 언어의 이름은 영국 스케치 코미디 시리즈 *Month Python's Flying Circus* 에서 파생되었습니다. 첫 번째 버전은 1991년 2월 20일에 출시되었습니다. 이 30일간의 Python 챌린지는 최신 버전의 Python인 Python 3를 차근차근 배울 수 있도록 도와줄 것입니다. 주제는 30일로 나뉘며, 매일 이해하기 쉬운 설명, 실제 사례, 많은 실습 및 프로젝트가 포함된 여러 주제가 포함됩니다.\n\n이 챌린지는 Python 프로그래밍 언어를 배우고자 하는 초보자와 전문가를 위해 고안되었습니다. 챌린지를 완료하는 데 30~100일이 소요될 수 있으며 텔레그램 그룹에 적극적으로 참여하는 사람들이 챌린지를 완료할 확률이 높습니다.\n시각적 학습자이거나 동영상을 선호하는 경우 이 [완전 초보를 위한 Python 동영상](https://www.youtube.com/watch?v=11OYpBrhdyM)으로 시작할 수 있습니다.\n\n## 왜 Python이느냐?\n\n인간의 언어에 매우 가깝고 배우기 쉽고 사용하기 쉬운 프로그래밍 언어입니다.\nPython은 다양한 산업 및 회사(Google 포함)에서 사용됩니다. 웹 응용 프로그램, 데스크톱 응용 프로그램, 시스템 관리 및 기계 학습 라이브러리를 개발하는 데 사용되었습니다. Python은 데이터 과학 및 기계 학습 커뮤니티에서 널리 사용되는 언어입니다. 이것이 Python 학습을 시작하도록 설득하기에 충분하기를 바랍니다. Python은 세상을 지배하고 있으니 지배 당하기 전에 Python을 지배하십시오.\n## 환경 설정\n\n### Python 설치\n\nPython 스크립트를 실행하려면 Python을 설치해야 합니다. Python을 [다운로드](https://www.python.org/)합시다.\nWindows 사용자인 경우. 빨간색 동그라미 친 버튼을 클릭합니다.\n\n\n\nmacOS 사용자인 경우. 빨간색 동그라미 친 버튼을 클릭합니다.\n\n[](https://www.python.org/)\n\nPython이 설치되어 있는지 확인하려면 장치 터미널에 다음 명령을 작성하십시오.\n\n```shell\npython --version\n```\n\n\n\n터미널에서 보시다시피 저는 현재 _Python 3.7.5_ 버전을 사용하고 있습니다. 귀하의 Python 버전은 내 버전과 다를 수 있지만 3.6 이상이어야 합니다. Python 버전을 볼 수 있다면 잘한 것입니다. 이제 컴퓨터에 Python이 설치되었습니다. 다음 섹션으로 계속 진행하십시오.\n\n### Python 셸\n\nPython은 해석된 스크립팅 언어이므로 컴파일할 필요가 없습니다. 코드를 한 줄씩 실행한다는 의미입니다. Python은 _Python Shell(Python Interactive Shell)_과 함께 제공됩니다. 단일 Python 명령을 실행하고 결과를 얻는 데 사용됩니다.\n\nPython Shell은 사용자의 Python 코드를 기다립니다. 코드를 입력하면 코드를 해석하여 다음 줄에 결과를 표시합니다.\n터미널이나 명령 프롬프트(cmd)를 열고 쓰기:\n\n```shell\npython\n```\n\n\n\nPython 대화형 셸이 열리고 Python 코드(Python 스크립트)를 작성하기를 기다립니다. 기호 >>> 옆에 Python 스크립트를 작성하고 Enter를 누릅니다.\nPython 스크립팅 셸에서 첫 번째 스크립트를 작성해 보겠습니다.\n\n\n\n훌륭합니다. Python 대화형 셸에서 첫 번째 Python 스크립트를 작성했습니다. Python 대화형 셸을 어떻게 닫습니까?\n셸을 닫으려면 기호 옆에 >> **exit()** 명령을 작성하고 Enter 키를 누릅니다.\n\n\n\n이제 Python 대화형 셸을 여는 방법과 종료하는 방법을 알았습니다.\n\nPython은 Python이 이해하는 스크립트를 작성하면 결과를 제공하고 그렇지 않으면 오류를 반환합니다. 고의적인 실수를 하고 Python이 무엇을 반환하는지 봅시다.\n\n\n\n반환된 오류에서 볼 수 있듯이 Python은 우리가 저지른 실수와 _Syntax Error: invalid syntax_를 알고 있을 정도로 영리합니다. Python에서 x를 곱셈으로 사용하는 것은 (x)가 Python에서 유효한 구문이 아니기 때문에 구문 오류입니다. (**x**) 대신 곱셈에 별표(*)를 사용합니다. 반환된 오류는 수정해야 할 사항을 명확하게 보여줍니다.\n\n프로그램에서 오류를 식별하고 제거하는 프로세스를 *디버깅*이라고 합니다. **x** 대신 *를 넣어 디버깅해 봅시다.\n\n\n\n버그가 수정되었고 코드가 실행되었으며 예상했던 결과를 얻었습니다. 프로그래머로서 매일 이러한 종류의 오류를 보게 될 것입니다. 디버깅 방법을 아는 것이 좋습니다. 디버깅을 잘하려면 어떤 종류의 오류가 발생했는지 이해해야 합니다. 발생할 수 있는 Python 오류 중 일부는 *SyntaxError*, *IndexError*, *NameError*, *ModuleNotFoundError*, *KeyError*, *ImportError*, *AttributeError*, *TypeError*, *ValueError*, *ZeroDivisionError* 등입니다. 이후 섹션에서 다른 Python **_오류 유형_**에 대해 자세히 알아볼 것입니다.\n\nPython 대화형 셸을 사용하는 방법을 더 연습해 보겠습니다. 터미널이나 명령 프롬프트로 이동하여 **python**이라는 단어를 씁니다.\n\n\n\nPython 대화형 셸이 열립니다. 몇 가지 기본적인 수학 연산(더하기, 빼기, 곱하기, 나누기, 나머지, 지수)을 수행해 보겠습니다.\n\nPython 코드를 작성하기 전에 먼저 몇 가지 수학을 수행해 보겠습니다:\n\n- 2 + 3 = 5\n- 3 - 2 = 1\n- 3 \\* 2 = 6\n- 3 / 2 = 1.5\n- 3 ^ 2 = 3 x 3 = 9\n\nPython에는 다음과 같은 추가 작업이 있습니다:\n\n- 3 % 2 = 1 => 나머지를 구함\n- 3 // 2 = 1 => 나머지를 제거\n\n위의 수학식을 Python 코드로 바꿔봅시다. Python 셸이 열렸으며 셸 맨 처음에 주석을 작성하겠습니다.\n\n_comment_는 Python에 의해 실행되지 않는 코드의 일부입니다. 따라서 코드를 더 읽기 쉽게 만들기 위해 코드에 일부 텍스트를 남길 수 있습니다. Python은 주석 부분을 실행하지 않습니다. Python에서 주석은 해시(#) 기호로 시작합니다.\n이것이 Python에서 주석을 작성하는 방법입니다\n\n```shell\n # 주석은 해시로 시작합니다.\n # (#) 심볼로 시작하기 때문에 이것은 파이썬 주석입니다.\n```\n\n\n\n다음 섹션으로 이동하기 전에 Python 대화형 셸에서 더 많은 연습을 해 보겠습니다. 셸에서 _exit()_를 작성하여 열린 셸을 닫았다가 다시 열어 Python 셸에서 텍스트를 쓰는 방법을 연습해 봅시다.\n\n\n\n### Visual Studio Code 설치\n\nPython 대화형 셸은 작은 스크립트 코드를 시도하고 테스트하는 데 적합하지만 큰 프로젝트에는 적합하지 않습니다. 실제 작업 환경에서 개발자는 다양한 코드 편집기를 사용하여 코드를 작성합니다. 이 30일간의 Python 프로그래밍 챌린지에서는 Visual Studio 코드를 사용합니다. Visual Studio Code는 매우 인기 있는 오픈 소스 텍스트 편집기입니다. 나는 vscode의 팬이고 Visual Studio 코드를 [다운로드](https://code.visualstudio.com/)하는 것을 추천하고 싶지만, 다른 편집자를 선호한다면 가지고 있는 것을 자유롭게 따르십시오.\n\n[](https://code.visualstudio.com/)\n\nVisual Studio Code를 설치하셨다면 어떻게 사용하는지 알아보겠습니다.\n비디오를 선호하는 경우 Python용 Visual Studio Code[비디오 자습서](https://www.youtube.com/watch?v=bn7Cx4z-vSo)를 따를 수 있습니다.\n\n#### visual studio code를 사용하기\n\nVisual Studio 아이콘을 두 번 클릭하여 Visual Studio 코드를 엽니다. 열면 이런 종류의 인터페이스가 나타납니다. 레이블이 지정된 아이콘을 따라해보세요.\n\n\n\n바탕 화면에 30DaysOfPython이라는 폴더를 만듭니다. 그런 다음 Visual Studio 코드를 사용하여 엽시다.\n\n\n\n\n\n파일을 열면 30DaysOfPython 프로젝트의 디렉토리 내부에 파일과 폴더를 생성하기 위한 바로 가기가 표시됩니다. 아래에서 볼 수 있듯이 첫 번째 파일인 helloworld.py를 만들었습니다. 당신도 똑같이 할 수 있습니다.\n\n\n\n하루동안 오래 코딩을 한 후에 코드 편집기를 닫고 싶습니까? 이렇게 열린 프로젝트를 닫으면 됩니다.\n\n\n\n축하합니다. 개발 환경 설정을 완료했습니다. 코딩을 시작해 봅시다.\n\n## Python 기본\n\n### Python 구문\n\nPython 스크립트는 Python 대화형 셸 또는 코드 편집기에서 작성할 수 있습니다. Python 파일의 확장자는 .py입니다.\n\n### Python 들여 쓰기\n\n들여쓰기는 텍스트의 공백입니다. 많은 언어에서 들여쓰기는 코드 가독성을 높이는 데 사용되지만 Python은 들여쓰기를 사용하여 코드 블록을 만듭니다. 다른 프로그래밍 언어에서는 중괄호를 사용하여 들여쓰기 대신 코드 블록을 만듭니다. Python 코드를 작성할 때 흔히 발생하는 버그 중 하나는 잘못된 들여쓰기입니다.\n\n\n\n### 주석\n\n주석은 코드를 더 읽기 쉽게 만들고 코드에 설명을 남기기 위해 매우 중요합니다. Python은 코드의 주석 부분을 실행하지 않습니다.\nPython에서 해시(#)로 시작하는 모든 텍스트는 주석입니다.\n\n**예시:한 문장 주석**\n\n```shell\n # This is the first comment\n # This is the second comment\n # Python is eating the world\n```\n\n**예시: 여러 문장 주석**\n\nTriple quote can be used for multiline comment if it is not assigned to a variable\n\n```shell\n\"\"\"This is multiline comment\nmultiline comment takes multiple lines.\npython is eating the world\n\"\"\"\n```\n\n### 데이터 타입\n\nPython에는 여러 유형의 데이터 유형이 있습니다. 가장 일반적인 것부터 시작하겠습니다. 다른 데이터 유형은 다른 섹션에서 자세히 다룰 것입니다. 당분간 다양한 데이터 유형을 살펴보고 익숙해지도록 합시다. 지금은 명확하게 이해하지 않아도 됩니다.\n\n#### Number\n\n- Integer: 정수(음수, 영 그리고 양수)\n 예시:\n ... -3, -2, -1, 0, 1, 2, 3 ...\n- Float: 십진수\n 예시\n ... -3.5, -2.25, -1.0, 0.0, 1.1, 2.2, 3.5 ...\n- Complex\n 예시\n 1 + j, 2 + 4j\n\n#### String\n\n작은따옴표 또는 큰따옴표 아래에 있는 하나 이상의 문자 모음입니다. 문자열이 두 문장 이상인 경우 삼중 따옴표를 사용합니다.\n\n**예시:**\n\n```py\n'Asabeneh'\n'Finland'\n'Python'\n'I love teaching'\n'I hope you are enjoying the first day of 30DaysOfPython Challenge'\n```\n\n#### Boolean\n\n부울 데이터 유형은 True 또는 False 값입니다. T와 F는 항상 대문자여야 합니다.\n\n**예시:**\n\n```python\n True # 불이 켜져있나요? 그러면 참입니다.\n False # 불이 꺼져있나요? 그러면 거짓입니다.\n```\n\n#### List\n\nPython 리스트는 다른 데이터 유형 항목을 저장할 수 있는 정렬된 컬렉션입니다. 리스트는 JavaScript의 배열과 비슷합니다.\n\n**Example:**\n\n```py\n[0, 1, 2, 3, 4, 5] # 모두 동일한 데이터 유형 - 숫자 리스트\n['Banana', 'Orange', 'Mango', 'Avocado'] # 모두 동일한 데이터 유형 - 문자열 리스트(과일)\n['Finland','Estonia', 'Sweden','Norway'] # 모두 동일한 데이터 유형 - 문자열 리스트(국가)\n['Banana', 10, False, 9.81] # 리스트의 다양한 데이터 유형 - 문자열, 정수, 부울 및 부동 소수점\n```\n\n#### Dictionary\n\nPython 사전 개체는 키 값 쌍 형식의 정렬되지 않은 데이터 모음입니다.\n\n**Example:**\n\n```py\n{\n'first_name':'Asabeneh',\n'last_name':'Yetayeh',\n'country':'Finland',\n'age':250,\n'is_married':True,\n'skills':['JS', 'React', 'Node', 'Python']\n}\n```\n\n#### Tuple\n\n튜플은 목록과 같은 다양한 데이터 유형의 정렬된 모음이지만 튜플이 생성되면 수정할 수 없습니다. 그것들은 변할 수 없습니다.\n\n**Example:**\n\n```py\n('Asabeneh', 'Pawel', 'Brook', 'Abraham', 'Lidiya') # Names\n```\n\n```py\n('Earth', 'Jupiter', 'Neptune', 'Mars', 'Venus', 'Saturn', 'Uranus', 'Mercury') # planets\n```\n\n#### Set\n\n집합은 목록 및 튜플과 유사한 데이터 유형의 모음입니다. 목록 및 튜플과 달리 집합은 순서가 지정된 항목 모음이 아닙니다. 수학에서와 마찬가지로 Python에서 set은 고유한 항목만 저장합니다.\n\n이후 섹션에서는 각각의 모든 Python 데이터 유형에 대해 자세히 설명합니다.\n\n**Example:**\n\n```py\n{2, 4, 3, 5}\n{3.14, 9.81, 2.7} # order is not important in set\n```\n\n### 데이터 타입 체크\n\n특정 데이터/변수의 데이터 유형을 확인하기 위해 **type** 기능을 사용합니다. 다음 터미널에서 다양한 Python 데이터 유형을 볼 수 있습니다:\n\n\n\n### Python 파일\n\n먼저 프로젝트 폴더인 30DaysOfPython을 엽니다. 이 폴더가 없으면 30DaysOfPython이라는 폴더 이름을 만듭니다. 이 폴더 안에 helloworld.py라는 파일을 만듭니다. 이제 Visual Studio 코드를 사용하여 Python 대화형 셸에서 수행한 작업을 수행해 보겠습니다.\n\nPython 대화형 셸은 **print**를 사용하지 않고 인쇄했지만 Visual Studio 코드에서 결과를 보려면 내장 함수 *print()를 사용해야 합니다. *print()* 내장 함수는 *print('arument1', 'argument2', 'argument3')*와 같이 하나 이상의 인수를 사용합니다. 아래 예를 참조하십시오.\n\n**Example:**\n\n파일 이름은 helloworld.py.\n\n```py\n# Day 1 - 30DaysOfPython Challenge\n\nprint(2 + 3) # addition(+)\nprint(3 - 1) # subtraction(-)\nprint(2 * 3) # multiplication(*)\nprint(3 / 2) # division(/)\nprint(3 ** 2) # exponential(**)\nprint(3 % 2) # modulus(%)\nprint(3 // 2) # Floor division operator(//)\n\n# Checking data types\nprint(type(10)) # Int\nprint(type(3.14)) # Float\nprint(type(1 + 3j)) # Complex number\nprint(type('Asabeneh')) # String\nprint(type([1, 2, 3])) # List\nprint(type({'name':'Asabeneh'})) # Dictionary\nprint(type({9.8, 3.14, 2.7})) # Set\nprint(type((9.8, 3.14, 2.7))) # Tuple\n```\n\nPython 파일을 실행하려면 아래 이미지를 확인하세요. Visual Studio Code에서 녹색 버튼을 실행하거나 터미널에 *python helloworld.py*를 입력하여 Python 파일을 실행할 수 있습니다.\n\n\n\n🌕 좋습니다. 당신은 방금 1일차 도전을 완료했고 당신은 위대한 여정에 있습니다. 이제 뇌와 근육을 위한 몇 가지 훈련을 해봅시다.\n\n## 💻 Exercises - Day 1\n\n### Exercise: Level 1\n\n1. 사용 중인 Python 버전 확인\n2. Python 대화형 셸을 열고 다음 작업을 수행합니다. 피연산자는 3과 4입니다.\n - 더하기(+)\n - 빼기(-)\n - 곱하기(\\*)\n - 나머지(%)\n - 나누기(/)\n - 지수(\\*\\*)\n - 정수 나누기(//)\n3. Python 대화형 셸에 문자열을 씁니다. 문자열은 다음과 같습니다:\n - 이름\n - 가족 이름\n - 국가 이름\n - I am enjoying 30 days of python\n4. 다음 데이터의 데이터 유형을 확인하십시오.:\n - 10\n - 9.8\n - 3.14\n - 4 - 4j\n - ['Asabeneh', 'Python', 'Finland']\n - 이름\n - 가족 이름\n - 국가 이름\n\n### Exercise: Level 2\n\n1. 30DaysOfPython 폴더 안에 day_1이라는 폴더를 만듭니다. day_1 폴더 안에 python 파일 helloworld.py를 만들고 질문 1, 2, 3, 4를 반복하세요. Python 파일에서 작업할 때 _print()_를 사용하는 것을 잊지 마세요. 파일을 저장한 디렉토리로 이동하여 실행합니다.\n\n### Exercise: Level 3\n\n1. Number(Integer, Float, Complex), String, Boolean, List, Tuple, Set 및 Dictionary와 같은 다양한 Python 데이터 유형에 대한 예제를 작성합니다.\n2. 참고 [Euclidean distance](https://en.wikipedia.org/wiki/Euclidean_distance#:~:text=In%20mathematics%2C%20the%20Euclidean%20distance,being%20called%20the%20Pythagorean%20distance.) (2, 3) 과 (10, 8) 사이\n\n🎉 축하합니다 ! 🎉\n\n[Day 2 >>](../02_Day_Variables_builtin_functions/02_variables_builtin_functions.md)\n"
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30 Dias de Python: Dia 2 - Variaveis, Builtin Functions
\n\n[<< Dia 1](../README.md) | [Dia 3 >>](../03_Day_Operators/03_operators.md)\n\n\n\n- [📘 Dia 2](#-dia-2)\n - [Built in functions](#built-in-functions)\n - [Variaveis](#Variaveis)\n - [Declarando múltiplas váriaveis em uma linha](#Declarando-múltiplas-variaveis-em-uma-linha)\n - [Tipos de dados](#Tipos-de-Dados)\n - [Checando tipos de dados e type Casting](#Checando-tipos-de-dados-e-Casting)\n - [Numeros](#Numeros)\n - [💻 Exercicios - Dia 2](#-Exercicios---Dia-2)\n - [Exercicios: Level 1](#Exercicios-level-1)\n - [Exercicios: Level 2](#Exercicios-level-2)\n\n# 📘 Dia 2\n\n## Built in functions\n\nEm Python, temos muitas built-in functions. As built-in functions estão disponíveis globalmente para seu uso, o que significa que você pode fazer uso das built-in functions sem importar ou configurar. Algumas das built-in functions do Python mais usadas são as seguintes: _print()_, _len()_, _type()_, _int()_, _float()_, _str()_, _input()_, _list()_, _dict()_, _min()_, _max()_, _sum()_, _sorted()_, _open()_, _file()_, _help()_ e _dir()_ . Na tabela a seguir, você verá uma lista gigantesca de funções do Python retiradas da [documentação do python](https://docs.python.org/3.9/library/functions.html).\n\n\nVamos abrir o shell do Python e começar a usar algumas built-in functions.\n\n\n\nVamos praticar mais usando diferentes built-in functions\n\n\n\nComo você pode ver no terminal acima, O Python possui palavras reservadas. Não usamos palavras reservadas para declarar variáveis ou funções. Abordaremos as variáveis na próxima seção.\n\nAcredito que agora você já esteja familiarizado com as built-in functions. Vamos fazer mais uma prática de built-in functions e passaremos para a próxima seção.\n\n\n\n## Variaveis\n\nAs variáveis armazenam dados na memória do computador. Variáveis mnemônicas são recomendadas para uso em muitas linguagens de programação. Uma variável mnemônica é um nome de variável que pode ser facilmente lembrado e associado. Uma variável refere-se a um endereço de memória no qual os dados são armazenados.\nNúmero no início, caractere especial e hífen não são permitidos ao nomear uma variável. Uma variável pode ter um nome curto (como x, y, z), mas um nome mais descritivo tipo (nome, sobrenome, idade, país) é altamente recomendado.\n\nRegras da nomeclatura de variáveis no Python\n\n- O nome de uma variável deve começar com uma letra ou underline\n- O nome de uma variável não pode começar com um número\n- Um nome de variável só pode conter caracteres alfanuméricos e underlines (A-z, 0-9 e \\_ )\n- O interpretador Python diferencia maiúsculas de minúsculas (nome, nome, nome e PRIMEIRO NOME) são variáveis diferentes) então tome cuidado com isso. \n\nAqui estão alguns exemplos de nomes de variáveis válidos:\n\n```shell\nfirstname\nlastname\nage\ncountry\ncity\nfirst_name\nlast_name\ncapital_city\n_if # if we want to use reserved word as a variable\nyear_2021\nyear2021\ncurrent_year_2021\nbirth_year\nnum1\nnum2\n```\n\nNomes invalidos de variaveis\n\n```shell\nfirst-name\nfirst@name\nfirst$name\nnum-1\n1num\n```\n\nUsaremos o estilo de nomenclatura de variáveis Python padrão que foi adotado por muitos desenvolvedores Python. Os desenvolvedores Python usam a convenção de nomenclatura de variáveis snake case (snake_case). Usamos underline após cada palavra para uma variável contendo mais de uma palavra (por exemplo, primeiro_nome, sobrenome, velocidade_de_rotação_do_motor). O exemplo abaixo é um exemplo de nomenclatura padrão de variáveis, o underline é necessário quando o nome da variável tem mais de uma palavra (isso é uma boa prática).\n\nQuando atribuímos um determinado tipo de dado a uma variável, isso é chamado de declaração de variável. Por exemplo, no exemplo abaixo, meu primeiro nome é atribuído a uma variável first_name. O sinal de igual é um operador de atribuição. Atribuir significa armazenar dados na variável (dar um valor a uma variavel). O sinal de igual em Python não é igualdade como em Matemática.\n\n_Exemplo:_\n\n```py\n# Variables in Python\nfirst_name = 'Asabeneh'\nlast_name = 'Yetayeh'\ncountry = 'Finland'\ncity = 'Helsinki'\nage = 250\nis_married = True\nskills = ['HTML', 'CSS', 'JS', 'React', 'Python']\nperson_info = {\n 'firstname':'Asabeneh',\n 'lastname':'Yetayeh',\n 'country':'Finland',\n 'city':'Helsinki'\n }\n```\n\nVamos usar as funções _print()_ e _len()_. A função de impressão aceita um número ilimitado de argumentos. Um argumento é um valor que podemos passar ou colocar entre parênteses, veja o exemplo abaixo.\n\n**Exemplo:**\n\n```py\nprint('Hello, World!') # The text Hello, World! is an argument\nprint('Hello',',', 'World','!') # it can take multiple arguments, four arguments have been passed\nprint(len('Hello, World!')) # it takes only one argument\n```\n\nVamos imprimir e também encontrar o comprimento das variáveis declaradas no topo:\n\n**Exemplo:**\n\n```py\n# Printing the values stored in the variables\n\nprint('First name:', first_name)\nprint('First name length:', len(first_name))\nprint('Last name: ', last_name)\nprint('Last name length: ', len(last_name))\nprint('Country: ', country)\nprint('City: ', city)\nprint('Age: ', age)\nprint('Married: ', is_married)\nprint('Skills: ', skills)\nprint('Person information: ', person_info)\n```\n\n### Declarando múltiplas variaveis em uma linha\n\nMúltiplas variáveis também podem ser declaradas em uma linha:\n\n**Exemplo:**\n\n```py\nfirst_name, last_name, country, age, is_married = 'Asabeneh', 'Yetayeh', 'Helsink', 250, True\n\nprint(first_name, last_name, country, age, is_married)\nprint('First name:', first_name)\nprint('Last name: ', last_name)\nprint('Country: ', country)\nprint('Age: ', age)\nprint('Married: ', is_married)\n```\n\nPodemos obter a entrada do usuário usando a função _input()_. Vamos atribuir os dados que obtemos de um usuário às variáveis first_name e age.\n\n**Exemplo:**\n\n```py\nfirst_name = input('What is your name: ')\nage = input('How old are you? ')\n\nprint(first_name)\nprint(age)\n```\n\n## Tipos de Dados\n\nExistem vários tipos de dados no Python. Para identificar o tipo de dados, usamos a função _type_. Gostaria de pedir que você se concentrasse em compreender muito bem os diferentes tipos de dados. Quando se trata de programação, tudo se resume a tipos de dados. Introduzi os tipos de dados logo no início e depois veremos de novo, porque cada tópico está relacionado aos tipos de dados. Abordaremos os tipos de dados com mais detalhes em suas respectivas seções.\n\n## Checando tipos de dados e Casting\n\n- Checando tipos de dados: Para verificar o tipo de dados de determinados dados/variáveis, usamos o _type_\n **Exemplo:**\n\n```py\n# Different python data types\n# Let's declare variables with various data types\n\nfirst_name = 'Asabeneh' # str\nlast_name = 'Yetayeh' # str\ncountry = 'Finland' # str\ncity= 'Helsinki' # str\nage = 250 # int, it is not my real age, don't worry about it\n\n# Printing out types\nprint(type('Asabeneh')) # str\nprint(type(first_name)) # str\nprint(type(10)) # int\nprint(type(3.14)) # float\nprint(type(1 + 1j)) # complex\nprint(type(True)) # bool\nprint(type([1, 2, 3, 4])) # list\nprint(type({'name':'Asabeneh','age':250, 'is_married':250})) # dict\nprint(type((1,2))) # tuple\nprint(type(zip([1,2],[3,4]))) # set\n```\n\n- Type Casting: Podemos converter um tipo de dado em outro tipo de dado. Nós podemos usar esses tipos para fazer o casting _int()_, _float()_, _str()_, _list_, _set_\n Quando fazemos operações aritméticas, os números das strings devem ser primeiro convertidos para int ou float, caso contrário, retornará um erro. Se concatenarmos um número com uma string, o número deverá primeiro ser convertido em uma string. Falaremos sobre concatenação na seção String.\n\n **Exemplo:**\n\n```py\n# int to float\nnum_int = 10\nprint('num_int',num_int) # 10\nnum_float = float(num_int)\nprint('num_float:', num_float) # 10.0\n\n# float to int\ngravity = 9.81\nprint(int(gravity)) # 9\n\n# int to str\nnum_int = 10\nprint(num_int) # 10\nnum_str = str(num_int)\nprint(num_str) # '10'\n\n# str to int or float\nnum_str = '10.6'\nprint('num_int', int(num_str)) # 10\nprint('num_float', float(num_str)) # 10.6\n\n# str to list\nfirst_name = 'Asabeneh'\nprint(first_name) # 'Asabeneh'\nfirst_name_to_list = list(first_name)\nprint(first_name_to_list) # ['A', 's', 'a', 'b', 'e', 'n', 'e', 'h']\n```\n\n## Numeros\n\nNumeros e tipos de dados em python:\n\n1. Inteiros: Inteiros são considerados os(negativos, zero números positivos) \n Exemplo:\n ... -3, -2, -1, 0, 1, 2, 3 ...\n\n2. Float(Números Decimais)\n Exemplo:\n ... -3.5, -2.25, -1.0, 0.0, 1.1, 2.2, 3.5 ...\n\n3. Números Complexos\n Exemplo:\n 1 + j, 2 + 4j, 1 - 1j\n\n🌕 Você é incrível. Você acabou de completar os desafios do dia 2 e está dois passos à frente no caminho para a grandeza. Agora faça alguns exercícios para o cérebro e os músculos.\n\n## 💻 Exercicios - Dia 2\n\n### Exercicios: Level 1\n\n1. Dentro de 30DiasDePython crie uma pasta chamada dia_2. Dentro desta pasta crie um arquivo chamado variáveis.py\n2. Escreva um comentário em python dizendo: 'Dia 2/30 dias de programação em python'\n3. Declare uma variável de primeiro nome e atribua um valor a ela\n4. Declare uma variavel de sobrenome e atribua um valor a ela\n5. Declare uma variavel de nome completo e atribua um valor a ela\n6. Declare uma variavel do seu país e atribua um valor a ela\n7. Declare uma variavel da sua cidade e atribua um valor a ela\n8. Declare uma variavel da sua idade e atribua um valor a ela\n9. Declare uma variavel ano e atribua um valor a ela\n10. Declare uma variavel is_married e atribua um valor a ela\n11. Declare uma variavel is_true e atribua um valor a ela \n12. Declare uma variavel is_light_on e atribua um valor a ela\n13. Declare multiplas variaveis em uma linha\n\n### Exercicios: Level 2\n\n1. Verifique o tipo de dados de todas as suas variáveis usando a função integrada type()\n1. Usando a função integrada _len()_, encontre o comprimento do seu primeiro nome\n1. Compare o comprimento do seu nome e do seu sobrenome\n1. Declare 5 como num_one e 4 como num_two\n 1. Adicione num_one e num_two e atribua o valor a uma variável total\n 2. Subtraia num_two de num_one e atribua o valor a uma variável diff\n 3. Multiplique num_two e num_one e atribua o valor a um produto variável\n 4. Divida num_one por num_two e atribua o valor a uma divisão variável\n 5. Use a divisão de módulo para encontrar num_dois dividido por num_um e atribua o valor a uma variável restante\n 6. Calcule num_one elevado a num_two e atribua o valor a uma variável exp\n 7. Encontre a divisão mínima de num_one por num_two e atribua o valor a uma variável floor_division\n2. O raio de um círculo é de 30 metros.\n 1. Calcule a área de um círculo e atribua o valor a um nome de variável de _area_of_circle_\n 2. Calcule a circunferência de um círculo e atribua o valor a um nome de variável _circum_of_circle_\n 3. Pegue o raio como entrada do usuário e calcule a área.\n1. Use a função de entrada integrada para obter nome, sobrenome, país e idade de um usuário e armazenar o valor em seus nomes de variáveis correspondentes\n1. Execute help('keywords') no Python shell ou em seu arquivo para verificar as palavras ou palavras-chave reservadas do Python\n\n🎉 PARABÉNS ! 🎉\n\n[<< Day 1](../README.md) | [Day 3 >>](../03_Day_Operators/03_operators.md)\n"
},
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"path": "Portuguese/README.md",
"content": "# 🐍 30 Dias de python\n\n|# Day | Topics |\n|------|:---------------------------------------------------------:|\n| 01 | [Introdução](./readme.md)|\n| 02 | [Variaveis, Built-in Functions](./02_Dia_Variaveis_BuiltIn_Functions/README.md)|\n| 03 | [Operadores](./03_Day_Operators/03_operators.md)|\n| 04 | [Strings](./04_Day_Strings/04_strings.md)|\n| 05 | [Listas](./05_Day_Lists/05_lists.md)|\n| 06 | [Tuplas](./06_Day_Tuples/06_tuples.md)|\n| 07 | [Conjuntos](./07_Day_Sets/07_sets.md)|\n| 08 | [Dicionários](./08_Day_Dictionaries/08_dictionaries.md)|\n| 09 | [Condicionais](./09_Day_Conditionals/09_conditionals.md)|\n| 10 | [Loops](./10_Day_Loops/10_loops.md)|\n| 11 | [Funções](./11_Day_Functions/11_functions.md)|\n| 12 | [Modulos](./12_Day_Modules/12_modules.md)|\n| 13 | [Compreensão de Listas](./13_Day_List_comprehension/13_list_comprehension.md)|\n| 14 | [Higher Order Functions](./14_Day_Higher_order_functions/14_higher_order_functions.md)|\n| 15 | [Tripos de Erros](./15_Day_Python_type_errors/15_python_type_errors.md)|\n| 16 | [Python Date time](./16_Day_Python_date_time/16_python_datetime.md) |\n| 17 | [Manipulação de Excessão](./17_Day_Exception_handling/17_exception_handling.md)|\n| 18 | [Regex (Expressões Regulares)](./18_Day_Regular_expressions/18_regular_expressions.md)|\n| 19 | [Manipulação De Arquivos](./19_Day_File_handling/19_file_handling.md)|\n| 20 | [Gerenciador De Pacotes](./20_Day_Python_package_manager/20_python_package_manager.md)|\n| 21 | [Classes e Objetos](./21_Day_Classes_and_objects/21_classes_and_objects.md)|\n| 22 | [Web Scraping](./22_Day_Web_scraping/22_web_scraping.md)|\n| 23 | [Ambiente Virtual](./23_Day_Virtual_environment/23_virtual_environment.md)|\n| 24 | [Estatisticas](./24_Day_Statistics/24_statistics.md)|\n| 25 | [Pandas](./25_Day_Pandas/25_pandas.md)|\n| 26 | [Python web](./26_Day_Python_web/26_python_web.md)|\n| 27 | [Python com MongoDB](./27_Day_Python_with_mongodb/27_python_with_mongodb.md)|\n| 28 | [API](./28_Day_API/28_API.md)|\n| 29 | [Construindo API's](./29_Day_Building_API/29_building_API.md)|\n| 30 | [Conclusão](./30_Day_Conclusions/30_conclusions.md)|\n\n🧡🧡🧡 CODANDO FELIZ 🧡🧡🧡\n\n
\nAjudem o autor a criar mais materiais educacionais \n\n
\n\n[Dia 2 >>](./02_Dia_Variaveis_BuiltIn_Functions/README.md)\n\n\n\n- [🐍 30 Dias de python](#-30-dias-de-python)\n- [📘 Dia 1](#-dia-1)\n - [Bem Vindo!](#bem-vindo)\n - [Introdução](#introdução)\n - [Por quê Python?](#por-quê-python)\n - [Setup do ambiente](#setup-do-ambiente)\n - [Instalando o Python](#instalando-o-python)\n - [Python Shell](#python-shell)\n - [Instalando o Visual Studio Code](#instalando-o-visual-studio-code)\n - [Como usar o Visual Studio Code](#como-usar-o-visual-studio-code)\n - [Basico de Python](#basico-de-python)\n - [Sintaxe do Python](#sintaxe-do-python)\n - [Identação do Python](#identação-do-python)\n - [Comentários](#comentários)\n - [Tipos de dados](#tipos-de-dados)\n - [Números](#números)\n - [Strings](#strings)\n - [Booleanos](#booleanos)\n - [Listas](#listas)\n - [Dicionário](#dicionário)\n - [Tupla](#tupla)\n - [Set](#set)\n - [Checando Tipos de Dados](#checando-tipos-de-dados)\n - [Arquivo Python](#arquivo-python)\n - [💻 Exercicios - Dia 1](#-exercicios---dia-1)\n - [Exercicio: Level 1](#exercicio-level-1)\n - [Exercicio: Level 2](#exercicio-level-2)\n - [Exercicio: Level 3](#exercicio-level-3)\n\n# 📘 Dia 1\n\n## Bem Vindo!\n\n**Parabéns** por decidir participar do desafio de programação _30 dias de Python_ . E nesse desafio você vai aprender tudo o que você precisa para se tornar um programador python e todo o conceito de programação. No final do desafio você receberá o certificado do desafio de programação _30DiasDePython_.\n\nSe você quiser se envolver ativamente no desafio, você pode se juntar ao grupo do telegram [30DaysOfPython challenge](https://t.me/ThirtyDaysOfPython). \n\n## Introdução\n\nPython é uma linguagem de programação de alto nível para programação de uso geral. É uma linguagem de programação de código aberto, interpretada e orientada a objetos. Python foi criado por um programador holandês, Guido van Rossum. O nome da linguagem de programação Python foi derivado de uma série de comédia britânica, _Monty Python's Flying Circus_. A primeira versão foi lançada em 20 de fevereiro de 1991. Este desafio de 30 dias de Python irá ajudá-lo a aprender a versão mais recente do Python, Python 3, passo a passo. Os tópicos são divididos em 30 dias, onde cada dia contém diversos tópicos com explicações fáceis de entender, exemplos do mundo real, muitos exercícios práticos e projetos.\n\nEste desafio foi desenvolvido para iniciantes e profissionais que desejam aprender a linguagem de programação python. Pode levar de 30 a 100 dias para completar o desafio, as pessoas que participam ativamente do grupo de telegramas têm grande probabilidade de completar o desafio.\n\nEste desafio é fácil de ler, escrito originalmente em inglês coloquial e traduzido para um português, envolvente, motivador e ao mesmo tempo muito exigente. Você precisa destinar muito tempo para terminar este desafio. Se você é um dos que aprendem melhor vendo, você pode assistir às vídeo-aulas em \nCanal do Youtube do Washera Você pode começar pelo [Video de Python para iniciantes absolutos](https://youtu.be/OCCWZheOesI). Se inscreva no canal, comente suas dúvidas nos vídeos do YouTube e seja proativo, o autor eventualmente notará você.\n\nO autor gosta de ouvir sua opinião sobre o desafio, compartilhe o artigo do autor dando um feedback com sua opinião sobre o desafio 30DiasDePython. E você pode deixar seu feedback sobre o artigo em: [link](https://www.asabeneh.com/testimonials)\n\n## Por quê Python?\n\nÉ uma linguagem de programação muito próxima da linguagem humana, com uma sintaxe simples! e por isso fácil de aprender e usar. \nPython é usado por vários setores e empresas (incluindo o Google). Ele tem sido usado para desenvolver aplicações web, aplicativos de desktop, administração de sistemas e bibliotecas de machine learning. Python é uma linguagem altamente adotada na comunidade de data science e machine learning. Espero que isso seja suficiente para convencê-lo a começar a aprender Python. \n\n## Setup do ambiente\n\n### Instalando o Python\nPara executar um script escrito em Python, você precisa instalar o Python. Vamos para a página [download](https://www.python.org/) python.\nSe você for um usuario de windows. Clique no botão circulado em vermelho.\n\n[](https://www.python.org/)\n\nSe você for um usuário de MacOs. Clique no botão circulado em vermelho.\n\n[](https://www.python.org/)\n\nPara verificar se o python está instalado, digite o seguinte comando no terminal do seu dispositivo.\n```shell\npython --version\n```\n\n\n\nComo você pode ver no terminal, estou usando a versão _Python 3.7.5_ no momento. Sua versão do Python pode ser diferente da minha, mas deve ser 3.6 ou superior. Se você conseguir ver a versão python, muito bem. Python foi instalado em sua máquina. Continue para a próxima seção.\n\n### Python Shell\n\nPython é uma linguagem de script interpretada, portanto não precisa ser compilada. Isso significa que executa o código linha por linha. O Python vem com um _Python Shell (Shell Interativo do Python)_, também conhecido como REPL (Read Eval Print Loop). E é usado para executar um único comando python e obter o resultado.\n\nO Python Shell aguarda o código Python do usuário. Ao inserir o código, ele o interpreta e mostra o resultado na próxima linha.\nAbra seu terminal ou prompt de comando (cmd) e escreva:\n\n```shell\npython\n```\n\n\n\nO shell interativo do Python é aberto e aguarda que você escreva o código em Python (script Python). E você escreverá seu script Python próximo a este símbolo >>> e clique em Enter.\nVamos escrever nosso primeiro scripts no shell de script Python.\n\n\n\nMuito bem, você escreveu seu primeiro script Python no shell interativo Python. Como fechamos o shell interativo do Python?\nPara fechar o shell, próximo a este símbolo >> escreva o comando **exit()** e pressione Enter.\n\n\n\nAgora você sabe como abrir o shell interativo do Python e como sair dele.\n\nPython fornecerá resultados se você escrever scripts que Python entenda; caso contrário, retornará erros. Vamos cometer um erro proposital e ver o que o Python retornará.\n\n\n\nComo você pode ver no erro retornado, Python é tão inteligente que sabe o erro que cometemos e que foi _Syntax Error: Invalid Syntax_. Usar x como multiplicação em Python é um erro de sintaxe porque (x) não é uma sintaxe válida em Python. Em vez de (**x**) usamos asterisco (*) para multiplicação. O erro retornado mostra claramente o que corrigir.\n\nO processo de identificação e remoção de erros de um programa é chamado de _depuração_. Vamos depurá-lo colocando * no lugar de **x**.\n\n\n\nNosso bug foi corrigido, o código foi executado e obtivemos o resultado que esperávamos. Como programador, você verá esse tipo de erro diariamente. É bom saber como depurar. Para ser bom em depuração, você deve entender que tipo de erros está enfrentando. Alguns dos erros do Python que você pode encontrar são _SyntaxError_, _IndexError_, _NameError_, _ModuleNotFoundError_, _KeyError_, _ImportError_, _AttributeError_, _TypeError_, _ValueError_, _ZeroDivisionError_ etc. Veremos mais sobre diferentes tipos de erros no Python mais tarde, em outras seções! \n\nVamos praticar mais como usar o shell interativo Python. Vá para o seu terminal ou prompt de comando e escreva a palavra **python**.\n\n\n\nO shell interativo do Python é aberto. Vamos fazer algumas operações matemáticas básicas (adição, subtração, multiplicação, divisão, módulo, exponencial).\n\nVamos fazer algumas contas antes de escrever qualquer código Python:\n\n- 2 + 3 is 5\n- 3 - 2 is 1\n- 3 \\* 2 is 6\n- 3 / 2 is 1.5\n- 3 ** 2 is the same as 3 * 3\n\nEm python temos as seguintes operações adicionais:\n\n- 3 % 2 = 1 => que significa encontrar o resto ou (módulo da divisão)\n- 3 // 2 = 1 => que significa remover o resto da divisão\n\nVamos mudar as expressões matemáticas acima para código Python. O shell Python foi aberto e vamos escrever um comentário logo no início do shell.\n\nUm _comentário_ é uma parte do código que não é executada por python o comentário é ignorado pelo interpretador Python. Portanto, podemos deixar algum texto em nosso código para torná-lo mais legível. Python não executa a parte de comentários. Um comentário em python começa com o símbolo hash(#).\nÉ assim que você escreve um comentário em python:\n\n```shell\n # comment starts with hash\n # this is a python comment, because it starts with a (#) symbol\n```\n\n\n\nAntes de passarmos para a próxima seção, vamos praticar mais no shell interativo do Python. Feche o shell aberto escrevendo _exit()_ no shell e abra-o novamente e vamos praticar como escrever um texto no shell Python.\n\n\n\n### Instalando o Visual Studio Code\n\nO shell interativo Python é bom para testar pequenos códigos de script, mas não será para um grande projeto. No ambiente de trabalho real, os desenvolvedores usam diferentes editores de código para escrever códigos. Neste desafio de programação de 30 dias De Python usaremos código do visual studio. O Visual Studio Code é um editor de texto de código aberto muito popular. Sou fã do vscode e recomendo [download](https://code.visualstudio.com/) visual studio code, mas se você é a adépito a outros editores, fique à vontade para seguir com o que tiver.\n\n[](https://code.visualstudio.com/)\n\nSe você instalou o Visual Studio Code, vamos ver como usá-lo.\nSe preferir um vídeo, você pode seguir este tutorial da instalação e configuração do Visual Studio Code para Python [Video tutorial](https://www.youtube.com/watch?v=bn7Cx4z-vSo)\n\n#### Como usar o Visual Studio Code\n\nAbra o visual studio code clicando duas vezes no ícone do visual studio. Ao abri-lo, você obterá esse tipo de interface. Tente interagir com os ícones rotulados.\n\n\n\nCrie uma pasta chamada 30DiasDePython no seu desktop. Em seguida, abra-a usando o visual studio code.\n\n\n\n\n\nApós abri-lo você verá atalhos para criação de arquivos e pastas dentro do diretório do projeto 30DiasDePython. Como você pode ver abaixo, criei o primeiro arquivo, helloworld.py. Você pode fazer o mesmo.\n\n\n\nDepois de um longo dia codando, você deseja fechar seu editor de código fonte, certo? É assim que você fechará o projeto aberto.\n\n\n\nParabéns, você concluiu a configuração do ambiente de desenvolvimento. Vamos começar a codar.\n\n## Basico de Python\n\n### Sintaxe do Python\n\nUm script Python pode ser escrito no shell interativo Python ou no editor de código. Um arquivo Python possui uma extensão .py.\n\n### Identação do Python\n\nUma identação é um espaço em branco em um texto. A identação em muitas linguagens é usada para aumentar a legibilidade do código, mas o Python usa a identação para criar blocos de códigos. Em outras linguagens de programação, chaves são usadas para criar blocos de códigos em vez de a identação. Um dos bugs comuns ao escrever código um python é o erro de identação.\n\n\n\n### Comentários\n\nOs comentários são muito importantes para tornar o código mais legível e para deixar comentários em nosso código. Python não executa partes de comentários do nosso código.\nQualquer texto que comece com hash(#) em Python é um comentário.\n\n**Exemplo: de um comentário de uma linha**\n\n```shell\n # This is the first comment\n # This is the second comment\n # Python is eating the world\n```\n\n**Exemplo: de um Comentário de multiplas linhas conhecido como docstring**\n\nAspas triplas podem ser usadas para comentários de múltiplas linhas se não estiverem atribuídas a uma variável\n\n```shell\n\"\"\"This is multiline comment\nmultiline comment takes multiple lines.\npython is eating the world\n\"\"\"\n```\n\n### Tipos de dados\n\nEm Python existem vários tipos de dados. Vamos começar com os mais comuns. Diferentes tipos de dados serão abordados em detalhes em outras seções. Por enquanto, vamos examinar os diferentes tipos de dados e nos familiarizar com eles. Você não precisa ter um entendimento claro agora.\n\n#### Números\n\n- Inteiro: É considerado Inteiro(números negativos, zero e positivos)\n Exemplo:\n ... -3, -2, -1, 0, 1, 2, 3 ...\n- Float: Números decimais\n Exemplo:\n ... -3.5, -2.25, -1.0, 0.0, 1.1, 2.2, 3.5 ...\n- Complexos\n Exemplo:\n 1 + j, 2 + 4j\n\n#### Strings\n\nUma coleção de um ou mais caracteres entre aspas simples ou duplas são considerados strings. Se uma string tiver mais de uma frase, usamos aspas triplas.\n\n**Exemplo:**\n\n```py\n'Asabeneh'\n'Finland'\n'Python'\n'I love teaching'\n'I hope you are enjoying the first day of 30DaysOfPython Challenge'\n```\n\n#### Booleanos\n\nUm tipo de dado booleano é um valor True ou False. T e F devem estar sempre maiúsculos. \n\n**Exemplo:**\n\n```python\n True # Is the light on? If it is on, then the value is True\n False # Is the light on? If it is off, then the value is False\n```\n\n#### Listas\n\nA lista em Python é uma coleção ordenada que permite armazenar itens de diferentes tipos de dados. Uma lista é semelhante a um array em JavaScript.\n\n**Exemplo:**\n\n```py\n[0, 1, 2, 3, 4, 5] # all are the same data types - a list of numbers\n['Banana', 'Orange', 'Mango', 'Avocado'] # all the same data types - a list of strings (fruits)\n['Finland','Estonia', 'Sweden','Norway'] # all the same data types - a list of strings (countries)\n['Banana', 10, False, 9.81] # different data types in the list - string, integer, boolean and float\n```\n\n#### Dicionário\n\nUm objeto de dicionário Python é uma coleção não ordenada de dados em um formato de par de valores-chave.\n\n**Exemplo:**\n\n```py\n{\n'first_name':'Asabeneh',\n'last_name':'Yetayeh',\n'country':'Finland', \n'age':250, \n'is_married':True,\n'skills':['JS', 'React', 'Node', 'Python']\n}\n```\n\n#### Tupla\n\nUma tupla é uma coleção ordenada de diferentes tipos de dados, como uma lista, mas as tuplas não podem ser modificadas (são imutáveis) depois de criadas. Eles são imutáveis.\n\n**Exemplo:**\n\n```py\n('Asabeneh', 'Pawel', 'Brook', 'Abraham', 'Lidiya') # Names\n```\n\n```py\n('Earth', 'Jupiter', 'Neptune', 'Mars', 'Venus', 'Saturn', 'Uranus', 'Mercury') # planets\n```\n\n#### Set\n\nO set é uma coleção de tipos de dados semelhantes a uma lista e uma tupla. Ao contrário da lista e da tupla, set não é uma coleção ordenada de itens. Como na matemática, o conjunto em Python armazena apenas itens exclusivos.\n\nNas seções posteriores, entraremos em detalhes sobre cada tipo de dados Python.\n\n**Exemplo:**\n\n```py\n{2, 4, 3, 5}\n{3.14, 9.81, 2.7} # order is not important in set\n```\n\n### Checando Tipos de Dados\n\nPara checar um determinado tipo de dado dados/variáveis, usamos a função **type**. No terminal a seguir você verá diferentes tipos de dados python:\n\n\n\n### Arquivo Python\n\nPrimeiro abra a pasta do seu projeto, 30DiasDePython. Se você não tiver essa pasta, crie um nome de pasta chamada 30DiasDePython. Dentro desta pasta, crie um arquivo chamado helloworld.py. Agora, vamos fazer o que fizemos no shell interativo python usando o visual studio code.\n\nO shell interativo do Python estava imprimindo sem usar **print** mas no visual studio code para ver nosso resultado deveríamos usar uma função integrada _print(). A função interna _print()_ recebe um ou mais argumentos da seguinte maneira _print('arument1', 'argument2', 'argument3')_. Veja os exemplos abaixo.\n\n**Exemplo:**\n\nO nome do arquivo é helloworld.py\n\n```py\n# Day 1 - 30DaysOfPython Challenge\n\nprint(2 + 3) # addition(+)\nprint(3 - 1) # subtraction(-)\nprint(2 * 3) # multiplication(*)\nprint(3 / 2) # division(/)\nprint(3 ** 2) # exponential(**)\nprint(3 % 2) # modulus(%)\nprint(3 // 2) # Floor division operator(//)\n\n# Checking data types\nprint(type(10)) # Int\nprint(type(3.14)) # Float\nprint(type(1 + 3j)) # Complex number\nprint(type('Asabeneh')) # String\nprint(type([1, 2, 3])) # List\nprint(type({'name':'Asabeneh'})) # Dictionary\nprint(type({9.8, 3.14, 2.7})) # Set\nprint(type((9.8, 3.14, 2.7))) # Tuple\n```\n\nPara executar o arquivo python verifique a imagem abaixo. Você pode executar o arquivo python executando o botão verde em Visual Studio Code ou digitando _python helloworld.py_ no seu terminal.\n\n\n\n🌕 Você é incrível. Você acabou de completar o desafio do primeiro dia e está a caminho da grandeza. Agora faça alguns exercícios para o cérebro e os músculos.\n\n## 💻 Exercicios - Dia 1\n\n### Exercicio: Level 1\n\n1. Cheque a versão do python que você esta usando\n2. Abra o shell interativo python e execute as seguintes operações. Os operandos são 3 e 4.\n - adição(+)\n - subtração(-)\n - multiplicação(\\*)\n - modulo(%)\n - divisão(/)\n - exponencial(\\*\\*)\n - Divisão inteira(//)\n3. Escreva strings no shell interativo python. As strings são as seguintes:\n - Seu nome\n - Seu sobrenome\n - Seu país\n - Eu estou aproveitando o 30 dias de python\n4. Verifique os tipos de dados dos seguintes dados:\n - 10\n - 9.8\n - 3.14\n - 4 - 4j\n - ['Asabeneh', 'Python', 'Finland']\n - Seu nome\n - O seu sobrenome\n - Seu país\n\n### Exercicio: Level 2\n\n1. Crie uma pasta chamada dia_1 dentro da pasta 30DiasDePython. Dentro da pasta day_1, crie um arquivo python helloworld.py e repita as perguntas 1, 2, 3 e 4. Lembre-se de usar _print()_ quando estiver trabalhando em um arquivo python. Navegue até o diretório onde você salvou seu arquivo e execute-o.\n\n### Exercicio: Level 3\n\n1. Escreva um exemplo para diferentes tipos de dados Python, como Número (Inteiro, Flutuante, Complex), Strings, Booleanos, Listas, Tuplas, Set e Dicionário.\n2. Ache a [Distancia Euclidiana](https://en.wikipedia.org/wiki/Euclidean_distance#:~:text=In%20mathematics%2C%20the%20Euclidean%20distance,being%20called%20the%20Pythagorean%20distance.) entre (2, 3) e (10, 8)\n\n🎉 PARABÉNS ! 🎉\n\n[Day 2 >>](./02_Dia_Variaveis_BuiltIn_Functions/README.md)\n"
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{
"path": "Spanish/01_Day_Introduction/helloworld.py",
"content": "# Introducción\n# Día 1 - Desafío 30DaysOfPython\n\nprint(2 + 3) # suma(+)\nprint(3 - 1) # resta(-)\nprint(2 * 3) # multiplicación(*)\nprint(3 / 2) # división(/)\nprint(3 ** 2) # exponencial(**)\nprint(3 % 2) # módulo(%)\nprint(3 // 2) # División de piso(//)\n\n# Comprobando los tipos de datos\n\nprint(type(10)) # Int\nprint(type(3.14)) # Float\nprint(type(1 + 3j)) # Complejo\nprint(type('Asabeneh')) # Cadena\nprint(type([1, 2, 3])) # Lista\nprint(type({'name':'Asabeneh'})) # Diccionario\nprint(type({9.8, 3.14, 2.7})) # Conjunto\nprint(type((9.8, 3.14, 2.7))) # Tupla\n\n"
},
{
"path": "Spanish/02_Day_Variables_builtin_functions/02_variables_builtin_functions.md",
"content": "
\n
30 Dias de Python: Dia 2 - Variables, Funciones integradas
\n\n[<< Dia 1](../readme.md) | [Dia 3 >>](../03_Day_Operators/03_operators.md)\n\n\n\n- [📘 Día 2](#-día-2)\n - [Funciones integradas](#funciones-integradas)\n - [Variables](#variables)\n - [Declaración de múltiples variables en una línea](#declaración-de-múltiples-variables-en-una-línea)\n - [Tipos de datos](#tipos-de-datos)\n - [Comprobación de tipos de datos y conversión](#comprobación-de-tipos-de-datos-y-conversión)\n - [Números](#números)\n - [💻 Ejercicios - Día 2](#💻-ejercicios---día-2)\n - [Ejercicios: Nivel 1](#ejercicios-nivel-1)\n - [Ejercicios: Nivel 2](#ejercicios-nivel-2)\n\n# 📘 Dia 2\n\n## Funciones integradas\n\nEn Python tenemos muchas funciones integradas. Las funciones integradas están disponibles globalmente para su uso, lo que significa que puede hacer uso de las funciones integradas sin importarlas ni configurarlas. Algunas de las funciones integradas de Python más utilizadas son las siguientes: _print()_, _len()_, _type()_, _int()_, _float()_, _str()_, _input()_, _list()_, _dict()_, _min()_, _max()_, _sum()_, _sorted()_, _open()_, _file()_, _help()_ y _dir()_ . En la siguiente tabla, verá una lista exhaustiva de las funciones integradas de Python sacadas de la [documentación de Python](https://docs.python.org/3.9/library/functions.html).\n\n\n\nAbramos el shell de Python y comencemos a usar algunas de las funciones integradas más comunes.\n\n\n\nPractiquemos más usando diferentes funciones integradas\n\n\n\nComo puede ver en la terminal de arriba, Python tiene palabras reservadas. No usamos palabras reservadas para declarar variables o funciones. En la siguiente sección cubriremos las variables.\n\nCreo que a estas alturas ya está familiarizado con las funciones integradas. Hagamos una práctica más de funciones integradas y pasaremos a la siguiente sección.\n\n\n\n## Variables\n\nLas variables almacenan datos en la memoria de una computadora. Se recomienda el uso de variables mnemotécnicas en muchos lenguajes de programación. Una variable mnemotécnica es un nombre de variable que se puede recordar y asociar fácilmente. Una variable se refiere a una dirección de memoria en la que se almacenan los datos.\nNúmero al principio, carácter especial o guión no están permitidos al nombrar una variable. Una variable puede tener un nombre corto (como x, y, z), pero se recomienda enfáticamente un nombre más descriptivo (nombre, apellido, edad, país).\n\nReglas de nombres de variables de Python\n\n- Un nombre de variable debe comenzar con una letra o el carácter de subrayado\n- Un nombre de variable no puede comenzar con un número\n- Un nombre de variable solo puede contener caracteres alfanuméricos y guiones bajos (A-z, 0-9 y \\_)\n- Los nombres de las variables distinguen entre mayúsculas y minúsculas (firstname, Firstname, FirstName y FIRSTNAME) son variables diferentes)\n\nEstos son algunos ejemplos de nombres de variables válidos:\n\n```shell\nfirstname\nlastname\nage\ncountry\ncity\nfirst_name\nlast_name\ncapital_city\n_if # si queremos usar palabra reservada como variable\nyear_2021\nyear2021\ncurrent_year_2021\nbirth_year\nnum1\nnum2\n```\n\nNombres de variables no válidos\n\n```shell\nfirst-name\nfirst@name\nfirst$name\nnum-1\n1num\n```\n\nUsaremos el estilo estándar de nomenclatura de variables de Python que ha sido adoptado por muchos desarrolladores de Python. Los desarrolladores de Python usan la convención de nomenclatura de variables de caja de serpiente (snake_case). Usamos un carácter de subrayado después de cada palabra para una variable que contiene más de una palabra (p. ej., nombre, apellido, velocidad de rotación del motor). El siguiente ejemplo es un ejemplo de nomenclatura estándar de variables, se requiere guión bajo cuando el nombre de la variable es más de una palabra.\n\nCuando asignamos un determinado tipo de datos a una variable, se llama declaración de variable. Por ejemplo, en el siguiente ejemplo, mi nombre se asigna a una variable first_name. El signo igual es un operador de asignación. Asignar significa almacenar datos en la variable. El signo igual en Python no es la igualdad como en Matemáticas.\n\n_Ejemplo:_\n\n```py\n# Variables en Python\nfirst_name = 'Asabeneh'\nlast_name = 'Yetayeh'\ncountry = 'Finland'\ncity = 'Helsinki'\nage = 250\nis_married = True\nskills = ['HTML', 'CSS', 'JS', 'React', 'Python']\nperson_info = {\n 'firstname':'Asabeneh',\n 'lastname':'Yetayeh',\n 'country':'Finland',\n 'city':'Helsinki'\n }\n```\n\nUsemos las funciones integradas _print()_ y _len()_. La función de impresión toma un número ilimitado de argumentos. Un argumento es un valor que se puede pasar o poner dentro del paréntesis de la función, vea el ejemplo a continuación.\n\n**Ejemplo:**\n\n```py\nprint('Hello, World!') # El texto Hola, Mundo! es un argumento\nprint('Hello',',', 'World','!') # Puede tomar varios argumentos, se han pasado cuatro argumentos\nprint(len('Hello, World!')) # solo se necesita un argumento\n```\n\nImprimamos y también encontremos la longitud de las variables declaradas en la parte superior:\n\n**Ejemplo:**\n\n```py\n# Imprimiendo los valores almacenados en las variables\n\nprint('First name:', first_name)\nprint('First name length:', len(first_name))\nprint('Last name: ', last_name)\nprint('Last name length: ', len(last_name))\nprint('Country: ', country)\nprint('City: ', city)\nprint('Age: ', age)\nprint('Married: ', is_married)\nprint('Skills: ', skills)\nprint('Person information: ', person_info)\n```\n\n### Declaración de múltiples variables en una línea\n\nTambién se pueden declarar múltiples variables en una línea:\n\n**Ejemplo:**\n\n```py\nfirst_name, last_name, country, age, is_married = 'Asabeneh', 'Yetayeh', 'Helsink', 250, True\n\nprint(first_name, last_name, country, age, is_married)\nprint('First name:', first_name)\nprint('Last name: ', last_name)\nprint('Country: ', country)\nprint('Age: ', age)\nprint('Married: ', is_married)\n```\n\nObtener la entrada del usuario usando la función integrada _input()_. Asignemos los datos que obtenemos de un usuario a las variables first_name y age.\n**Ejemplo:**\n\n```py\nfirst_name = input('What is your name: ')\nage = input('How old are you? ')\n\nprint(first_name)\nprint(age)\n```\n\n## Tipos de datos\n\nHay varios tipos de datos en Python. Para identificar el tipo de datos usamos la función incorporada _type_. Me gustaría pedirle que se concentre en comprender muy bien los diferentes tipos de datos. Cuando se trata de programar, todo se trata de tipos de datos. Introduje los tipos de datos desde el principio y viene de nuevo, porque todos los temas están relacionados con los tipos de datos. Cubriremos los tipos de datos con más detalle en sus respectivas secciones.\n\n## Comprobación de tipos de datos y conversión\n\n- Verificar tipos de datos: para verificar el tipo de datos de ciertos datos/variables usamos el _type_\n **Ejemplo:**\n\n```py\n# Diferentes tipos de datos en python\n# Declaremos variables con varios tipos de datos\n\nfirst_name = 'Asabeneh' # str\nlast_name = 'Yetayeh' # str\ncountry = 'Finland' # str\ncity= 'Helsinki' # str\nage = 250 # int, no es mi edad real, no te preocupes\n\n# Imprimir tipos\nprint(type('Asabeneh')) # str\nprint(type(first_name)) # str\nprint(type(10)) # int\nprint(type(3.14)) # float\nprint(type(1 + 1j)) # complex\nprint(type(True)) # bool\nprint(type([1, 2, 3, 4])) # list\nprint(type({'name':'Asabeneh','age':250, 'is_married':250})) # dict\nprint(type((1,2))) # tuple\nprint(type(zip([1,2],[3,4]))) # set\n```\n\n- Casting: Conversión de un tipo de dato a otro tipo de dato. Usamos _int()_, _float()_, _str()_, _list_, _set_\n Cuando hacemos operaciones aritméticas, los números de cadena deben convertirse primero a int o float; de lo contrario, devolverá un error. Si concatenamos un número con una cadena, el número debe convertirse primero en una cadena. Hablaremos sobre la concatenación en la sección String.\n\n **Ejemplo:**\n\n```py\n# int a float\nnum_int = 10\nprint('num_int',num_int) # 10\nnum_float = float(num_int)\nprint('num_float:', num_float) # 10.0\n\n# float a int\ngravity = 9.81\nprint(int(gravity)) # 9\n\n# int a str\nnum_int = 10\nprint(num_int) # 10\nnum_str = str(num_int)\nprint(num_str) # '10'\n\n# str a int o float\nnum_str = '10.6'\nprint('num_int', int(num_str)) # 10\nprint('num_float', float(num_str)) # 10.6\n\n# str a list\nfirst_name = 'Asabeneh'\nprint(first_name) # 'Asabeneh'\nfirst_name_to_list = list(first_name)\nprint(first_name_to_list) # ['A', 's', 'a', 'b', 'e', 'n', 'e', 'h']\n```\n\n## Números\n\nTipos de datos numéricos en Python:\n\n1. Integers: números enteros (negativos, cero y positivos)\n Ejemplo:\n ... -3, -2, -1, 0, 1, 2, 3...\n\n2. Floating: números de coma (números decimales)\n Ejemplo:\n ... -3,5, -2,25, -1,0, 0,0, 1,1, 2,2, 3,5...\n\n3. Complex: números complejos\n Ejemplo:\n 1 + j, 2 + 4j, 1 - 1j\n\n🌕 Eres increíble. Acaba de completar los desafíos del día 2 y está dos pasos por delante en su camino hacia la grandeza. Ahora haz algunos ejercicios para tu cerebro y tus músculos.\n\n## 💻 Ejercicios - Día 2\n\n### Ejercicios: Nivel 1\n\n1. Dentro de 30DaysOfPython crea una carpeta llamada day_2. Dentro de esta carpeta crea un archivo llamado variables.py\n2. Escriba un comentario de python que diga 'Día 2: 30 días de programación en python'\n3. Declarar una variable de nombre y asignarle un valor\n4. Declarar una variable de apellido y asignarle un valor\n5. Declare una variable de nombre completo y asígnele un valor\n6. Declarar una variable de país y asignarle un valor\n7. Declarar una variable de ciudad y asignarle un valor\n8. Declarar una variable de edad y asignarle un valor\n9. Declarar una variable de año y asignarle un valor\n10. Declarar una variable is_married y asignarle un valor\n11. Declarar una variable is_true y asignarle un valor\n12. Declare una variable is_light_on y asígnele un valor\n13. Declarar múltiples variables en una línea\n\n### Ejercicios: Nivel 2\n\n1. Verifique el tipo de datos de todas sus variables usando la función incorporada type()\n1. Usando la función incorporada _len()_, encuentre la longitud de su nombre\n1. Compara la longitud de tu nombre y tu apellido\n1. Declarar 5 como num_one y 4 como num_two\n 1. Sume num_one y num_two y asigne el valor a un total variable\n 2. Reste num_two de num_one y asigne el valor a una variable diff\n 3. Multiplique num_two y num_one y asigne el valor a un producto variable\n 4. Divide num_one por num_two y asigna el valor a una división variable\n 5. Use la división de módulo para encontrar num_two dividido por num_one y asigne el valor a un residuo variable\n 6. Calcula num_one a la potencia de num_two y asigna el valor a una variable exp\n 7. Encuentra la división de piso de num_one por num_two y asigna el valor a una variable floor_division\n1. El radio de un círculo es de 30 metros.\n 1. Calcule el área de un círculo y asigne el valor a una variable con el nombre de _area_of_circle_\n 2. Calcule la circunferencia de un círculo y asigne el valor a una variable con el nombre de _circum_of_circle_\n 3. Tome el radio como entrada del usuario y calcule el área.\n1. Use la función de entrada integrada para obtener el nombre, el apellido, el país y la edad de un usuario y almacene el valor en sus nombres de variables correspondientes\n1. Ejecute la ayuda ('palabras clave') en el shell de Python o en su archivo para verificar las palabras o palabras clave reservadas de Python\n\n🎉 ¡FELICITACIONES! 🎉\n\n[<< Day 1](../readme.md) | [Day 3 >>](../03_Day_Operators/03_operators.md)\n"
},
{
"path": "Spanish/02_Day_Variables_builtin_functions/variables.py",
"content": "\n# Variables en Python\n\nfirst_name = 'Asabeneh'\nlast_name = 'Yetayeh'\ncountry = 'Finland'\ncity = 'Helsinki'\nage = 250\nis_married = True\nskills = ['HTML', 'CSS', 'JS', 'React', 'Python']\nperson_info = {\n 'firstname':'Asabeneh', \n 'lastname':'Yetayeh', \n 'country':'Finland',\n 'city':'Helsinki'\n }\n\n# Imprimir los valores almacenados en las variables\n\nprint('First name:', first_name)\nprint('First name length:', len(first_name))\nprint('Last name: ', last_name)\nprint('Last name length: ', len(last_name))\nprint('Country: ', country)\nprint('City: ', city)\nprint('Age: ', age)\nprint('Married: ', is_married)\nprint('Skills: ', skills)\nprint('Person information: ', person_info)\n\n# Declarar múltiples variables en una línea\n\nfirst_name, last_name, country, age, is_married = 'Asabeneh', 'Yetayeh', 'Helsink', 250, True\n\nprint(first_name, last_name, country, age, is_married)\nprint('First name:', first_name)\nprint('Last name: ', last_name)\nprint('Country: ', country)\nprint('Age: ', age)\nprint('Married: ', is_married)"
},
{
"path": "Spanish/02_variables_builtin_functions_sp.md",
"content": "
\n
30 días de Python: Día 2 - Variables y funciones integradas
\n\n[<< Día 1](./readme_sp.md) | [Día 3 >>](./03_operators_sp.md)\n\n\n\n_Lectura aproximada: 12 min_\n\n- [📘 Día 2](#-día-2)\n - [Funciones integradas](#funciones-integradas)\n - [Variables](#variables)\n - [Declarar varias variables en una línea](#declarar-varias-variables-en-una-línea)\n - [Tipos de datos](#tipos-de-datos)\n - [Conversión de tipos de datos](#conversión-de-tipos-de-datos)\n - [Números](#números)\n - [💻 Ejercicios - Día 2](#-ejercicios---día-2)\n - [Ejercicio: Nivel 1](#ejercicio-nivel-1)\n - [Ejercicio: Nivel 2](#ejercicio-nivel-2)\n\n# 📘 Día 2\n\n## Funciones integradas\n\nPython proporciona muchas funciones integradas. Las funciones integradas están disponibles a nivel global, lo que significa que puede usarlas sin importar o configurar nada. A continuación se muestran algunas de las funciones integradas más comunes de Python: _print()_, _len()_, _type()_, _int()_, _float()_, _str()_, _input()_, _list()_, _dict()_, _min()_, _max()_, _sum()_, _sorted()_, _open()_, _file()_, _help()_, _dir()_. En la tabla siguiente verá la lista completa de funciones integradas obtenida de la [documentación de Python](https://docs.python.org/3.9/library/functions.html).\n\n\n\nAbramos el intérprete interactivo de Python y comencemos a usar algunas de las funciones integradas más comunes.\n\n\n\nPractique más usando diferentes funciones integradas\n\n\n\nComo se muestra arriba, Python tiene palabras reservadas. No podemos usar palabras reservadas para declarar variables o funciones. Presentaremos las variables en la sección siguiente.\n\nConfío en que ahora esté familiarizado con las funciones integradas. Practiquemos más con ellas antes de continuar a la siguiente sección.\n\n\n\n## Variables\n\nLas variables almacenan datos en la memoria del ordenador. En muchos lenguajes de programación se recomienda usar nombres de variables mnemotécnicos. Un nombre mnemotécnico es un nombre de variable fácil de recordar y asociar. Una variable hace referencia a la dirección de memoria donde se almacena un dato.\n\nAl nombrar variables, no se permite empezar con un número, usar caracteres especiales ni guiones. Una variable puede tener un nombre corto (por ejemplo x, y, z), pero se recomienda encarecidamente usar nombres más descriptivos (nombre, apellido, edad, país).\n\nReglas para nombres de variables en Python\n\n- El nombre de la variable debe comenzar con una letra o un guion bajo\n- El nombre de la variable no puede comenzar con un número\n- El nombre de la variable sólo puede contener caracteres alfanuméricos y guiones bajos (A-z, 0-9 y _)\n- Los nombres de variables distinguen mayúsculas de minúsculas (firstname, Firstname, FirstName y FIRSTNAME son variables diferentes)\n\nA continuación algunos ejemplos de nombres válidos:\n\n```shell\nfirstname\nlastname\nage\ncountry\ncity\nfirst_name\nlast_name\ncapital_city\n\t_if # si queremos usar una palabra reservada como variable\nyear_2021\nyear2021\ncurrent_year_2021\nbirth_year\nnum1\nnum2\n```\n\nNombres de variables inválidos\n\n```shell\nfirst-name\nfirst@name\nfirst$name\nnum-1\n1num\n```\nUsaremos la convención de nombres estándar adoptada por muchos desarrolladores de Python. Los desarrolladores de Python usan la convención snake_case. Para variables que contienen varias palabras usamos guiones bajos entre las palabras (por ejemplo first_name, last_name, engine_rotation_speed). El siguiente ejemplo muestra la convención estándar: cuando el nombre de la variable contiene más de una palabra, se deben usar guiones bajos.\n\nCuando asignamos un valor a una variable, esto se llama declarar una variable. Por ejemplo, en el siguiente ejemplo mi nombre se asigna a la variable first_name. El signo igual es el operador de asignación. Asignar significa almacenar un dato en una variable. El signo igual en Python no es el mismo que en matemáticas.\n\n_Ejemplo:_\n\n```py\n# Variables en Python\nfirst_name = 'Asabeneh'\nlast_name = 'Yetayeh'\ncountry = 'Finland'\ncity = 'Helsinki'\nage = 250\nis_married = True\nskills = ['HTML', 'CSS', 'JS', 'React', 'Python']\nperson_info = {\n 'firstname':'Asabeneh',\n 'lastname':'Yetayeh',\n 'country':'Finland',\n 'city':'Helsinki'\n }\n```\n\nUsemos las funciones integradas _print()_ y _len()_. La función print puede aceptar un número ilimitado de argumentos. Un argumento es un valor que podemos pasar dentro de los paréntesis de la función; vea el ejemplo a continuación.\n\n**Ejemplo:**\n\n```py\nprint('Hello, World!') # The text Hello, World! is an argument\nprint('Hello',',', 'World','!') # it can take multiple arguments, four arguments have been passed\nprint(len('Hello, World!')) # it takes only one argument\n```\n\nImprimamos y calculemos la longitud de las variables declaradas arriba：\n\n\n**Ejemplo:**\n\n```py\n# Imprimir valores de las variables\n\nprint('First name:', first_name)\nprint('First name length:', len(first_name))\nprint('Last name: ', last_name)\nprint('Last name length: ', len(last_name))\nprint('Country: ', country)\nprint('City: ', city)\nprint('Age: ', age)\nprint('Married: ', is_married)\nprint('Skills: ', skills)\nprint('Person information: ', person_info)\n```\n\n### Declarar varias variables en una línea\n\nTambién se pueden declarar múltiples variables en la misma línea：\n\n**Ejemplo:**\n\n```py\nfirst_name, last_name, country, age, is_married = 'Asabeneh', 'Yetayeh', 'Helsink', 250, True\n\nprint(first_name, last_name, country, age, is_married)\nprint('First name:', first_name)\nprint('Last name: ', last_name)\nprint('Country: ', country)\nprint('Age: ', age)\nprint('Married: ', is_married)\n```\n\nUse la función integrada _input()_ para obtener entrada del usuario. Asignemos los datos ingresados por el usuario a las variables first_name y age.\n.\n**Ejemplo:**\n\n```py\nfirst_name = input('What is your name: ') \nage = input('How old are you? ')\n\nprint(first_name)\nprint(age)\n```\n\n## Tipos de datos\n\nHay varios tipos de datos en Python. Para identificar el tipo de un dato usamos la función integrada _type_. Le recomiendo dominar los distintos tipos de datos: en programación todo está relacionado con los tipos de datos. Ya introduje los tipos de datos al principio y los vuelvo a mencionar porque cada tema está relacionado con los tipos de datos. Estudiaremos cada tipo con más detalle en capítulos posteriores.\n\n## Conversión de tipos de datos\n\n- Comprobar el tipo de dato: Para comprobar el tipo de un dato/variable usamos la función _type_\n\n **Ejemplo:**\n\n```py\n# Diferentes tipos de datos en Python\n# Declaramos algunas variables con distintos tipos de datos\n\nfirst_name = 'Asabeneh' # str\nlast_name = 'Yetayeh' # str\ncountry = 'Finland' # str\ncity= 'Helsinki' # str\nage = 250 # int, no se preocupe, esta no es mi edad real :) \n\n# Printing out types\nprint(type('Asabeneh')) # str\nprint(type(first_name)) # str\nprint(type(10)) # int\nprint(type(3.14)) # float\nprint(type(1 + 1j)) # complex\nprint(type(True)) # bool\nprint(type([1, 2, 3, 4])) # list\nprint(type({'name':'Asabeneh','age':250, 'is_married':250})) # dict\nprint(type((1,2))) # tuple\nprint(type(zip([1,2],[3,4]))) # set\n```\n\n- Conversión de tipos: convertir un tipo de dato a otro. Usamos _int()_, _float()_, _str()_, _list_, _set_.\nCuando realizamos operaciones aritméticas, las cadenas que contienen números deben convertirse primero a int o float, de lo contrario se producirá un error. Si concatenamos un número y una cadena, hay que convertir primero el número a cadena. Veremos la concatenación en la sección de cadenas.\n\n\n **Ejemplo:**\n\n```py\n# De entero a float\nnum_int = 10\nprint('num_int',num_int) # 10\nnum_float = float(num_int)\nprint('num_float:', num_float) # 10.0\n\n# De float a entero\ngravity = 9.81\nprint(int(gravity)) # 9\n\n# De entero a cadena\nnum_int = 10\nprint(num_int) # 10\nnum_str = str(num_int)\nprint(num_str) # '10'\n\n# De cadena a entero o float\nnum_str = '10.6'\nprint('num_int', int(num_str)) # 10\nprint('num_float', float(num_str)) # 10.6\n\n# De cadena a lista\nfirst_name = 'Asabeneh'\nprint(first_name) # 'Asabeneh'\nfirst_name_to_list = list(first_name)\nprint(first_name_to_list) # ['A', 's', 'a', 'b', 'e', 'n', 'e', 'h']\n```\n\n## Números\n\nDiferentes tipos numéricos en Python\n\n- Integer: números enteros (negativos, 0 y positivos)\n Ejemplo:\n ... -3, -2, -1, 0, 1, 2, 3 ...\n- Float: números de punto flotante\n Ejemplo\n ... -3.5, -2.25, -1.0, 0.0, 1.1, 2.2, 3.5 ...\n- Complex: números complejos\n Ejemplo\n 1 + j, 2 + 4j, 1 - 1j\n\n🌕 ¡Excelente! Acabas de completar el desafío del Día 2, estás un paso más cerca del éxito. Ahora realiza algunos ejercicios para ejercitar tu mente y tus habilidades.\n\n\n## 💻 Ejercicios - Día 2\n\n### Ejercicio: Nivel 1\n\n1. Crea una carpeta `day_2` dentro de la carpeta `30DaysOfPython`. Dentro de esa carpeta crea un archivo `variables.py`\n2. Añade un comentario: 'Día 2: 30 Days of Python programming'\n3. Declara una variable `first_name` y asígnale un valor\n4. Declara una variable `last_name` y asígnale un valor\n5. Declara una variable `full_name` y asígnale un valor\n6. Declara una variable `country` y asígnale un valor\n7. Declara una variable `city` y asígnale un valor\n8. Declara una variable `age` y asígnale un valor\n9. Declara una variable `year` y asígnale un valor\n10. Declara una variable `is_married` y asígnale un valor\n11. Declara una variable `is_true` y asígnale un valor\n12. Declara una variable `is_light_on` y asígnale un valor\n13. Declara múltiples variables en una sola línea\n\n### Ejercicio: Nivel 2\n\n1. Usa la función integrada _type()_ para comprobar el tipo de las variables que declaraste\n1. Usa la función _len()_ para calcular la longitud de la variable `first_name`\n1. Compara la longitud de las variables `first_name` y `last_name`\n1. Declara las variables `num_one = 5` y `num_two = 4`\n 1. Suma `num_one` y `num_two` y asigna el resultado a la variable `total`\n 2. Resta `num_two` de `num_one` y asigna el resultado a la variable `diff`\n 3. Multiplica `num_one` y `num_two` y asigna el resultado a la variable `product`\n 4. Divide `num_one` entre `num_two` y asigna el resultado a la variable `division`\n 5. Usa la operación módulo para obtener el resto de `num_two` dividido por `num_one` y asígnalo a `remainder`\n 6. Calcula `num_one` elevado a `num_two` y asigna el valor a `exp`\n 7. Calcula la división entera de `num_one` entre `num_two` (operación de floor division) y asigna el resultado a `floor_division`\n1. El círculo tiene un radio de 30 metros.\n 1. Calcula el área del círculo y asígnala a la variable `_area_of_circle_`\n 2. Calcula la circunferencia del círculo y asígnala a la variable `_circum_of_circle_`\n 3. Pide el radio al usuario y calcula el área.\n1. Usa la función integrada `input()` para obtener nombre, apellido, país y edad del usuario y almacena los valores en las variables correspondientes\n1. Ejecuta `help('keywords')` en el intérprete de Python o en un archivo para comprobar las palabras reservadas (keywords) de Python\n\n\n\n🎉 ¡Felicidades! 🎉\n\n[<< Día 1](./readme_sp.md) | [Día 3 >>](./03_operators_sp.md)"
},
{
"path": "Spanish/03_Day_Operators/03_operators.md",
"content": "
\n\n[<< Dia 2](../02_Day_Variables_builtin_functions/02_variables_builtin_functions.md) | [Dia 4 >>](../04_Day_Strings/04_strings.md)\n\n\n\n- [📘 Día 3](#📘-día-3)\n - [Booleano](#booleano)\n - [Operadores](#operadores)\n - [Operadores de asignación](#operadores-de-asignación)\n - [Operadores aritméticos:](#operadores-aritméticos)\n - [Operadores de comparación](#operadores-de-comparación)\n - [Operadores lógicos](#operadores-lógicos)\n - [💻 Ejercicios - Día 3](#💻-ejercicios---día-3)\n\n# 📘 Día 3\n\n## Booleano\n\nUn tipo de datos booleano representa uno de los dos valores: _Verdadero_ o _Falso_. El uso de estos tipos de datos quedará claro una vez que comencemos a usar el operador de comparación. La primera letra **T** para Verdadero y **F** para Falso debe ser en mayúscula a diferencia de JavaScript.\n**Ejemplo: valores booleanos**\n\n```py\nprint(True)\nprint(False)\n```\n\n## Operadores\n\nPython language supports several types of operators. In this section, we will focus on few of them.\n\n### Operadores de asignación\n\nLos operadores de asignación se utilizan para asignar valores a las variables. Tomemos = como ejemplo. El signo igual en matemáticas muestra que dos valores son iguales, sin embargo, en Python significa que estamos almacenando un valor en una determinada variable y lo llamamos asignación o asignación de valor a una variable. La siguiente tabla muestra los diferentes tipos de operadores de asignación de Python, tomados de [w3school](https://www.w3schools.com/python/python_operators.asp).\n\n\n\n### Operadores aritméticos:\n\n- Suma (+): a + b\n- Resta(-): a - b\n- Multiplicación(*): a * b\n- División(/): a/b\n- Módulo(%): a % b\n- División de piso(//): a // b\n- Exponenciación(**): a ** b\n\n\n\n**Ejemplo: Enteros**\n\n```py\n# Operaciones aritméticas en Python\n# enteros\n\nprint('Addition: ', 1 + 2) # 3\nprint('Subtraction: ', 2 - 1) # 1\nprint('Multiplication: ', 2 * 3) # 6\nprint ('Division: ', 4 / 2) # 2.0 La división en Python da un número flotante\nprint('Division: ', 6 / 2) # 3.0 \nprint('Division: ', 7 / 2) # 3.5\nprint('Division without the remainder: ', 7 // 2) # 3, da sin el número flotante o sin el resto\nprint ('Division without the remainder: ',7 // 3) # 2\nprint('Modulus: ', 3 % 2) # 1, da el resto\nprint('Exponentiation: ', 2 ** 3) # 9 significa 2 * 2 * 2\n```\n\n**Ejemplo: Floats**\n\n```py\n# Números flotantes\nprint('Floating Point Number, PI', 3.14)\nprint('Floating Point Number, gravity', 9.81)\n```\n\n**Ejemplo: Números complex**\n\n```py\n# Números complejos\nprint('Complex number: ', 1 + 1j)\nprint('Multiplying complex numbers: ',(1 + 1j) * (1 - 1j))\n```\n\nDeclaremos una variable y asignemos un tipo de dato numérico. Voy a usar una variable de un solo carácter, pero recuerde que no desarrolle el hábito de declarar este tipo de variables. Los nombres de las variables deben ser siempre mnemotécnicos.\n\n**Ejemplo:**\n\n```python\n# Declarar la variable en la parte superior primero\n\na = 3 # a es un nombre de variable y 3 es un tipo de dato entero\nb = 2 # b es un nombre de variable y 3 es un tipo de dato entero\n\n# Operaciones aritméticas y asignación del resultado a una variable\ntotal = a + b\ndiff = a - b\nproduct = a * b\ndivision = a / b\nremainder = a % b\nfloor_division = a // b\nexponential = a ** b\n\n# Debería haber usado sum en lugar de total, pero sum es una función integrada; trate de evitar anular las funciones integradas\nprint(total) # si no etiqueta su impresión con alguna cadena, nunca sabrá de dónde viene el resultado\nprint('a + b = ', total)\nprint('a - b = ', diff)\nprint('a * b = ', product)\nprint('a / b = ', division)\nprint('a % b = ', remainder)\nprint('a // b = ', floor_division)\nprint('a ** b = ', exponentiation)\n```\n\n**Ejemplo:**\n\n```py\nprint('== Addition, Subtraction, Multiplication, Division, Modulus ==')\n\n# Declarar valores y organizarlos juntos\nnum_one = 3\nnum_two = 4\n\n# Operaciones aritmeticas\ntotal = num_one + num_two\ndiff = num_two - num_one\nproduct = num_one * num_two\ndiv = num_two / num_one\nremainder = num_two % num_one\n\n# Imprimiendo valores con etiqueta\nprint('total: ', total)\nprint('difference: ', diff)\nprint('product: ', product)\nprint('division: ', div)\nprint('remainder: ', remainder)\n```\n\nEmpecemos a conectar los puntos y empecemos a hacer uso de lo que ya sabemos para calcular (área, volumen, densidad, peso, perímetro, distancia, fuerza).\n\n**Ejemplo:**\n```py\n# Cálculo del área de un círculo\nradius = 10 # radio de un circulo\narea_of_circle = 3.14 * radius ** 2 # dos signo * significa exponente o potencia\nprint('Area of a circle:', area_of_circle)\n\n# Calcular el área de un rectángulo\nlength = 10\nwidth = 20\narea_of_rectangle = length * width\nprint('Area of rectangle:', area_of_rectangle)\n\n# Calcular el peso de un objeto\nmass = 75\ngravity = 9.81\nweight = mass * gravity\nprint(weight, 'N') # Agregando unidad al peso\n\n# Calcular la densidad de un líquido\nmass = 75 # en kg\nvolume = 0.075 # en metros cúbicos\ndensity = mass / volume # 1000 Kg/m^3\n\n```\n\n### Operadores de comparación\n\nEn programación comparamos valores, usamos operadores de comparación para comparar dos valores. Comprobamos si un valor es mayor o menor o igual a otro valor. La siguiente tabla muestra los operadores de comparación de Python que se tomaron de [w3shool](https://www.w3schools.com/python/python_operators.asp).\n\n\n**Ejemplo: Operadores de comparación**\n\n```py\nprint(3 > 2) # True, porque 3 es mayor que 2\nprint(3 >= 2) # True, porque 3 es mayor que 2\nprint(3 < 2) # False, porque 3 es mayor que 2\nprint(2 < 3) # True, porque 2 es menor que 3\nprint(2 <= 3) # True, porque 2 es menor que 3\nprint(3 == 2) # False, porque 3 no es igual a 2\nprint(3 != 2) # True, porque 3 no es igual a 2\nprint(len('mango') == len('avocado')) # False\nprint(len('mango') != len('avocado')) # True\nprint(len('mango') < len('avocado')) # True\nprint(len('milk') != len('meat')) # False\nprint(len('milk') == len('meat')) # True\nprint(len('tomato') == len('potato')) # True\nprint(len('python') > len('dragon')) # False\n\n\n# Comparar algo da un True o False\n\nprint('True == True: ', True == True)\nprint('True == False: ', True == False)\nprint('False == False:', False == False)\n```\n\nAdemás del operador de comparación anterior, Python usa:\n\n- _is_: Devuelve True si ambas variables son el mismo objeto (x es y)\n- _is not_: Devuelve True si ambas variables no son el mismo objeto (x no es y)\n- _in_: Devuelve True si la lista consultada contiene un elemento determinado (x en y)\n- _not in_: Devuelve True si la lista consultada no tiene un elemento determinado (x en y)\n\n```py\nprint('1 is 1', 1 is 1) # True - porque los valores de los datos son los mismos\nprint('1 is not 2', 1 is not 2) # True - porque 1 no es 2\nprint('A in Asabeneh', 'A' in 'Asabeneh') # True - A encontrado en la cadena\nprint('B in Asabeneh', 'B' in 'Asabeneh') # False - no hay b mayúscula\nprint('coding' in 'coding for all') # True - porque 'coding for all' tiene la palabra 'coding'\nprint('a in an:', 'a' in 'an') # True\nprint('4 is 2 ** 2:', 4 is 2 ** 2) # True\n```\n\n### Operadores lógicos\n\nA diferencia de otros lenguajes de programación, Python utiliza las palabras clave _and_, _or_ y _not_ para los operadores lógicos. Los operadores lógicos se utilizan para combinar sentencias condicionales:\n\n\n\n```py\nprint(3 > 2 and 4 > 3) # True - porque ambas afirmaciones son verdaderas\nprint(3 > 2 and 4 < 3) # False - porque la segunda afirmación es falsa\nprint(3 < 2 and 4 < 3) # False - porque ambas afirmaciones son falsas\nprint('True and True: ', True and True)\nprint(3 > 2 or 4 > 3) # True - porque ambas afirmaciones son verdaderas\nprint(3 > 2 or 4 < 3) # True - porque una de las afirmaciones es verdadera\nprint(3 < 2 or 4 < 3) # False - porque ambas afirmaciones son falsas\nprint('True or False:', True or False)\nprint(not 3 > 2) # False - porque 3 > 2 es verdadero, entonces no verdadero da falso\nprint(not True) # False - Negación, el operador not devuelve verdadero a falso\nprint(not False) # True\nprint(not not True) # True\nprint(not not False) # False\n\n```\n\n🌕 Tienes una energía ilimitada. Acaba de completar los desafíos del día 3 y está tres pasos por delante en su camino hacia la grandeza. Ahora haz algunos ejercicios para tu cerebro y tus músculos.\n\n## 💻 Ejercicios - Día 3\n\n1. Declara tu edad como variable entera\n2. Declara tu altura como una variable flotante\n3. Declarar una variable que almacene un número complejo\n4. Escriba un script que solicite al usuario que ingrese la base y la altura del triángulo y calcule el área de este triángulo (área = 0,5 x b x h).\n\n```py\n Enter base: 20\n Enter height: 10\n The area of the triangle is 100\n```\n\n5. Escriba un script que solicite al usuario que ingrese el lado a, el lado b y el lado c del triángulo. Calcula el perímetro del triángulo (perímetro = a + b + c).\n\n```py\nEnter side a: 5\nEnter side b: 4\nEnter side c: 3\nThe perimeter of the triangle is 12\n```\n\n6. Obtenga la longitud y el ancho de un rectángulo usando el indicador. Calcula su área (área = largo x ancho) y perímetro (perímetro = 2 x (largo + ancho))\n7. Obtenga el radio de un círculo usando el aviso. Calcula el área (área = pi x r x r) y la circunferencia (c = 2 x pi x r) donde pi = 3,14.\n8. Calcular la pendiente, la intersección x y la intersección y de y = 2x -2\n9. La pendiente es (m = y2-y1/x2-x1). Encuentre la pendiente y la [distancia euclidiana](https://en.wikipedia.org/wiki/Euclidean_distance#:~:text=In%20mathematics%2C%20the%20Euclidean%20distance,being%20called%20the%20Pythagorean%20distance.) entre el punto (2, 2) y el punto (6,10)\n10. Compara las pendientes en las tareas 8 y 9.\n11. Calcula el valor de y (y = x^2 + 6x + 9). Trate de usar diferentes valores de x y descubra en qué valor de x y será 0.\n12. Encuentra la longitud de 'python' y 'dragon' y haz una declaración de comparación falsa.\n13. Use el operador _and_ para verificar si 'on' se encuentra tanto en 'python' como en 'dragon'\n14. _Espero que este curso no esté lleno de jerga_. Use el operador _in_ para verificar si _jerga_ está en la oración.\n15. No hay 'on' ni en dragón ni en pitón\n16. Encuentre la longitud del texto _python_ y convierta el valor en flotante y conviértalo en cadena\n17. Los números pares son divisibles por 2 y el resto es cero. ¿Cómo verifica si un número es par o no usando python?\n18. Verifique si la división de piso de 7 por 3 es igual al valor int convertido de 2.7.\n19. Comprueba si el tipo de '10' es igual al tipo de 10\n20. Comprueba si int('9.8') es igual a 10\n21. Escriba un script que solicite al usuario que ingrese las horas y la tarifa por hora. ¿Calcular el salario de la persona?\n\n```py\nEnter hours: 40\nEnter rate per hour: 28\nYour weekly earning is 1120\n```\n\n22. Escriba un script que le solicite al usuario que ingrese el número de años. Calcula el número de segundos que una persona puede vivir. Suponga que una persona puede vivir cien años.\n\n```py\nEnter number of years you have lived: 100\nYou have lived for 3153600000 seconds.\n```\n\n23. Escriba un script de Python que muestre la siguiente tabla\n\n```py\n1 1 1 1 1\n2 1 2 4 8\n3 1 3 9 27\n4 1 4 16 64\n5 1 5 25 125\n```\n\n🎉 ¡FELICITACIONES! 🎉\n\n[<< Day 2](../02_Day_Variables_builtin_functions/02_variables_builtin_functions.md) | [Day 4 >>](../04_Day_Strings/04_strings.md)\n"
},
{
"path": "Spanish/03_Day_Operators/day-3.py",
"content": "# Operaciones aritméticas en Python\n# Integers\n\nprint('Addition: ', 1 + 2)\nprint('Subtraction: ', 2 - 1)\nprint('Multiplication: ', 2 * 3)\nprint ('Division: ', 4 / 2) # La división en python da un número flotante\nprint('Division: ', 6 / 2)\nprint('Division: ', 7 / 2)\nprint('Division without the remainder: ', 7 // 2) # da sin el número flotante o sin el resto\nprint('Modulus: ', 3 % 2) # Da el resto\nprint ('Division without the remainder: ', 7 // 3)\nprint('Exponential: ', 3 ** 2) # significa 3 * 3\n\n# Números Floating \nprint('Floating Number,PI', 3.14)\nprint('Floating Number, gravity', 9.81)\n\n# Números Complex\nprint('Complex number: ', 1 + 1j)\nprint('Multiplying complex number: ',(1 + 1j) * (1-1j))\n\n# Declarar la variable en la parte superior primero\n\na = 3 # a es un nombre de variable y 3 es un tipo de dato entero\nb = 2 # b es un nombre de variable y 3 es un tipo de dato entero\n\n# Operaciones aritméticas y asignación del resultado a una variable\ntotal = a + b\ndiff = a - b\nproduct = a * b\ndivision = a / b\nremainder = a % b\nfloor_division = a // b\nexponential = a ** b\n\n# Debería haber usado sum en lugar de total, pero sum es una función integrada. Trate de evitar anular las funciones integradas.\nprint(total) # si no etiqueta su impresión con alguna cadena, nunca sabrá de dónde viene el resultado\nprint('a + b = ', total)\nprint('a - b = ', diff)\nprint('a * b = ', product)\nprint('a / b = ', division)\nprint('a % b = ', remainder)\nprint('a // b = ', floor_division)\nprint('a ** b = ', exponential)\n\n# Declarar valores y organizarlos juntos\nnum_one = 3\nnum_two = 4\n\n# Operaciones aritmeticas\ntotal = num_one + num_two\ndiff = num_two - num_one\nproduct = num_one * num_two\ndiv = num_two / num_two\nremainder = num_two % num_one\n\n# Imprimiendo valores con etiqueta\nprint('total: ', total)\nprint('difference: ', diff)\nprint('product: ', product)\nprint('division: ', div)\nprint('remainder: ', remainder)\n\n\n# Cálculo del área de un círculo\nradius = 10 # radio de un circulo\narea_of_circle = 3.14 * radius ** 2 # dos * signo significa exponente o potencia\nprint('Area of a circle:', area_of_circle)\n\n# Calcular el área de un rectángulo\nlength = 10\nwidth = 20\narea_of_rectangle = length * width\nprint('Area of rectangle:', area_of_rectangle)\n\n# Calcular el peso de un objeto\nmass = 75\ngravity = 9.81\nweight = mass * gravity\nprint(weight, 'N')\n\nprint(3 > 2) # True, porque 3 es mayor que 2\nprint(3 >= 2) # True, porque 3 es mayor que 2\nprint(3 < 2) # False, porque 3 es mayor que 2\nprint(2 < 3) # True, porque 2 es menor que 3\nprint(2 <= 3) # True, porque 2 es menor que 3\nprint(3 == 2) # False, porque 3 no es igual a 2\nprint(3 != 2) # True, porque 3 no es igual a 2\nprint(len('mango') == len('avocado')) # False\nprint(len('mango') != len('avocado')) # True\nprint(len('mango') < len('avocado')) # True\nprint(len('milk') != len('meat')) # False\nprint(len('milk') == len('meat')) # True\nprint(len('tomato') == len('potato')) # True\nprint(len('python') > len('dragon')) # False\n\n# Comparación booleana\nprint('True == True: ', True == True)\nprint('True == False: ', True == False)\nprint('False == False:', False == False)\nprint('True and True: ', True and True)\nprint('True or False:', True or False)\n\n# Comparación de otra forma\nprint('1 is 1', 1 is 1) # True - porque los valores de los datos son los mismos\nprint('1 is not 2', 1 is not 2) # True - porque 1 no es 2\nprint('A in Asabeneh', 'A' in 'Asabeneh') # True - A encontrado en la cadena\nprint('B in Asabeneh', 'B' in 'Asabeneh') # False - no hay b mayúscula\nprint('coding' in 'coding for all') # True - porque codificar para todos tiene la palabra codificar\nprint('a in an:', 'a' in 'an') # True\nprint('4 is 2 ** 2:', 4 is 2 ** 2) # True\n\nprint(3 > 2 and 4 > 3) # True - porque ambas afirmaciones son verdaderas\nprint(3 > 2 and 4 < 3) # False - porque la segunda afirmación es falsa\nprint(3 < 2 and 4 < 3) # False - porque ambas afirmaciones son falsas\nprint(3 > 2 or 4 > 3) # True - porque ambas afirmaciones son verdaderas\nprint(3 > 2 or 4 < 3) # True - porque uno de los enunciados es verdadero\nprint(3 < 2 or 4 < 3) # False - porque ambas afirmaciones son falsas\nprint(not 3 > 2) # False - porque 3 > 2 es verdadero, entonces not verdadero da falso\nprint(not True) # False - Negación, el operador not devuelve verdadero a falso\nprint(not False) # True\nprint(not not True) # True\nprint(not not False) # False"
},
{
"path": "Spanish/03_operators_sp.md",
"content": "
\n\n[<< Día 2](./02_variables_builtin_functions_sp.md) | [Día 4 >>](./04_strings_sp.md)\n\n\n\n_Lectura aproximada: 12 min_\n- [📘 Día 3](#-día-3)\n - [Boolean](#boolean)\n - [Operadores](#operadores)\n - [Operadores de asignación](#operadores-de-asignación)\n - [Operadores aritméticos](#operadores-aritméticos)\n - [Operadores de comparación](#operadores-de-comparación)\n - [Operadores lógicos](#operadores-lógicos)\n - [💻 Ejercicios - Día 3](#-ejercicios---día-3)\n\n# 📘 Día 3\n\n## Boolean\n\nEl tipo booleano representa uno de dos valores: _True_ o _False_. Cuando comencemos a usar operadores de comparación su uso quedará claro. La primera letra **T** representa True y **F** representa False; a diferencia de JavaScript, en Python las palabras booleanas deben escribirse con la primera letra en mayúscula.\n\n**Ejemplo: valores booleanos**\n\n```py\nprint(True)\nprint(False)\n```\n\n## Operadores\n\nPython soporta varios tipos de operadores. En esta sección nos centraremos en algunos de ellos.\n\n### Operadores de asignación\n\nLos operadores de asignación se usan para asignar valores a las variables. Tomemos = como ejemplo: en matemáticas el signo igual indica que dos valores son iguales, pero en Python indica que estamos almacenando un valor en una variable; esto se llama asignación. La tabla siguiente muestra los diferentes operadores de asignación en Python (tomada de [w3schools](https://www.w3schools.com/python/python_operators.asp)).\n\n\n\n### Operadores aritméticos:\n\n- Suma (+): a + b\n- Resta (-): a - b\n- Multiplicación (*): a * b\n- División (/): a / b\n- Módulo (%): a % b\n- División entera (//): a // b\n- Exponenciación (**): a ** b\n\n\n\n**Ejemplo: enteros**\n\n```py\n# Operadores aritméticos en Python\n# Enteros\n\nprint('Addition: ', 1 + 2) # 3\nprint('Subtraction: ', 2 - 1) # 1\nprint('Multiplication: ', 2 * 3) # 6\nprint ('Division: ', 4 / 2) # 2.0 la división en Python devuelve float\nprint('Division: ', 6 / 2) # 3.0 \nprint('Division: ', 7 / 2) # 3.5\nprint('Division without the remainder: ', 7 // 2) # 3, devuelve la parte entera del cociente\nprint ('Division without the remainder: ',7 // 3) # 2\nprint('Modulus: ', 3 % 2) # 1, devuelve el resto\nprint('Exponentiation: ', 2 ** 3) # 8 representa 2 * 2 * 2\n```\n\n**Ejemplo: flotantes**\n\n```py\n# Flotantes\nprint('Floating Point Number, PI', 3.14)\nprint('Floating Point Number, gravity', 9.81)\n```\n\n**Ejemplo: números complejos**\n\n```py\n# Números complejos\nprint('Complex number: ', 1 + 1j)\nprint('Multiplying complex numbers: ',(1 + 1j) * (1 - 1j))\n```\n\nDeclararemos una variable y le asignaremos un valor numérico. En el ejemplo uso nombres de una sola letra, pero no acostumbres a nombrar variables así; los nombres deben ser siempre fáciles de recordar.\n\n**Ejemplo:**\n\n```python\n# Primero declaramos las variables\n\na = 3 # a es un nombre de variable, 3 es un valor entero\nb = 2 # b es un nombre de variable, 2 es un valor entero\n\n# Realizamos operaciones aritméticas y asignamos los resultados a variables\ntotal = a + b\ndiff = a - b\nproduct = a * b\ndivision = a / b\nremainder = a % b\nfloor_division = a // b\nexponential = a ** b\n\n# Deberíamos usar sum en lugar de total, pero sum es una función integrada — evita sobrescribirla\nprint(total) # Si no imprimimos etiquetas, no sabremos qué representa cada valor\nprint('a + b = ', total)\nprint('a - b = ', diff)\nprint('a * b = ', product)\nprint('a / b = ', division)\nprint('a % b = ', remainder)\nprint('a // b = ', floor_division)\nprint('a ** b = ', exponentiation)\n```\n\n**Ejemplo:**\n\n```py\nprint('== Addition, Subtraction, Multiplication, Division, Modulus ==')\n\n# Declaramos las variables\nnum_one = 3\nnum_two = 4\n\n# Operaciones aritméticas\ntotal = num_one + num_two\ndiff = num_two - num_one\nproduct = num_one * num_two\ndiv = num_two / num_one\nremainder = num_two % num_one\n\n# Imprimimos con etiquetas\nprint('total: ', total)\nprint('difference: ', diff)\nprint('product: ', product)\nprint('division: ', div)\nprint('remainder: ', remainder)\n```\n\nComencemos a usar números con decimales y pongamos en práctica lo aprendido para calcular áreas, volúmenes, densidades, pesos, perímetros, distancias y fuerzas.\n\n**Ejemplo:**\n\n```py\n# Calcular el área de un círculo\nradius = 10 # radio del círculo\narea_of_circle = 3.14 * radius ** 2 # dos * indican exponente o potencia\nprint('Area of a circle:', area_of_circle)\n\n# Calcular el área del rectángulo\nlength = 10\nwidth = 20\narea_of_rectangle = length * width\nprint('Area of rectangle:', area_of_rectangle)\n\n# Calcular el peso de un objeto\nmass = 75\ngravity = 9.81\nweight = mass * gravity\nprint(weight, 'N') # añadimos la unidad para la fuerza\n\n# Calcular la densidad de un líquido\nmass = 75 # unidad: Kg\nvolume = 0.075 # unidad: m³\ndensity = mass / volume # 1000 Kg/m³\n\n```\n\n### Operadores de comparación\n\nEn programación usamos operadores de comparación para comparar dos valores. Comprobamos si un valor es mayor, menor o igual a otro. La tabla siguiente muestra los operadores de comparación en Python (tomada de [w3schools](https://www.w3schools.com/python/python_operators.asp)).\n\n\n**Ejemplo: operadores de comparación**\n\n```py\nprint(3 > 2) # True, porque 3 es mayor que 2\nprint(3 >= 2) # True, porque 3 es mayor o igual que 2\nprint(3 < 2) # False, porque 3 no es menor que 2\nprint(2 < 3) # True, porque 2 es menor que 3\nprint(2 <= 3) # True, porque 2 es menor o igual que 3\nprint(3 == 2) # False, porque 3 no es igual a 2\nprint(3 != 2) # True, porque 3 no es igual a 2\nprint(len('mango') == len('avocado')) # False\nprint(len('mango') != len('avocado')) # True\nprint(len('mango') < len('avocado')) # True\nprint(len('milk') != len('meat')) # False\nprint(len('milk') == len('meat')) # True\nprint(len('tomato') == len('potato')) # True\nprint(len('python') > len('dragon')) # False\n\n\n# Las comparaciones devuelven True o False\n\nprint('True == True: ', True == True)\nprint('True == False: ', True == False)\nprint('False == False:', False == False)\n```\n\nAdemás de los operadores de comparación anteriores, Python también utiliza：\n\n- _is_: devuelve True si los objetos son idénticos (x is y)\n- _is not_: devuelve True si los objetos no son idénticos (x is not y)\n- _in_: devuelve True si un elemento está en una secuencia (x in y)\n- _not in_: devuelve True si un elemento no está en una secuencia (x not in y)\n\n```py\nprint('1 is 1', 1 is 1) # True - porque los objetos son idénticos\nprint('1 is not 2', 1 is not 2) # True - porque los objetos no son idénticos\nprint('A in Asabeneh', 'A' in 'Asabeneh') # True - la cadena contiene 'A'\nprint('B in Asabeneh', 'B' in 'Asabeneh') # False - no hay 'B' mayúscula\nprint('coding' in 'coding for all') # True - 'coding' está en 'coding for all'\nprint('a in an:', 'a' in 'an') # True\nprint('4 is 2 ** 2:', 4 is 2 ** 2) # True\n```\n\n### Operadores lógicos\n\nA diferencia de otros lenguajes de programación, Python usa las palabras clave _and_, _or_ y _not_ como operadores lógicos. Los operadores lógicos se utilizan para combinar expresiones condicionales:\n\n\n\n```py\nprint(3 > 2 and 4 > 3) # True - porque ambas expresiones son True\nprint(3 > 2 and 4 < 3) # False - porque una de las expresiones es False\nprint(3 < 2 and 4 < 3) # False - porque ambas expresiones son False\nprint('True and True: ', True and True)\nprint(3 > 2 or 4 > 3) # True - porque una o ambas expresiones son True\nprint(3 > 2 or 4 < 3) # True - porque una de las expresiones es True\nprint(3 < 2 or 4 < 3) # False - porque ambas expresiones son False\nprint('True or False:', True or False)\nprint(not 3 > 2) # False - 3 > 2 es True, not True es False\nprint(not True) # False - not convierte True en False\nprint(not False) # True\nprint(not not True) # True\nprint(not not False) # False\n\n```\n\n🌕 ¡Con energía! Acabas de completar el desafío del Día 3 y has avanzado tres pasos en el camino hacia el dominio. Ahora realiza algunos ejercicios para poner a prueba tu mente y tus habilidades.\n\n\n## 💻 Ejercicios - Día 3\n\n1. Declara una variable entera que represente tu edad\n2. Declara una variable float que represente tu altura\n3. Declara una variable compleja\n4. Escribe un script que pida al usuario la base y la altura de un triángulo y calcule su área (Área = 0,5 x b x h).\n\n```py\n Entrada base: 20\n Entrada altura: 10\n El área del triángulo es 100\n```\n\n5. Escribe un script que pida al usuario los lados a, b y c de un triángulo y calcule su perímetro (Perímetro = a + b + c).\n\n```py\n Entrada lado a: 5\n Entrada lado b: 4\n Entrada lado c: 3\n El perímetro del triángulo es 12\n```\n6. Pide al usuario la longitud y la anchura de un rectángulo. Calcula su área (Área = largo x ancho) y su perímetro (Perímetro = 2 x (largo + ancho)).\n7. Pide al usuario el radio de un círculo. Calcula su área (Área = pi x r x r) y su circunferencia (Circunferencia = 2 x pi x r), con pi = 3.14.\n8. Calcula la pendiente, la intersección en x y la intersección en y de y = 2x - 2.\n9. La pendiente se calcula como (m = (y2 - y1) / (x2 - x1)). Encuentra la pendiente y la distancia euclídea entre los puntos (2, 2) y (6, 10).\n10. Compara las pendientes obtenidas en los ejercicios 8 y 9.\n11. Calcula el valor de y para y = x^2 + 6x + 9. Prueba con distintos valores de x y encuentra cuándo y es 0.\n12. Encuentra la longitud de 'python' y 'dragon', y realiza una comparación ficticia.\n13. Usa el operador _and_ para comprobar si tanto 'python' como 'dragon' contienen 'on'.\n14. En la oración _I hope this course is not full of jargon_, usa el operador _in_ para comprobar si contiene la palabra _jargon_.\n15. Comprueba que ni 'dragon' ni 'python' contienen 'on'.\n16. Encuentra la longitud de 'python', conviértela a float y luego a string.\n17. Los números pares son divisibles por 2 con resto 0. ¿Cómo comprobar en Python si un número es par o impar?\n18. Comprueba si la división entera de 7 entre 3 es igual al valor entero de 2.7.\n19. Comprueba si el tipo de '10' es igual al tipo de 10.\n20. Comprueba si int('9.8') es igual a 10.\n21. Escribe un script que solicite las horas trabajadas y la tarifa por hora al usuario y calcule el salario.\n\n```py\nIntroduce horas trabajadas: 40\nIntroduce tarifa por hora: 28\nTu salario semanal es 1120\n```\n\n\n22. Escribe un script que pida al usuario los años vividos y calcule cuántos segundos ha vivido una persona (supongamos que puede vivir 100 años).\n\n```py\nIntroduce cuántos años has vivido: 100\nHas vivido 3153600000 segundos.\n```\n\n23. Escribe un script en Python que muestre la siguiente tabla\n\n\n```py\n1 1 1 1 1\n2 1 2 4 8\n3 1 3 9 27\n4 1 4 16 64\n5 1 5 25 125\n```\n\n🎉 ¡Felicidades! 🎉\n\n[<< Día 2](./02_variables_builtin_functions_sp.md) | [Día 4 >>](./04_strings_sp.md)\n"
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"path": "Spanish/04_strings_sp.md",
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\n\n[<< Día 3](./03_operators_sp.md) | [Día 5 >>](./05_lists_sp.md)\n\n\n\n_Lectura aproximada: 20 min_\n\n- [Día 4](#día-4)\n - [Cadenas](#cadenas)\n - [Crear cadenas](#crear-cadenas)\n - [Concatenación de cadenas](#concatenación-de-cadenas)\n - [Secuencias de escape en cadenas](#secuencias-de-escape-en-cadenas)\n - [Formateo de cadenas](#formateo-de-cadenas)\n - [Formateo clásico (% operador)](#formateo-clásico--operador)\n - [Formateo moderno (str.format)](#formateo-moderno-strformat)\n - [Interpolación / f-Strings (Python 3.6+)](#interpolación--f-strings-python-36)\n - [Las cadenas en Python son secuencias de caracteres](#las-cadenas-en-python-son-secuencias-de-caracteres)\n - [Desempaquetar caracteres](#desempaquetar-caracteres)\n - [Obtener caracteres por índice](#obtener-caracteres-por-índice)\n - [Slicing de cadenas](#slicing-de-cadenas)\n - [Invertir cadenas](#invertir-cadenas)\n - [Saltar caracteres al hacer slicing](#saltar-caracteres-al-hacer-slicing)\n - [Métodos de cadenas](#métodos-de-cadenas)\n - [💻 Ejercicios - Día 4](#-ejercicios---día-4)\n\n# Día 4\n\n## Cadenas\n\nEl texto es un tipo de dato de cadena. Cualquier dato escrito como texto es una cadena. Todo lo que esté entre comillas simples, dobles o triples se considera una cadena. Existen muchos métodos y funciones integradas para trabajar con cadenas. Use la función `len()` para obtener la longitud de una cadena.\n\n### Crear cadenas\n\n```py\nletter = 'P' # Una cadena puede ser un carácter o un texto\nprint(letter) # P\nprint(len(letter)) # 1\ngreeting = 'Hello, World!' # Las cadenas se crean con comillas simples o dobles, \"Hello, World!\"\nprint(greeting) # Hello, World!\nprint(len(greeting)) # 13\nsentence = \"I hope you are enjoying 30 days of Python Challenge\"\nprint(sentence)\n```\n\nLas cadenas multilínea se crean utilizando tres comillas simples (`'''`) o tres comillas dobles (`\"\"\"`). A continuación un ejemplo:\n\n```py\nmultiline_string = '''I am a teacher and enjoy teaching.\nI didn't find anything as rewarding as empowering people.\nThat is why I created 30 days of python.'''\nprint(multiline_string)\n\n# Otra forma\nmultiline_string = \"\"\"I am a teacher and enjoy teaching.\nI didn't find anything as rewarding as empowering people.\nThat is why I created 30 days of python.\"\"\"\nprint(multiline_string)\n```\n\n### Concatenación de cadenas\n\nPodemos concatenar cadenas. La unión de cadenas se llama concatenación. Vea el siguiente ejemplo:\n\n```py\n\nfirst_name = 'Asabeneh'\nlast_name = 'Yetayeh'\nspace = ' '\nfull_name = first_name + space + last_name\nprint(full_name) # Asabeneh Yetayeh\n# Uso de `len()` para obtener la longitud de una cadena\nprint(len(first_name)) # 8\nprint(len(last_name)) # 7\nprint(len(first_name) > len(last_name)) # True\nprint(len(full_name)) # 16\n```\n\n### Secuencias de escape en cadenas\n\nEn Python y otros lenguajes una barra invertida (`\\`) seguida de un carácter forma una secuencia de escape. Algunas secuencias comunes son:\n\n- \\n: nueva línea\n- \\t: tabulación (4 espacios)\n- \\\\\\\\: barra invertida\n- \\' : comilla simple\n- \\\" : comilla doble\n\nAhora veamos ejemplos del uso de estas secuencias.\n\n```py\nprint('I hope everyone is enjoying the Python Challenge.\\nAre you ?') # nueva línea\nprint('Days\\tTopics\\tExercises') # añade una tabulación\nprint('Day 1\\t5\\t5')\nprint('Day 2\\t6\\t20')\nprint('Day 3\\t5\\t23')\nprint('Day 4\\t1\\t35')\nprint('This is a backslash symbol (\\\\)') # imprime barra invertida\nprint('In every programming language it starts with \\\"Hello, World!\\\"') # comillas dobles dentro de comillas simples\n\n# Salida\nI hope every one is enjoying the Python Challenge.\nAre you ?\nDays\tTopics\tExercises\nDay 1\t5\t 5\nDay 2\t6\t 20\nDay 3\t5\t 23\nDay 4\t1\t 35\nThis is a backslash symbol (\\)\nIn every programming language it starts with \"Hello, World!\"\n```\n\n### Formateo de cadenas\n\n#### Formateo clásico (% operador)\n\nEn Python existen varias maneras de formatear cadenas. En esta sección veremos algunas de ellas.\nEl operador '%' se usa para formatear una tupla de variables dentro de una cadena de formato, usando especificadores como '%s', '%d', '%f' y '%.nf'.\n\n- %s - cadena (o cualquier objeto representable como cadena)\n- %d - entero\n- %f - punto flotante\n- \"%.nf\" - punto flotante con precisión fija (n decimales)\n\n```py\n# Solo cadenas\nfirst_name = 'Asabeneh'\nlast_name = 'Yetayeh'\nlanguage = 'Python'\nformated_string = 'I am %s %s. I teach %s' %(first_name, last_name, language)\nprint(formated_string)\n\n# Cadenas y números\nradius = 10\npi = 3.14\narea = pi * radius ** 2\nformated_string = 'The area of circle with a radius %d is %.2f.' %(radius, area) # 2 indica 2 decimales\n\npython_libraries = ['Django', 'Flask', 'NumPy', 'Matplotlib','Pandas']\nformated_string = 'The following are python libraries:%s' % (python_libraries)\nprint(formated_string) # imprime \"The following are python libraries:['Django', 'Flask', 'NumPy', 'Matplotlib','Pandas']\"\n```\n\n#### Formateo moderno (str.format)\n\nEste método de formateo se introdujo en Python 3.\n\n```py\n\nfirst_name = 'Asabeneh'\nlast_name = 'Yetayeh'\nlanguage = 'Python'\nformated_string = 'I am {} {}. I teach {}'.format(first_name, last_name, language)\nprint(formated_string)\na = 4\nb = 3\n\nprint('{} + {} = {}'.format(a, b, a + b))\nprint('{} - {} = {}'.format(a, b, a - b))\nprint('{} * {} = {}'.format(a, b, a * b))\nprint('{} / {} = {:.2f}'.format(a, b, a / b)) # limitar a dos decimales\nprint('{} % {} = {}'.format(a, b, a % b))\nprint('{} // {} = {}'.format(a, b, a // b))\nprint('{} ** {} = {}'.format(a, b, a ** b))\n\n# Salida\n4 + 3 = 7\n4 - 3 = 1\n4 * 3 = 12\n4 / 3 = 1.33\n4 % 3 = 1\n4 // 3 = 1\n4 ** 3 = 64\n\n# Cadenas y números\nradius = 10\npi = 3.14\narea = pi * radius ** 2\nformated_string = 'The area of a circle with a radius {} is {:.2f}.'.format(radius, area) # mantener dos decimales\nprint(formated_string)\n\n```\n\n#### Interpolación / f-Strings (Python 3.6+)\n\nOtra forma moderna de formatear cadenas es la interpolación con f-strings. Las cadenas empiezan con `f` y se insertan expresiones entre llaves.\n\n```py\na = 4\nb = 3\nprint(f'{a} + {b} = {a +b}')\nprint(f'{a} - {b} = {a - b}')\nprint(f'{a} * {b} = {a * b}')\nprint(f'{a} / {b} = {a / b:.2f}')\nprint(f'{a} % {b} = {a % b}')\nprint(f'{a} // {b} = {a // b}')\nprint(f'{a} ** {b} = {a ** b}')\n```\n\n### Las cadenas en Python son secuencias de caracteres\n\nLas cadenas en Python son secuencias de caracteres y comparten los mismos métodos de acceso que otras secuencias como listas y tuplas. La forma más sencilla de extraer caracteres individuales (o elementos de cualquier secuencia) es desempaquetarlos en variables.\n\n#### Desempaquetar caracteres\n\n```\nlanguage = 'Python'\na,b,c,d,e,f = language # desempaquetar caracteres y asignarlos a variables\nprint(a) # P\nprint(b) # y\nprint(c) # t\nprint(d) # h\nprint(e) # o\nprint(f) # n\n```\n\n#### Obtener caracteres por índice\n\nEn programación la indexación comienza en cero. Por tanto, la primera letra está en el índice 0 y la última en la longitud de la cadena menos uno.\n\n\n\n```py\nlanguage = 'Python'\nfirst_letter = language[0]\nprint(first_letter) # P\nsecond_letter = language[1]\nprint(second_letter) # y\nlast_index = len(language) - 1\nlast_letter = language[last_index]\nprint(last_letter) # n\n```\n\nSi queremos contar desde la derecha usamos índices negativos; -1 es el último índice.\n\n```py\nlanguage = 'Python'\nlast_letter = language[-1]\nprint(last_letter) # n\nsecond_last = language[-2]\nprint(second_last) # o\n```\n\n#### Slicing de cadenas\n\nEn Python podemos obtener subcadenas mediante slicing.\n\n```py\nlanguage = 'Python'\nfirst_three = language[0:3] # empieza en índice 0, hasta 3 pero sin incluir 3\nprint(first_three) #Pyt\nlast_three = language[3:6]\nprint(last_three) # hon\n# Otra forma\nlast_three = language[-3:]\nprint(last_three) # hon\nlast_three = language[3:]\nprint(last_three) # hon\n```\n\n#### Invertir cadenas\n\nPodemos invertir fácilmente una cadena.\n\n```py\ngreeting = 'Hello, World!'\nprint(greeting[::-1]) # !dlroW ,olleH\n```\n\n#### Saltar caracteres al hacer slicing\n\nAl pasar un parámetro de paso en slicing podemos omitir caracteres al extraer subcadenas.\n\n\n```py\nlanguage = 'Python'\npto = language[0:6:2] #\nprint(pto) # Pto\n```\n\n### Métodos de cadenas\n\nHay muchos métodos para manipular y formatear cadenas. A continuación vemos algunos ejemplos:\n\n- capitalize(): convierte el primer carácter de la cadena a mayúscula\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.capitalize()) # 'Thirty days of python' (primera letra en mayúscula)\n```\n\n- count(): devuelve el número de ocurrencias de una subcadena: `count(subcadena, start=.., end=..)`. `start` y `end` definen el rango de conteo.\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.count('y')) # 3\nprint(challenge.count('y', 7, 14)) # 1, cuenta entre índices 7 y 14\nprint(challenge.count('th')) # 2\n```\n\n- endswith(): determina si la cadena termina con la subcadena dada; devuelve `True` o `False`\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.endswith('on')) # True\nprint(challenge.endswith('tion')) # False (no termina con 'tion')\n```\n\n- expandtabs(): reemplaza tabulaciones por espacios; el tamaño por defecto es 8, acepta parámetro de tamaño.\n\n```py\nchallenge = 'thirty\\tdays\\tof\\tpython'\nprint(challenge.expandtabs()) # 'thirty days of python'\nprint(challenge.expandtabs(10)) # 'thirty days of python' (tabulaciones expandidas a 10 espacios)\n```\n\n- find(): devuelve el índice de la primera aparición de una subcadena; si no se encuentra devuelve -1\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.find('y')) # 5\nprint(challenge.find('th')) # 0\n```\n\n- rfind(): devuelve el índice de la última aparición de una subcadena; si no se encuentra devuelve -1\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.rfind('y')) # 16\nprint(challenge.rfind('th')) # 17\n```\n\n- format(): formatea una cadena para una salida más legible\nPara más información sobre el formateo de cadenas consulte este [enlace](https://www.programiz.com/python-programming/methods/string/format)\n\n```py\nfirst_name = 'Asabeneh'\nlast_name = 'Yetayeh'\nage = 250\njob = 'teacher'\ncountry = 'Finland'\nsentence = 'I am {} {}. I am a {}. I am {} years old. I live in {}.'.format(first_name, last_name, age, job, country)\nprint(sentence) # I am Asabeneh Yetayeh. I am 250 years old. I am a teacher. I live in Finland.\n\nradius = 10\npi = 3.14\narea = pi * radius ** 2\nresult = 'The area of a circle with radius {} is {}'.format(str(radius), str(area))\nprint(result) # The area of a circle with radius 10 is 314\n```\n\n- index(): devuelve el índice de la primera aparición de una subcadena; acepta parámetros de inicio y fin (por defecto 0 y longitud de la cadena). Si la subcadena no se encuentra, lanza `ValueError`.\n\n```py\nchallenge = 'thirty days of python'\nsub_string = 'da'\nprint(challenge.index(sub_string)) # 7\nprint(challenge.index(sub_string, 9)) # error\n```\n\n- rindex(): devuelve el índice de la última aparición de una subcadena; acepta parámetros de inicio y fin (por defecto 0 y longitud de la cadena).\n\n```py\nchallenge = 'thirty days of python'\nsub_string = 'da'\nprint(challenge.rindex(sub_string)) # 8\nprint(challenge.rindex(sub_string, 9)) # error\n```\n\n- isalnum(): determina si todos los caracteres de la cadena son alfanuméricos\n\n```py\nchallenge = 'ThirtyDaysPython'\nprint(challenge.isalnum()) # True\n\nchallenge = '30DaysPython'\nprint(challenge.isalnum()) # True\n\nchallenge = 'thirty days of python'\nprint(challenge.isalnum()) # False, el espacio no es un carácter alfanumérico\n\nchallenge = 'thirty days of python 2019'\nprint(challenge.isalnum()) # False\n```\n\n- isalpha(): determina si todos los caracteres de la cadena son letras (a-z y A-Z)\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.isalpha()) # False, el espacio no es una letra\nchallenge = 'ThirtyDaysPython'\nprint(challenge.isalpha()) # True\nnum = '123'\nprint(num.isalpha()) # False\n```\n\n- isdecimal(): determina si todos los caracteres son decimales (0-9)\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.isdecimal()) # False\nchallenge = '123'\nprint(challenge.isdecimal()) # True\nchallenge = '\\u00B2'\nprint(challenge.isdigit()) # False\nchallenge = '12 3'\nprint(challenge.isdecimal()) # False, contiene espacios\n```\n\n- isdigit(): determina si todos los caracteres son dígitos (0-9 y otros caracteres numéricos Unicode)\n\n```py\nchallenge = 'Thirty'\nprint(challenge.isdigit()) # False\nchallenge = '30'\nprint(challenge.isdigit()) # True\nchallenge = '\\u00B2'\nprint(challenge.isdigit()) # True (caracteres numéricos Unicode)\n```\n\n- isnumeric(): determina si todos los caracteres son numéricos o están relacionados con números (similar a `isdigit()` pero acepta más símbolos, p. ej. ½)\n\n```py\nnum = '10'\nprint(num.isnumeric()) # True\nnum = '\\u00BD' # ½\nprint(num.isnumeric()) # True\nnum = '10.5'\nprint(num.isnumeric()) # False\n```\n\n- isidentifier(): comprueba si la cadena es un identificador válido (nombre de variable válido)\n\n```py\nchallenge = '30DaysOfPython'\nprint(challenge.isidentifier()) # False, porque empieza por un número\nchallenge = 'thirty_days_of_python'\nprint(challenge.isidentifier()) # True\n```\n\n- islower(): determina si todas las letras de la cadena están en minúsculas\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.islower()) # True\nchallenge = 'Thirty days of python'\nprint(challenge.islower()) # False\n```\n\n- isupper(): determina si todas las letras de la cadena están en mayúsculas\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.isupper()) # False\nchallenge = 'THIRTY DAYS OF PYTHON'\nprint(challenge.isupper()) # True\n```\n\n- join(): devuelve la cadena resultante tras unir los elementos\n\n```py\nweb_tech = ['HTML', 'CSS', 'JavaScript', 'React']\nresult = ' '.join(web_tech)\nprint(result) # 'HTML CSS JavaScript React' (devuelve la cadena unida)\n```\n\n```py\nweb_tech = ['HTML', 'CSS', 'JavaScript', 'React']\nresult = '# '.join(web_tech)\nprint(result) # 'HTML# CSS# JavaScript# React'\n```\n\n- strip(): elimina los caracteres dados del inicio y del final de la cadena\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.strip('noth')) # 'irty days of py' (elimina los caracteres dados del inicio y final)\n```\n\n- replace(): reemplaza una subcadena por otra dada\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.replace('python', 'coding')) # 'thirty days of coding'\n```\n\n- split(): divide una cadena usando un separador dado o espacios\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.split()) # ['thirty', 'days', 'of', 'python']\nchallenge = 'thirty, days, of, python'\nprint(challenge.split(', ')) # ['thirty', 'days', 'of', 'python']\n```\n\n- title(): devuelve la cadena en formato título (Title Case)\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.title()) # Thirty Days Of Python\n```\n\n- swapcase(): convierte mayúsculas a minúsculas y minúsculas a mayúsculas\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.swapcase()) # THIRTY DAYS OF PYTHON\nchallenge = 'Thirty Days Of Python'\nprint(challenge.swapcase()) # tHIRTY dAYS oF pYTHON\n```\n\n- startswith(): determina si la cadena comienza con la subcadena especificada\n\n```py\nchallenge = 'thirty days of python'\nprint(challenge.startswith('thirty')) # True\n\nchallenge = '30 days of python'\nprint(challenge.startswith('thirty')) # False (no empieza con 'thirty')\n```\n\n🌕 Eres una persona extraordinaria con un enorme potencial. Acabas de completar el desafío del Día 4; llevas cuatro pasos en tu camino para convertirte en un gran profesional. Ahora realiza algunos ejercicios para entrenar tu mente y tus habilidades.\n\n## 💻 Ejercicios - Día 4\n\n1. Une las cadenas 'Thirty', 'Days', 'Of', 'Python' en 'Thirty Days Of Python'.\n2. Une las cadenas 'Coding', 'For', 'All' en 'Coding For All'.\n3. Declara la variable `company` y asígnale el valor inicial \"Coding For All\".\n4. Imprime la variable `company` usando `print()`.\n5. Usa `len()` y `print()` para mostrar la longitud de la cadena `company`.\n6. Usa el método `upper()` para convertir todos los caracteres a mayúsculas.\n7. Usa el método `lower()` para convertir todos los caracteres a minúsculas.\n8. Aplica `capitalize()`, `title()` y `swapcase()` sobre la cadena 'Coding For All'.\n9. Extrae mediante slicing la primera palabra de 'Coding For All'.\n10. Usa `index`, `find` u otros métodos para comprobar si la cadena 'Coding For All' contiene la palabra 'Coding'.\n11. Reemplaza la palabra 'Coding' por 'Python' en 'Coding For All'.\n12. Reemplaza 'Python for Everyone' por 'Python for All' (usa `replace()` u otro método).\n13. Separa la cadena 'Coding For All' usando espacios como separador.\n14. Divide la cadena 'Facebook, Google, Microsoft, Apple, IBM, Oracle, Amazon' por las comas.\n15. ¿Qué carácter está en el índice 0 de 'Coding For All'?\n16. ¿Cuál es el índice del último carácter de 'Coding For All'?\n17. ¿Qué carácter está en el índice 10 de 'Coding For All'?\n18. Crea una sigla (acrónimo) a partir de 'Python For Everyone'.\n19. Crea una sigla a partir de 'Coding For All'.\n20. Usando `index`, determina la primera aparición de la letra 'C' en 'Coding For All'.\n21. Usando `index`, determina la primera aparición de la letra 'F' en 'Coding For All'.\n22. Usa `rfind` para determinar la última aparición de 'l' en 'Coding For All People'.\n23. Usa `index` o `find` para encontrar la primera aparición de la palabra 'because' en: 'You cannot end a sentence with because because because is a conjunction'\n24. Usa `rindex` para encontrar la última aparición de la palabra 'because' en: 'You cannot end a sentence with because because because is a conjunction'.\n25. Elimina la frase 'because because because' de: 'You cannot end a sentence with because because because is a conjunction'.\n26. Encuentra la primera aparición de la palabra 'because' en: 'You cannot end a sentence with because because because is a conjunction'.\n27. Elimina la frase 'because because because' de la oración anterior.\n28. ¿La cadena 'Coding For All' empieza con la subcadena 'Coding'?\n29. ¿La cadena 'Coding For All' termina con la subcadena 'coding'?\n30. Elimina los espacios en blanco a la izquierda y derecha de la cadena ' Coding For All '.\n31. Usando `isidentifier()`, ¿cuál de las siguientes devuelve `True`?\n - 30DaysOfPython\n - thirty_days_of_python\n32. Dada la lista ['Django', 'Flask', 'Bottle', 'Pyramid', 'Falcon'], únela en una cadena separada por espacios.\n33. Usa la secuencia de escape de nueva línea para separar las siguientes oraciones:\n ```py\n I am enjoying this challenge.\n I just wonder what is next.\n ```\n34. Usa la secuencia de tabulación para mostrar:\n ```py\n Name Age Country City\n Asabeneh 250 Finland Helsinki\n ```\n35. Usa un método de formateo de cadenas para imprimir:\n\n```py\nradius = 10\narea = 3.14 * radius ** 2\n# The area of a circle with radius 10 is 314 meters square.\n```\n\n36. Usa un método de formateo de cadenas para imprimir:\n\n```py\n8 + 6 = 14\n8 - 6 = 2\n8 * 6 = 48\n8 / 6 = 1.33\n8 % 6 = 2\n8 // 6 = 1\n8 ** 6 = 262144\n```\n\n🎉 ¡Felicidades! 🎉\n\n[<< Día 3](./03_operators_sp.md) | [Día 5 >>](./05_lists_sp.md)\n\n\n"
},
{
"path": "Spanish/05_lists_sp.md",
"content": "
\n\n[<< Día 4](./04_strings_sp.md) | [Día 6 >>](./06_tuples_sp.md)\n\n\n\n- [Día 5](#día-5)\n - [Listas](#listas)\n - [Cómo crear listas](#cómo-crear-listas)\n - [Acceder por índice positivo](#acceder-por-índice-positivo)\n - [Acceder por índice negativo](#acceder-por-índice-negativo)\n - [Desempaquetado de listas](#desempaquetado-de-listas)\n - [Slicing de listas](#slicing-de-listas)\n - [Modificar listas](#modificar-listas)\n - [Buscar elementos](#buscar-elementos)\n - [Agregar elementos](#agregar-elementos)\n - [Insertar elementos](#insertar-elementos)\n - [Eliminar elementos](#eliminar-elementos)\n - [Eliminar con pop()](#eliminar-con-pop)\n - [Eliminar con del](#eliminar-con-del)\n - [Vaciar la lista](#vaciar-la-lista)\n - [Copiar listas](#copiar-listas)\n - [Unir listas](#unir-listas)\n - [Contar elementos](#contar-elementos)\n - [Encontrar el índice de un elemento](#encontrar-el-índice-de-un-elemento)\n - [Invertir listas](#invertir-listas)\n - [Ordenar listas](#ordenar-listas)\n - [💻 Ejercicios - Día 5](#-ejercicios---día-5)\n - [Ejercicios: Nivel 1](#ejercicios-nivel-1)\n - [Ejercicios: Nivel 2](#ejercicios-nivel-2)\n\n# Día 5\n\n## Listas\n\nEn Python hay cuatro tipos de colecciones:\n\n- List: colección ordenada y mutable. Permite elementos duplicados.\n- Tuple: colección ordenada e inmutable. Permite elementos duplicados.\n- Set: colección no ordenada e indexable; no permite duplicados (aunque se pueden añadir elementos).\n- Dictionary: colección no ordenada, mutable y accesible por clave. No permite claves duplicadas.\n\n\nUna lista es una colección ordenada y mutable que puede contener elementos de diferentes tipos. Una lista puede estar vacía o contener elementos heterogéneos.\n\n### Cómo crear listas\n\nEn Python podemos crear listas de dos maneras:\n\n- Usando la función incorporada `list()`\n\n```py\n# Sintaxis\nlst = list()\n```\n\n```py\nempty_list = list() # Esta es una lista vacía\nprint(len(empty_list)) # 0\n```\n- Usando corchetes `[]`\n\n```py\n# Sintaxis\nlst = []\n```\n\n```py\nempty_list = [] # Esta es una lista vacía\nprint(len(empty_list)) # 0\n```\n\nListas con valores iniciales. Usamos `len()` para comprobar la longitud.\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon'] # lista de frutas\nvegetables = ['Tomato', 'Potato', 'Cabbage','Onion', 'Carrot'] # lista de verduras\nanimal_products = ['milk', 'meat', 'butter', 'yoghurt'] # lista de animal products\nweb_techs = ['HTML', 'CSS', 'JS', 'React','Redux', 'Node', 'MongDB'] # lista de web technologies\ncountries = ['Finland', 'Estonia', 'Denmark', 'Sweden', 'Norway']\n\n# Imprimir listas y su longitud\nprint('Fruits:', fruits)\nprint('Number of fruits:', len(fruits))\nprint('Vegetables:', vegetables)\nprint('Number of vegetables:', len(vegetables))\nprint('Animal products:',animal_products)\nprint('Number of animal products:', len(animal_products))\nprint('Web technologies:', web_techs)\nprint('Number of web technologies:', len(web_techs))\nprint('Countries:', countries)\nprint('Number of countries:', len(countries))\n```\n\n```sh\nSalida\nFruits: ['banana', 'orange', 'mango', 'lemon']\nNumber of fruits: 4\nVegetables: ['Tomato', 'Potato', 'Cabbage', 'Onion', 'Carrot']\nNumber of vegetables: 5\nAnimal products: ['milk', 'meat', 'butter', 'yoghurt']\nNumber of animal products: 4\nWeb technologies: ['HTML', 'CSS', 'JS', 'React', 'Redux', 'Node', 'MongDB']\nNumber of web technologies: 7\nCountries: ['Finland', 'Estonia', 'Denmark', 'Sweden', 'Norway']\nNumber of countries: 5\n```\n\n- Las listas pueden contener elementos de distintos tipos\n\n```py\n lst = ['Asabeneh', 250, True, {'country':'Finland', 'city':'Helsinki'}] # lista con distintos tipos de datos\n```\n\n\n### Acceder por índice positivo\n\nUsamos índices para acceder a los elementos de una lista. Los índices comienzan en 0. La imagen muestra claramente dónde empiezan los índices.\n\n\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfirst_fruit = fruits[0] # estamos usando su índice para acceder al primer elemento\nprint(first_fruit) # banana\nsecond_fruit = fruits[1]\nprint(second_fruit) # orange\nlast_fruit = fruits[3]\nprint(last_fruit) # lemon\n# Last index\nlast_index = len(fruits) - 1\nlast_fruit = fruits[last_index]\n```\n\n### Acceder por índice negativo\n\nLos índices negativos cuentan desde el final; `-1` es el último elemento, `-2` el penúltimo.\n\n\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfirst_fruit = fruits[-4]\nlast_fruit = fruits[-1]\nsecond_last = fruits[-2]\nprint(first_fruit) # banana\nprint(last_fruit) # lemon\nprint(second_last) # mango\n```\n\n### Desempaquetado de listas\n\n```py\nlst = ['item1','item2','item3', 'item4', 'item5']\nfirst_item, second_item, third_item, *rest = lst\nprint(first_item) # item1\nprint(second_item) # item2\nprint(third_item) # item3\nprint(rest) # ['item4', 'item5']\n\n```\n\n```py\n# Ejemplo uno\nfruits = ['banana', 'orange', 'mango', 'lemon','lime','apple']\nfirst_fruit, second_fruit, third_fruit, *rest = fruits \nprint(first_fruit) # banana\nprint(second_fruit) # orange\nprint(third_fruit) # mango\nprint(rest) # ['lemon','lime','apple']\n# Ejemplo dos\nfirst, second, third,*rest, tenth = [1,2,3,4,5,6,7,8,9,10]\nprint(first) # 1\nprint(second) # 2\nprint(third) # 3\nprint(rest) # [4,5,6,7,8,9]\nprint(tenth) # 10\n# Ejemplo tres\ncountries = ['Germany', 'France','Belgium','Sweden','Denmark','Finland','Norway','Iceland','Estonia']\ngr, fr, bg, sw, *scandic, es = countries\nprint(gr)\nprint(fr)\nprint(bg)\nprint(sw)\nprint(scandic)\nprint(es)\n```\n\n### Slicing de listas\n\n- Índices positivos: especificando inicio, fin y paso obtenemos una nueva lista. (inicio por defecto 0, fin por defecto len(lst) - 1, paso por defecto 1)\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nall_fruits = fruits[0:4] # devuelve todos los elementos\n# mismo resultado que arriba\nall_fruits = fruits[0:] # Si no se especifica el índice de fin, devolverá todos los elementos desde el inicio hasta el final\norange_and_mango = fruits[1:3] # no incluye el índice 3\norange_mango_lemon = fruits[1:]\norange_and_lemon = fruits[::2] # usamos el tercer parámetro (paso). Toma cada 2 elementos - ['banana', 'mango']\n```\n\n- Índices negativos: especificando inicio, fin y paso con índices negativos se obtiene una nueva lista.\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nall_fruits = fruits[-4:] # Devuelve todos los elementos\norange_and_mango = fruits[-3:-1] # No incluye el último elemento, ['orange', 'mango']\norange_mango_lemon = fruits[-3:] # Devuelve los elementos desde -3 hasta el final, ['orange', 'mango', 'lemon']\nreverse_fruits = fruits[::-1] # un paso negativo invierte la lista, ['lemon', 'mango', 'orange', 'banana']\n```\n\n### Modificar listas\n\nUna lista es una colección ordenada y mutable. A continuación modificamos la lista `fruits`.\n\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits[0] = 'avocado'\nprint(fruits) # ['avocado', 'orange', 'mango', 'lemon']\nfruits[1] = 'apple'\nprint(fruits) # ['avocado', 'apple', 'mango', 'lemon']\nlast_index = len(fruits) - 1\nfruits[last_index] = 'lime'\nprint(fruits) # ['avocado', 'apple', 'mango', 'lime']\n```\n\n### Buscar elementos\n\nUse el operador `in` para comprobar si un elemento es miembro de una lista. Véase el ejemplo.\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\ndoes_exist = 'banana' in fruits\nprint(does_exist) # True\ndoes_exist = 'lime' in fruits\nprint(does_exist) # False\n```\n\n### Agregar elementos\n\nPara añadir un elemento al final de una lista usamos el método `append()`.\n\n```py\n# Sintaxis\nlst = list()\nlst.append(item)\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits.append('apple')\nprint(fruits) # ['banana', 'orange', 'mango', 'lemon', 'apple']\nfruits.append('lime') # ['banana', 'orange', 'mango', 'lemon', 'apple', 'lime']\nprint(fruits)\n```\n\n### Insertar elementos\n\nPodemos usar el método *insert()* para insertar un elemento en un índice específico de la lista. Ten en cuenta que los demás elementos se desplazarán a la derecha. El método *insert()* recibe dos parámetros: el índice y el elemento a insertar.\n\n\n```py\n# Sintaxis\nlst = ['item1', 'item2']\nlst.insert(index, item)\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits.insert(2, 'apple') # inserta 'apple' entre 'orange' y 'mango'\nprint(fruits) # ['banana', 'orange', 'apple', 'mango', 'lemon']\nfruits.insert(3, 'lime') # ['banana', 'orange', 'apple', 'lime', 'mango', 'lemon']\nprint(fruits)\n```\n\n### Eliminar elementos\n\n- Usa el método *remove()* para eliminar un elemento específico de la lista\n\n```py\n# Sintaxis\nlst = ['item1', 'item2']\nlst.remove(item)\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon', 'banana']\nfruits.remove('banana')\nprint(fruits) # ['orange', 'mango', 'lemon', 'banana'] - este método elimina la primera aparición del elemento en la lista\nfruits.remove('lemon')\nprint(fruits) # ['orange', 'mango', 'banana']\n```\n\n### Eliminar con `pop()`\n\nUsa `pop()` para eliminar el elemento en el índice dado (si no se indica, elimina el último elemento):\n\n```py\n# Sintaxis\nlst = ['item1', 'item2']\nlst.pop() # Último elemento\nlst.pop(index)\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits.pop()\nprint(fruits) # ['banana', 'orange', 'mango']\n\nfruits.pop(0)\nprint(fruits) # ['orange', 'mango']\n```\n\n### Eliminar con `del`\n\nUsa la palabra clave *del* para eliminar un índice específico, también puede eliminar un rango de índices o eliminar por completo la lista\n\n\n```py\n# Sintaxis\nlst = ['item1', 'item2']\ndel lst[index] # Elimina solo un elemento\ndel lst # Elimina la lista completa\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon', 'kiwi', 'lime']\ndel fruits[0]\nprint(fruits) # ['orange', 'mango', 'lemon', 'kiwi', 'lime']\ndel fruits[1]\nprint(fruits) # ['orange', 'lemon', 'kiwi', 'lime']\ndel fruits[1:3] # elimina elementos en el rango dado; no eliminará el elemento con índice 3!\nprint(fruits) # ['orange', 'lime']\ndel fruits\nprint(fruits) # Esto producirá: NameError: name 'fruits' is not defined\n```\n\n### Vaciar listas\n\nUsa `clear()` para vaciar una lista:\n\n```py\n# Sintaxis\nlst = ['item1', 'item2']\nlst.clear()\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits.clear()\nprint(fruits) # []\n```\n\n### Copiar listas\n\nPuedes copiar una lista reasignándola a una nueva variable: `list2 = list1`. En ese caso `list2` referencia el mismo objeto; los cambios se reflejarán en ambos. Si quieres una copia independiente usa el método `copy()`.\n\n```py\n# Sintaxis\nlst = ['item1', 'item2']\nlst_copy = lst.copy()\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits_copy = fruits.copy()\nprint(fruits_copy) # ['banana', 'orange', 'mango', 'lemon'] (copia de la lista)\n```\n\n### Unir listas\n\nHay varias formas de concatenar o unir dos o más listas.\n\n- Suma (+)\n\n```py\n# Sintaxis\nlist3 = list1 + list2\n```\n\n```py\npositive_numbers = [1, 2, 3, 4, 5]\nzero = [0]\nnegative_numbers = [-5,-4,-3,-2,-1]\nintegers = negative_numbers + zero + positive_numbers\nprint(integers) # [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5]\nfruits = ['banana', 'orange', 'mango', 'lemon']\nvegetables = ['Tomato', 'Potato', 'Cabbage', 'Onion', 'Carrot']\nfruits_and_vegetables = fruits + vegetables\nprint(fruits_and_vegetables ) # ['banana', 'orange', 'mango', 'lemon', 'Tomato', 'Potato', 'Cabbage', 'Onion', 'Carrot']\n```\n\n- Usar el método *extend()*\nEl método *extend()* puede anexar una lista a otra. Véase el ejemplo a continuación.\n\n```py\n# Sintaxis\nlist1 = ['item1', 'item2']\nlist2 = ['item3', 'item4', 'item5']\nlist1.extend(list2)\n```\n\n```py\nnum1 = [0, 1, 2, 3]\nnum2= [4, 5, 6]\nnum1.extend(num2)\nprint('Numbers:', num1) # Numbers: [0, 1, 2, 3, 4, 5, 6]\nnegative_numbers = [-5,-4,-3,-2,-1]\npositive_numbers = [1, 2, 3,4,5]\nzero = [0]\n\nnegative_numbers.extend(zero)\nnegative_numbers.extend(positive_numbers)\nprint('Integers:', negative_numbers) # Integers: [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5]\nfruits = ['banana', 'orange', 'mango', 'lemon']\nvegetables = ['Tomato', 'Potato', 'Cabbage', 'Onion', 'Carrot']\nfruits.extend(vegetables)\nprint('Fruits and vegetables:', fruits ) # Fruits and vegetables: ['banana', 'orange', 'mango', 'lemon', 'Tomato', 'Potato', 'Cabbage', 'Onion', 'Carrot']\n```\n\n### Contar elementos\n\nUsa el método *count()* para devolver el número de veces que aparece un elemento en la lista:\n\n\n```py\n# Sintaxis\nlst = ['item1', 'item2']\nlst.count(item)\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nprint(fruits.count('orange')) # 1\nages = [22, 19, 24, 25, 26, 24, 25, 24]\nprint(ages.count(24)) # 3\n```\n\n### Encontrar el índice de un elemento\n\nEl método *index()* devuelve el índice de un elemento en la lista:\n\n```py\n# Sintaxis\nlst = ['item1', 'item2']\nlst.index(item)\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nprint(fruits.index('orange')) # 1\nages = [22, 19, 24, 25, 26, 24, 25, 24]\nprint(ages.index(24)) # 2, primera aparición\n```\n\n### Invertir listas\n\nUsa el método *reverse()* para invertir el orden de la lista.\n\n```py\n# Sintaxis\nlst = ['item1', 'item2']\nlst.reverse()\n\n```\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon']\nfruits.reverse()\nprint(fruits) # ['lemon', 'mango', 'orange', 'banana']\nages = [22, 19, 24, 25, 26, 24, 25, 24]\nages.reverse()\nprint(ages) # [24, 25, 24, 26, 25, 24, 19, 22]\n```\n\n### Ordenar listas\n\nPara ordenar una lista podemos usar el método *sort()* o la función incorporada *sorted()*. El método *sort()* reordena la lista en orden ascendente y modifica la lista original. Si el parámetro reverse de *sort()* es True, ordenará la lista en orden descendente.\n\n- sort(): Este método modifica la lista original\n\n ```py\n # Sintaxis\n lst = ['item1', 'item2']\n lst.sort() # ascending\n lst.sort(reverse=True) # descending\n ```\n\n **Ejemplo:**\n\n ```py\n fruits = ['banana', 'orange', 'mango', 'lemon']\n fruits.sort()\n print(fruits) # ordenadas alfabéticamente, ['banana', 'lemon', 'mango', 'orange']\n fruits.sort(reverse=True)\n print(fruits) # ['orange', 'mango', 'lemon', 'banana']\n ages = [22, 19, 24, 25, 26, 24, 25, 24]\n ages.sort()\n print(ages) # [19, 22, 24, 24, 24, 25, 25, 26]\n \n ages.sort(reverse=True)\n print(ages) # [26, 25, 25, 24, 24, 24, 22, 19]\n ```\n\n sorted(): No modifica la lista original; devuelve una nueva lista\n\n **Ejemplo:**\n\n ```py\n fruits = ['banana', 'orange', 'mango', 'lemon']\n print(sorted(fruits)) # ['banana', 'lemon', 'mango', 'orange']\n # Reverse order\n fruits = ['banana', 'orange', 'mango', 'lemon']\n fruits = sorted(fruits,reverse=True)\n print(fruits) # ['orange', 'mango', 'lemon', 'banana']\n ```\n\n\n\n🌕 Muy bien, has avanzado mucho. Acabas de completar el desafío del día 5. Ahora realiza algunos ejercicios para practicar.\n\n## 💻 Ejercicios - Día 5\n\n### Ejercicios: Nivel 1\n\n1. Declara una lista vacía\n2. Declara una lista con más de 5 elementos\n3. Encuentra la longitud de la lista\n4. Obtén el primer, medio y último elemento de la lista\n5. Declara una lista llamada `mixed_data_types` que contenga tu nombre, edad, altura, estado civil y dirección\n6. Declara una lista `it_companies` e inicialízala con: Facebook, Google, Microsoft, Apple, IBM, Oracle y Amazon\n7. Imprime la lista usando `print()`\n8. Imprime el número de empresas en la lista\n9. Imprime la primera, la del medio y la última empresa\n10. Cambia el nombre de una de las empresas y vuelve a imprimir la lista\n11. Agrega una empresa IT a `it_companies`\n12. Inserta una empresa IT en la mitad de la lista\n13. Cambia el nombre de una empresa en `it_companies` a mayúsculas (¡excepto IBM!)\n14. Une `it_companies` en una cadena usando la cadena '#; '\n15. Verifica si una empresa existe en `it_companies`\n16. Ordena la lista usando el método `sort()`\n17. Invierte la lista en orden descendente usando `reverse()`\n18. Corta (slice) las primeras 3 empresas de la lista\n19. Corta (slice) las últimas 3 empresas de la lista\n20. Corta la(s) empresa(s) del medio de la lista\n21. Elimina la primera empresa IT de la lista\n22. Elimina la(s) empresa(s) del medio de la lista\n23. Elimina la última empresa IT de la lista\n24. Elimina todas las empresas IT de la lista\n25. Destruye la lista `it_companies`\n26. Concatena las siguientes listas:\n\n ```py\n front_end = ['HTML', 'CSS', 'JS', 'React', 'Redux']\n back_end = ['Node','Express', 'MongoDB']\n ```\n27. Inserta 'Python' y 'SQL' después de `full_stack` en la lista concatenada.\n\n### Ejercicios: Nivel 2\n\n1. A continuación, una lista con las edades de 10 estudiantes:\n\n```py\nages = [19, 22, 19, 24, 20, 25, 26, 24, 25, 24]\n```\n\n- Ordena la lista y encuentra la edad máxima y mínima\n- Agrega la edad mínima y máxima nuevamente a la lista\n- Encuentra la mediana de las edades (un elemento medio o el promedio de dos elementos medios)\n- Encuentra la edad promedio (suma de todos los elementos dividida por su cantidad)\n- Encuentra el rango de edades (máximo - mínimo)\n- Compara |min - promedio| y |max - promedio| usando la función `abs()`\n\n1. Encuentra el país del medio en la [lista de países](https://github.com/Taki-Ta/30-Days-Of-Python-Simplified_Chinese_Version/tree/master/data/countries.py)\n2. Divide la lista de países en dos listas iguales (si es par; si no, la primera lista tendrá un país más)\n3. Para la lista ['China', 'Russia', 'USA', 'Finland', 'Sweden', 'Norway', 'Denmark'], separa los tres primeros países de los países nórdicos restantes.\n\n🎉 ¡Felicidades! 🎉\n\n[<< Día 4](./04_strings_sp.md) | [Día 6 >>](./06_tuples_sp.md)\n"
},
{
"path": "Spanish/06_tuples_sp.md",
"content": "
\n\n[<< Día 5](./05_lists_sp.md) | [Día 7 >>](./07_sets_sp.md)\n\n\n\n- [Día 6](#día-6)\n - [Tuplas](#tuplas)\n - [Cómo crear tuplas](#cómo-crear-tuplas)\n - [Longitud de la tupla](#longitud-de-la-tupla)\n - [Obtener elementos de la tupla](#obtener-elementos-de-la-tupla)\n - [Slicing de tuplas](#slicing-de-tuplas)\n - [Convertir tupla a lista](#convertir-tupla-a-lista)\n - [Comprobar si un elemento está en la tupla](#comprobar-si-un-elemento-está-en-la-tupla)\n - [Unir tuplas](#unir-tuplas)\n - [Eliminar tupla](#eliminar-tupla)\n - [💻 Ejercicios - Día 6](#-ejercicios---día-6)\n - [Ejercicios: Nivel 1](#ejercicios-nivel-1)\n - [Ejercicios: Nivel 2](#ejercicios-nivel-2)\n\n# Día 6\n\n## Tuplas\n\nUna tupla es una colección ordenada e inmutable que puede contener distintos tipos de datos. Una vez creada una tupla, no podemos cambiar sus valores. No podemos usar métodos como add, insert o remove en una tupla porque no es modificable (es inmutable). A diferencia de las listas, las tuplas tienen menos métodos. Los métodos asociados a tuplas son:\n\n- tuple(): crea una tupla vacía\n- count(): cuenta cuántas veces aparece un elemento en la tupla\n- index(): busca el índice de un elemento en la tupla\n- Operador +: concatena dos o más tuplas creando una nueva tupla\n\n### Cómo crear tuplas\n\n- Crear una tupla vacía\n\n ```py\n # Sintaxis\n empty_tuple = ()\n # o usando el constructor de tuplas\n empty_tuple = tuple()\n ```\n\n- Crear una tupla con valores iniciales\n\n ```py\n # Sintaxis\n tpl = ('item1', 'item2','item3')\n ```\n\n ```py\n fruits = ('banana', 'orange', 'mango', 'lemon')\n ```\n\n\n### Longitud de la tupla\n\nUsamos la función _len()_ para obtener la longitud de una tupla.\n\n```py\n# Sintaxis\ntpl = ('item1', 'item2', 'item3')\nlen(tpl)\n```\n\n### Obtener elementos de la tupla\n\n- Índices positivos\n Al igual que con las listas, usamos índices positivos o negativos para acceder a los elementos de una tupla.\n \n\n ```py\n # Sintaxis\n tpl = ('item1', 'item2', 'item3')\n first_item = tpl[0]\n second_item = tpl[1]\n ```\n\n ```py\n fruits = ('banana', 'orange', 'mango', 'lemon')\n first_fruit = fruits[0]\n second_fruit = fruits[1]\n last_index =len(fruits) - 1\n last_fruit = fruits[las_index]\n ```\n\n- Índices negativos\n Los índices negativos cuentan desde el final: -1 es el último elemento, -2 el penúltimo, y así sucesivamente.\n \n\n ```py\n # Sintaxis\n tpl = ('item1', 'item2', 'item3','item4')\n first_item = tpl[-4]\n second_item = tpl[-3]\n ```\n\n ```py\n fruits = ('banana', 'orange', 'mango', 'lemon')\n first_fruit = fruits[-4]\n second_fruit = fruits[-3]\n last_fruit = fruits[-1]\n ```\n\n### Slicing de tuplas\n\nPodemos extraer subtuplas especificando un rango de índices de inicio y fin; el resultado es una nueva tupla con los elementos seleccionados.\n\n- Rango de índices positivos\n\n ```py\n # Sintaxis\n tpl = ('item1', 'item2', 'item3','item4')\n all_items = tpl[0:4] # todos los elementos\n all_items = tpl[0:] # todos los elementos\n middle_two_items = tpl[1:3] # no incluye el índice 3\n ```\n\n ```py\n fruits = ('banana', 'orange', 'mango', 'lemon')\n all_fruits = fruits[0:4] # todos los elementos\n all_fruits= fruits[0:] # todos los elementos\n orange_mango = fruits[1:3] # no incluye el índice 3\n orange_to_the_rest = fruits[1:]\n ```\n\n- Rango de índices negativos\n\n ```py\n # Sintaxis\n tpl = ('item1', 'item2', 'item3','item4')\n all_items = tpl[-4:] # todos los elementos\n middle_two_items = tpl[-3:-1] # no incluye el índice 3\n ```\n\n ```py\n\n fruits = ('banana', 'orange', 'mango', 'lemon')\n all_fruits = fruits[-4:] # todos los elementos\n orange_mango = fruits[-3:-1] # no incluye el índice 3\n orange_to_the_rest = fruits[-3:]\n ```\n\n### Convertir tupla a lista\n\nPodemos convertir una tupla en una lista y viceversa. Si queremos modificar una tupla, conviene convertirla primero en lista.\n\n```py\n# Sintaxis\ntpl = ('item1', 'item2', 'item3','item4')\nlst = list(tpl)\n```\n\n```py\nfruits = ('banana', 'orange', 'mango', 'lemon')\nfruits = list(fruits)\nfruits[0] = 'apple'\nprint(fruits) # ['apple', 'orange', 'mango', 'lemon']\nfruits = tuple(fruits)\nprint(fruits) # ('apple', 'orange', 'mango', 'lemon')\n```\n\n### Comprobar si un elemento está en la tupla\n\nPodemos usar el operador _in_ para comprobar si un elemento pertenece a la tupla; devuelve un valor booleano.\n\n```py\n# Sintaxis\ntpl = ('item1', 'item2', 'item3','item4')\n'item2' in tpl # True\n```\n\n```py\nfruits = ('banana', 'orange', 'mango', 'lemon')\nprint('orange' in fruits) # True\nprint('apple' in fruits) # False\nfruits[0] = 'apple' # TypeError: 'tuple' object does not support item assignment\n```\n\n\n\n### Unir tuplas\n\nPodemos concatenar dos o más tuplas usando el operador +.\n\n```py\n# Sintaxis\ntpl1 = ('item1', 'item2', 'item3')\ntpl2 = ('item4', 'item5','item6')\ntpl3 = tpl1 + tpl2\n```\n\n```py\nfruits = ('banana', 'orange', 'mango', 'lemon')\nvegetables = ('Tomato', 'Potato', 'Cabbage','Onion', 'Carrot')\nfruits_and_vegetables = fruits + vegetables\n```\n\n### Eliminar tupla\n\nNo se pueden eliminar elementos individuales de una tupla, pero sí se puede eliminar la tupla completa con la palabra clave _del_.\n\n```py\n# Sintaxis\ntpl1 = ('item1', 'item2', 'item3')\ndel tpl1\n\n```\n\n```py\nfruits = ('banana', 'orange', 'mango', 'lemon')\ndel fruits\n```\n\n\n🌕 Muy bien, lo conseguiste. Acabas de completar el desafío del día 6. Ahora realiza algunos ejercicios para practicar.\n\n## 💻 Ejercicios - Día 6\n\n### Ejercicios: Nivel 1\n\n1. Crea una tupla vacía\n2. Crea una tupla con los nombres de tus hermanos y hermanas (pueden ser ficticios)\n3. Concatena las tuplas de hermanos y asígnalas a `siblings`\n4. ¿Cuántos hermanos tienes?\n5. Modifica la tupla de `siblings` y añade los nombres de tus padres; asígnala a `family_members`\n\n### Ejercicios: Nivel 2\n\n1. Extrae los hermanos y los padres desde `family_members`\n2. Crea las tuplas `fruits`, `vegetables` y `animal_products`. Concatena las tres tuplas y asígnalas a la variable `food_stuff_tp`\n3. Convierte la tupla `food_stuff_tp` en la lista `food_stuff_lt`\n4. Extrae los elementos del medio desde la tupla `food_stuff_tp` o la lista `food_stuff_lt`\n5. Extrae las primeras tres y las últimas tres entradas de la lista `food_stuff_lt`\n6. Elimina completamente la tupla `food_stuff_tp`\n7. Comprueba si existen los elementos:\n- Verifica si 'Estonia' está en la tupla `nordic_countries`\n- Verifica si 'Iceland' está en la tupla `nordic_countries`\n\n ```py\n nordic_countries = ('Denmark', 'Finland','Iceland', 'Norway', 'Sweden')\n ```\n\n\n[<< Día 5](./05_lists_sp.md) | [Día 7 >>](./07_sets_sp.md)\n"
},
{
"path": "Spanish/07_sets_sp.md",
"content": "
\n\n[<< Día 6](./06_tuples_sp.md) | [Día 8 >>](./08_dictionaries_sp.md)\n\n\n\n- [📘 Día 7](#-día-7)\n - [Conjuntos](#conjuntos)\n - [Crear conjuntos](#crear-conjuntos)\n - [Obtener la longitud del conjunto](#obtener-la-longitud-del-conjunto)\n - [Acceder a elementos del conjunto](#acceder-a-elementos-del-conjunto)\n - [Comprobar elementos](#comprobar-elementos)\n - [Añadir elementos al conjunto](#añadir-elementos-al-conjunto)\n - [Eliminar elementos del conjunto](#eliminar-elementos-del-conjunto)\n - [Vaciar el conjunto](#vaciar-el-conjunto)\n - [Eliminar conjunto](#eliminar-conjunto)\n - [Convertir lista a conjunto](#convertir-lista-a-conjunto)\n - [Unir conjuntos](#unir-conjuntos)\n - [Encontrar intersección](#encontrar-intersección)\n - [Comprobar subconjuntos y superconjuntos](#comprobar-subconjuntos-y-superconjuntos)\n - [Comprobar la diferencia entre conjuntos](#comprobar-la-diferencia-entre-conjuntos)\n - [Encontrar diferencia simétrica](#encontrar-diferencia-simétrica)\n - [Comprobar conjuntos disjuntos](#comprobar-conjuntos-disjuntos)\n - [💻 Ejercicios - Día 7](#-ejercicios---día-7)\n - [Ejercicios: Nivel 1](#ejercicios-nivel-1)\n - [Ejercicios: Nivel 2](#ejercicios-nivel-2)\n - [Ejercicios: Nivel 3](#ejercicios-nivel-3)\n\n# 📘 Día 7\n\n## Conjuntos\n\nUn conjunto es una colección de elementos. Volvamos a las clases de matemáticas de primaria o secundaria: la definición matemática de conjuntos aplica también en Python. Un conjunto es una colección desordenada y no indexada de elementos distintos. En Python, los conjuntos almacenan elementos únicos y se pueden encontrar la _unión_, la _intersección_, la _diferencia_, la _diferencia simétrica_, los _subconjuntos_, los _superconjuntos_ y los _conjuntos disjuntos_ entre conjuntos.\n\n### Crear conjuntos\n\nUsamos la función incorporada _set()_.\n\n- Crear un conjunto vacío\n\n```py\n# Sintaxis\nst = set()\n```\n\n- Crear un conjunto con elementos iniciales\n\n```py\n# Sintaxis\nst = {'item1', 'item2', 'item3', 'item4'}\n```\n\n**Ejemplo:**\n\n```py\n# Sintaxis\nfruits = {'banana', 'orange', 'mango', 'lemon'}\n```\n\n### Obtener la longitud del conjunto\n\nUsamos la función **len()** para obtener la longitud de un conjunto.\n\n```py\n# Sintaxis\nst = {'item1', 'item2', 'item3', 'item4'}\nlen(st)\n```\n\n**Ejemplo:**\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\nlen(fruits)\n\n```\n\n### Acceder a elementos del conjunto\n\nUsamos bucles para recorrer los elementos. Veremos esto con más detalle en la sección de bucles.\n\n### Comprobar elementos\n\nPara comprobar si un elemento existe en un conjunto usamos el operador de pertenencia _in_.\n\n```py\n# Sintaxis\nst = {'item1', 'item2', 'item3', 'item4'}\nprint(\"Does set st contain item3? \", 'item3' in st) # Does set st contain item3? True\n```\n\n**Ejemplo:**\n\n```py\n\nfruits = {'plátano', 'naranja', 'mango', 'limón'}\n\nprint('mango' in fruits ) # True\n\n```\n\n### Añadir elementos al conjunto\n\nUna vez creado el conjunto no podemos cambiar elementos existentes, pero sí podemos añadir nuevos.\n\n- Usar el método _add()_ para agregar un solo elemento\n\n```py\n# Sintaxis\nst = {'item1', 'item2', 'item3', 'item4'}\nst.add('item5')\n```\n\n**Ejemplo:**\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\nfruits.add('lime')\n```\n\n- Usar el método _update()_ para agregar varios elementos\n El método _update()_ permite añadir múltiples elementos; recibe un iterable como argumento.\n\n```py\n# Sintaxis\nst = {'item1', 'item2', 'item3', 'item4'}\nst.update(['item5','item6','item7'])\n```\n\n**Ejemplo:**\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\nvegetables = ('tomato', 'potato', 'cabbage','onion', 'carrot')\nfruits.update(vegetables)\n```\n\n### Eliminar elementos del conjunto\n\nPodemos usar el método _remove()_ para eliminar un elemento de un conjunto. Si el elemento no existe, _remove()_ lanzará un error; por eso es útil comprobar antes si existe. El método _discard()_ no lanzará error si el elemento no existe.\n\n```py\n# Sintaxis\nst = {'item1', 'item2', 'item3', 'item4'}\nst.remove('item2')\n```\n\nEl método _pop()_ elimina y devuelve un elemento aleatorio del conjunto.\n\n**Ejemplo:**\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\nfruits.pop() # Elimina un elemento aleatorio del conjunto\n```\n\nSi nos interesa el elemento eliminado.\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\nremoved_item = fruits.pop()\n```\n\n### Vaciar el conjunto\n\nSi queremos vaciar todas las entradas de un conjunto, podemos usar el método _clear()_.\n\n```py\n# Sintaxis\nst = {'item1', 'item2', 'item3', 'item4'}\nst.clear()\n```\n\n**Ejemplo:**\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\nfruits.clear()\nprint(fruits) # set()\n```\n\n### Eliminar conjunto\n\nSi queremos eliminar el conjunto por completo, podemos usar el operador _del_.\n\n```py\n# Sintaxis\nst = {'item1', 'item2', 'item3', 'item4'}\ndel st\n```\n\n**Ejemplo:**\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\ndel fruits\n```\n\n### Convertir lista a conjunto\n\nPodemos convertir una lista en un conjunto y viceversa. Convertir una lista a conjunto elimina duplicados y conserva solo elementos únicos.\n\n```py\n# Sintaxis\nlst = ['item1', 'item2', 'item3', 'item4', 'item1']\nst = set(lst) # {'item2', 'item4', 'item1', 'item3'} - El orden es aleatorio, ya que los conjuntos son generalmente no ordenados\n```\n\n**Ejemplo:**\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon','orange', 'banana']\nfruits = set(fruits) # {'mango', 'lemon', 'banana', 'orange'}\n```\n\n### Unir conjuntos\n\nPodemos usar los métodos _union()_ o _update()_ para combinar dos conjuntos.\n\n- Union\n Este método devuelve un nuevo conjunto\n\n```py\n# Sintaxis\nst1 = {'item1', 'item2', 'item3', 'item4'}\nst2 = {'item5', 'item6', 'item7', 'item8'}\nst3 = st1.union(st2)\n```\n\n**Ejemplo:**\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\nvegetables = {'tomato', 'potato', 'cabbage','onion', 'carrot'}\nprint(fruits.union(vegetables)) # {'lemon', 'carrot', 'tomato', 'banana', 'mango', 'orange', 'cabbage', 'potato', 'onion'}\n```\n\n- Update\n Este método inserta los elementos de un conjunto en el conjunto dado\n\n```py\n# Sintaxis\nst1 = {'item1', 'item2', 'item3', 'item4'}\nst2 = {'item5', 'item6', 'item7', 'item8'}\nst1.update(st2) # Los elementos de st2 se añaden a st1\n```\n\n**Ejemplo:**\n\n```py\nfruits = {'banana', 'orange', 'mango', 'lemon'}\nvegetables = {'tomato', 'potato', 'cabbage','onion', 'carrot'}\nfruits.update(vegetables)\nprint(fruits) # {'lemon', 'carrot', 'tomato', 'banana', 'mango', 'orange', 'cabbage', 'potato', 'onion'}\n```\n\n### Encontrar intersección\n\nLa intersección devuelve un conjunto con los elementos que están presentes en ambos conjuntos. Véase el ejemplo.\n\n```py\n# Sintaxis\nst1 = {'item1', 'item2', 'item3', 'item4'}\nst2 = {'item3', 'item2'}\nst1.intersection(st2) # {'item3', 'item2'}\n```\n\n**Ejemplo:**\n\n```py\nwhole_numbers = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10}\neven_numbers = {0, 2, 4, 6, 8, 10}\nwhole_numbers.intersection(even_numbers) # {0, 2, 4, 6, 8, 10}\n\npython = {'p', 'y', 't', 'h', 'o', 'n'}\ndragon = {'d', 'r', 'a', 'g', 'o', 'n'}\npython.intersection(dragon) # {'o', 'n'}\n```\n\n### Comprobar subconjuntos y superconjuntos\n\nUn conjunto puede ser subconjunto o superconjunto de otro:\n\n- Subconjunto: _issubset()_\n- Superconjunto: _issuperset()_\n\n```py\n# Sintaxis\nst1 = {'item1', 'item2', 'item3', 'item4'}\nst2 = {'item2', 'item3'}\nst2.issubset(st1) # True\nst1.issuperset(st2) # True\n```\n\n**Ejemplo:**\n\n```py\nwhole_numbers = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10}\neven_numbers = {0, 2, 4, 6, 8, 10}\nwhole_numbers.issubset(even_numbers) # Falso, porque es un superconjunto\nwhole_numbers.issuperset(even_numbers) # Verdadero\n\npython = {'p', 'y', 't', 'h', 'o', 'n'}\ndragon = {'d', 'r', 'a', 'g', 'o', 'n'}\npython.issubset(dragon) # Falso\n```\n\n### Comprobar la diferencia entre conjuntos\n\nDevuelve la diferencia entre dos conjuntos.\n\n```py\n# Sintaxis\nst1 = {'item1', 'item2', 'item3', 'item4'}\nst2 = {'item2', 'item3'}\nst2.difference(st1) # set()\nst1.difference(st2) # {'item1', 'item4'} => st1\\st2\n```\n\n**Ejemplo:**\n\n```py\nwhole_numbers = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10}\neven_numbers = {0, 2, 4, 6, 8, 10}\nwhole_numbers.difference(even_numbers) # {1, 3, 5, 7, 9}\n\npython = {'p', 'y', 't', 'o', 'n'}\ndragon = {'d', 'r', 'a', 'g', 'o', 'n'}\npython.difference(dragon) # {'p', 'y', 't'} - El resultado es desordenado (propiedad de los conjuntos)\ndragon.difference(python) # {'d', 'r', 'a', 'g'}\n```\n\n### Encontrar diferencia simétrica\n\nDevuelve la diferencia simétrica entre dos conjuntos. Es decir, devuelve los elementos que pertenecen a uno de los conjuntos pero no a ambos; matemáticamente: (A\\B) ∪ (B\\A).\n\n```py\n# Sintaxis\nst1 = {'item1', 'item2', 'item3', 'item4'}\nst2 = {'item2', 'item3'}\n# Significa (A\\B) ∪ (B\\A)\nst2.symmetric_difference(st1) # {'item1', 'item4'}\n```\n\n**Ejemplo:**\n\n```py\nwhole_numbers = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10}\nsome_numbers = {1, 2, 3, 4, 5}\nwhole_numbers.symmetric_difference(some_numbers) # {0, 6, 7, 8, 9, 10}\n\npython = {'p', 'y', 't', 'h', 'o', 'n'}\ndragon = {'d', 'r', 'a', 'g', 'o', 'n'}\npython.symmetric_difference(dragon) # {'r', 't', 'p', 'y', 'g', 'a', 'd', 'h'}\n```\n\n### Comprobar conjuntos disjuntos\n\nSi dos conjuntos no comparten elementos se dicen disjuntos. Podemos usar el método _isdisjoint()_ para comprobar si dos conjuntos son disjuntos.\n\n```py\n# Sintaxis\nst1 = {'item1', 'item2', 'item3', 'item4'}\nst2 = {'item2', 'item3'}\nst2.isdisjoint(st1) # Falso\n```\n\n**Ejemplo:**\n\n```py\neven_numbers = {0, 2, 4, 6, 8}\nodd_numbers = {1, 3, 5, 7, 9}\neven_numbers.isdisjoint(odd_numbers) # Verdadero, porque no comparten elementos\n\npython = {'p', 'y', 't', 'h', 'o', 'n'}\ndragon = {'d', 'r', 'a', 'g', 'o', 'n'}\npython.isdisjoint(dragon) # Falso, comparten {'o', 'n'}\n```\n\n🌕 Eres una estrella en ascenso. Acabas de completar el desafío del día 7. Ahora realiza algunos ejercicios para practicar.\n\n## 💻 Ejercicios - Día 7\n\n```py\n# Conjuntos\nit_companies = {'Facebook', 'Google', 'Microsoft', 'Apple', 'IBM', 'Oracle', 'Amazon'}\nA = {19, 22, 24, 20, 25, 26}\nB = {19, 22, 20, 25, 26, 24, 28, 27}\nage = [22, 19, 24, 25, 26, 24, 25, 24]\n```\n\n### Ejercicios: Nivel 1\n\n1. Encuentra la longitud del conjunto `it_companies`\n2. Agrega 'Twitter' a `it_companies`\n3. Inserta varias empresas IT a `it_companies` de una sola vez\n4. Elimina una empresa de `it_companies`\n5. ¿Cuál es la diferencia entre `remove()` y `discard()`?\n\n### Ejercicios: Nivel 2\n\n1. Concatena A y B\n2. Encuentra la intersección entre A y B\n3. ¿Es A un subconjunto de B?\n4. ¿Son A y B conjuntos disjuntos?\n5. Combina A con B y viceversa\n6. ¿Cuál es la diferencia simétrica entre A y B?\n7. Elimina un conjunto por completo\n\n### Ejercicios: Nivel 3\n\n1. Convierte la lista de edades a un conjunto y compara la longitud de la lista y la del conjunto: ¿cuál es mayor?\n2. Explica la diferencia entre estos tipos de datos: cadena, lista, tupla y conjunto\n3. Para la frase _\"Soy profesor, me gusta motivar y enseñar a las personas.\"_ ¿cuántas palabras únicas tiene? Usa `split()` y conjuntos para obtener las palabras únicas.\n\n🎉 ¡Felicidades! 🎉\n\n[<< Día 6](./06_tuples_sp.md) | [Día 8 >>](./08_dictionaries_sp.md)\n"
},
{
"path": "Spanish/08_dictionaries_sp.md",
"content": "
\n\n[<< Día 7](./07_sets_sp.md) | [Día 9 >>](./09_conditionals_sp.md)\n\n\n\n- [📘 Día 8](#-día-8)\n - [Diccionarios](#diccionarios)\n - [Crear diccionarios](#crear-diccionarios)\n - [Longitud del diccionario](#longitud-del-diccionario)\n - [Acceder a elementos del diccionario](#acceder-a-elementos-del-diccionario)\n - [Añadir elementos al diccionario](#añadir-elementos-al-diccionario)\n - [Modificar elementos del diccionario](#modificar-elementos-del-diccionario)\n - [Comprobar claves en el diccionario](#comprobar-claves-en-el-diccionario)\n - [Eliminar pares clave-valor del diccionario](#eliminar-pares-clave-valor-del-diccionario)\n - [Convertir diccionario a lista de tuplas](#convertir-diccionario-a-lista-de-tuplas)\n - [Vaciar diccionario](#vaciar-diccionario)\n - [Eliminar diccionario](#eliminar-diccionario)\n - [Copiar diccionario](#copiar-diccionario)\n - [Convertir claves a lista](#convertir-claves-a-lista)\n - [Convertir valores a lista](#convertir-valores-a-lista)\n - [💻 Ejercicios - Día 8](#-ejercicios---día-8)\n\n# 📘 Día 8\n\n## Diccionarios\n\nUn diccionario es un tipo de datos compuesto por pares clave-valor desordenados y modificables (mutables).\n\n### Crear diccionarios\n\nPara crear diccionarios, usamos llaves {} o la función incorporada _dict()_.\n\n```py\n# Sintaxis\nempty_dict = {}\n# Diccionario con valores\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\n```\n\n**Ejemplo:**\n\n```py\nperson = {\n 'first_name':'Asabeneh',\n 'last_name':'Yetayeh',\n 'age':250,\n 'country':'Finland',\n 'is_married':True,\n 'skills':['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address':{\n 'street':'Space street',\n 'zipcode':'02210'\n }\n }\n```\n\nEl diccionario anterior muestra que los valores pueden ser de cualquier tipo de datos: cadenas, booleanos, listas, tuplas, conjuntos o diccionarios.\n\n### Longitud del diccionario\n\nEsta función comprueba la cantidad de pares clave-valor en el diccionario.\n\n```py\n# Sintaxis\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\nprint(len(dct)) # 4\n```\n\n**Ejemplo:**\n\n```py\nperson = {\n 'first_name':'Asabeneh',\n 'last_name':'Yetayeh',\n 'age':250,\n 'country':'Finland',\n 'is_married':True,\n 'skills':['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address':{\n 'street':'Space street',\n 'zipcode':'02210'\n }\n }\nprint(len(person)) # 7\n\n```\n\n### Acceder a elementos del diccionario\n\nPodemos acceder a los elementos del diccionario referenciando sus claves.\n\n```py\n# Sintaxis\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\nprint(dct['key1']) # value1\nprint(dct['key4']) # value4\n```\n\n**Ejemplo:**\n\n```py\nperson = {\n 'first_name':'Asabeneh',\n 'last_name':'Yetayeh',\n 'age':250,\n 'country':'Finland',\n 'is_married':True,\n 'skills':['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address':{\n 'street':'Space street',\n 'zipcode':'02210'\n }\n }\nprint(person['first_name']) # Asabeneh\nprint(person['country']) # Finland\nprint(person['skills']) # ['JavaScript', 'React', 'Node', 'MongoDB', 'Python']\nprint(person['skills'][0]) # JavaScript\nprint(person['address']['street']) # Space street\nprint(person['city']) # Error\n```\n\nCuando se accede a un elemento por clave, si la clave no existe se lanzará un error. Para evitarlo, primero compruebe si existe la clave o use el método _get_. El método get devuelve None si la clave no existe (que es un objeto de tipo NoneType).\n\n```py\nperson = {\n 'first_name':'Asabeneh',\n 'last_name':'Yetayeh',\n 'age':250,\n 'country':'Finland',\n 'is_married':True,\n 'skills':['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address':{\n 'street':'Space street',\n 'zipcode':'02210'\n }\n }\nprint(person.get('first_name')) # Asabeneh\nprint(person.get('country')) # Finland\nprint(person.get('skills')) #['HTML','CSS','JavaScript', 'React', 'Node', 'MongoDB', 'Python']\nprint(person.get('city')) # None\n```\n\n### Añadir elementos al diccionario\n\nPodemos añadir nuevos pares clave-valor al diccionario\n\n```py\n# Sintaxis\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\ndct['key5'] = 'value5'\n```\n\n**Ejemplo:**\n\n```py\nperson = {\n 'first_name':'Asabeneh',\n 'last_name':'Yetayeh',\n 'age':250,\n 'country':'Finland',\n 'is_married':True,\n 'skills':['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address':{\n 'street':'Space street',\n 'zipcode':'02210'\n }\n}\nperson['job_title'] = 'Instructor'\nperson['skills'].append('HTML')\nprint(person)\n```\n\n### Modificar elementos del diccionario\n\nPodemos modificar elementos del diccionario\n\n```py\n# Sintaxis\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\ndct['key1'] = 'value-one'\n```\n\n**Ejemplo:**\n\n```py\nperson = {\n 'first_name':'Asabeneh',\n 'last_name':'Yetayeh',\n 'age':250,\n 'country':'Finland',\n 'is_married':True,\n 'skills':['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address':{\n 'street':'Space street',\n 'zipcode':'02210'\n }\n}\nperson['first_name'] = 'Eyob'\nperson['age'] = 252\n```\n\n### Comprobar claves en el diccionario\n\nUsamos el operador _in_ para comprobar si una clave existe en el diccionario\n\n```py\n# Sintaxis\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\nprint('key2' in dct) # True\nprint('key5' in dct) # False\n```\n\n### Eliminar pares clave-valor del diccionario\n\n- _pop(key)_: elimina el elemento con la clave especificada\n- _popitem()_: elimina el último elemento\n- _del_: elimina el elemento con la clave especificada\n\n```py\n# Sintaxis\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\ndct.pop('key1') # elimina el elemento key1\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\ndct.popitem() # elimina el último elemento\ndel dct['key2'] # elimina el elemento key2\n```\n\n**Ejemplo:**\n\n```py\nperson = {\n 'first_name':'Asabeneh',\n 'last_name':'Yetayeh',\n 'age':250,\n 'country':'Finland',\n 'is_married':True,\n 'skills':['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address':{\n 'street':'Space street',\n 'zipcode':'02210'\n }\n}\nperson.pop('first_name') # elimina el elemento first_name\nperson.popitem() # elimina el último elemento\ndel person['is_married'] # elimina el elemento is_married\n```\n\n### Convertir diccionario a lista de tuplas\n\nEl método _items()_ convierte el diccionario en una lista de tuplas.\n\n```py\n# Sintaxis\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\nprint(dct.items()) # dict_items([('key1', 'value1'), ('key2', 'value2'), ('key3', 'value3'), ('key4', 'value4')])\n```\n\n### Vaciar diccionario\n\nSi no necesitamos los elementos del diccionario, podemos usar el método _clear()_ para vaciarlo\n\n```py\n# Sintaxis\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\nprint(dct.clear()) # None\n```\n\n### Eliminar diccionario\n\nSi ya no necesitamos el diccionario, podemos eliminarlo por completo\n\n```py\n# Sintaxis\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\ndel dct\n```\n\n### Copiar diccionario\n\nPodemos usar el método _copy()_ para copiar un diccionario. Usar copy evita que el diccionario original sea modificado.\n\n```py\n# Sintaxis\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\ndct_copy = dct.copy() # {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\n```\n\n### Obtener lista de claves del diccionario\n\nEl método keys() nos da una lista con todas las claves del diccionario.\n\n```py\n# Sintaxis\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\nkeys = dct.keys()\nprint(keys) # dict_keys(['key1', 'key2', 'key3', 'key4'])\n```\n\n### Obtener lista de valores del diccionario\n\nEl método values() nos da una lista con todos los valores del diccionario.\n\n```py\n# Sintaxis\ndct = {'key1':'value1', 'key2':'value2', 'key3':'value3', 'key4':'value4'}\nvalues = dct.values()\nprint(values) # dict_values(['value1', 'value2', 'value3', 'value4'])\n```\n\n🌕 ¡Bien hecho! Ahora dominas las potentes capacidades de los diccionarios. Has completado el desafío del Día 8, estás un paso más cerca del éxito. Ahora ejercita tu mente y tu cuerpo.\n\n## 💻 Ejercicios - Día 8\n\n1. Crea un diccionario vacío llamado dog\n2. Añade las claves name, color, breed, legs y age al diccionario dog\n3. Crea un diccionario student con las claves first_name, last_name, gender, age, marital status, skills, country, city y address\n4. Obtén la longitud del diccionario student\n5. Obtén el valor de skills y comprueba su tipo; debe ser una lista\n6. Modifica skills añadiendo una o dos habilidades\n7. Obtén la lista de claves del diccionario\n8. Obtén la lista de valores del diccionario\n9. Usa el método _items()_ para convertir el diccionario en una lista de tuplas\n10. Elimina un elemento del diccionario\n11. Elimina uno de los diccionarios\n\n🎉 ¡Felicidades! 🎉\n\n[<< Día 7](./07_sets_sp.md) | [Día 9 >>](./09_conditionals_sp.md)\n"
},
{
"path": "Spanish/09_conditionals_sp.md",
"content": "
\n
30 días de Python: Día 9 - Sentencias condicionales
\n\n[<< Día 8](./08_dictionaries_sp.md) | [Día 10 >>](./10_loops_sp.md)\n\n\n\n- [📘 Día 9](#-día-9)\n - [Sentencias condicionales](#sentencias-condicionales)\n - [Condición If](#condición-if)\n - [If Else](#if-else)\n - [If Elif Else](#if-elif-else)\n - [Abreviación](#abreviación)\n - [Condicionales anidados](#condicionales-anidados)\n - [If y operadores lógicos](#if-y-operadores-lógicos)\n - [If y operador lógico Or](#if-y-operador-lógico-or)\n - [💻 Ejercicios - Día 9](#-ejercicios---día-9)\n - [Ejercicios: Nivel 1](#ejercicios-nivel-1)\n\n# 📘 Día 9\n\n## Sentencias condicionales\n\nPor defecto, las sentencias en un script de Python se ejecutan secuencialmente de arriba hacia abajo. Si la lógica lo requiere, podemos cambiar el orden de dos maneras:\n\n- Ejecución condicional: si una expresión es verdadera, se ejecutan uno o más bloques de código\n- Ejecución repetitiva: mientras una expresión sea verdadera, se repiten uno o más bloques de código. En esta sección discutiremos las sentencias *if*, *else* y *elif*. Los operadores de comparación y lógicos vistos antes serán útiles aquí.\n\n### Condición If\n\nEn Python y otros lenguajes, la palabra clave *if* se usa para comprobar si una condición es verdadera y ejecutar un bloque de código. Recuerda la indentación después de los dos puntos.\n\n```py\n# Sintaxis\nif condition:\n # Si la condición es verdadera, ejecutar este bloque de código\n```\n\n**Ejemplo 1**\n\n```py\na = 3\nif a > 0:\n print('A es un número positivo')\n# A es un número positivo\n```\n\nComo se muestra arriba, 3 es mayor que 0. La condición es verdadera y se ejecuta el bloque de código. Si la condición fuera falsa, no veríamos resultado; para manejar condiciones falsas usamos el bloque *else*.\n\n### If Else\n\nSi la condición es verdadera se ejecuta el primer bloque, de lo contrario se ejecuta el bloque *else*.\n\n```py\n# Sintaxis\nif condition:\n # Si la condición es verdadera, ejecutar este bloque\nelse:\n # Si la condición es falsa, ejecutar este bloque\n```\n\n**Ejemplo:**\n\n```py\na = 3\nif a < 0:\n print('A es un número negativo')\nelse:\n print('A es un número positivo')\n```\n\nLa condición anterior es falsa, por eso se ejecuta el bloque *else*. ¿Y si tenemos más de dos condiciones? Podemos usar *elif*.\n\n### If Elif Else\n\nEn la vida tomamos decisiones cada día que implican más de una condición. En programación, cuando tenemos múltiples condiciones, usamos *elif*.\n\n```py\n# Sintaxis\nif condition:\n # código\nelif condition:\n # código\nelse:\n # código\n```\n\n**Ejemplo:**\n\n```py\na = 0\nif a > 0:\n print('A es un número positivo')\nelif a < 0:\n print('A es un número negativo')\nelse:\n print('A es cero')\n```\n\n### Abreviación\n\n```py\n# Sintaxis\n if condición else \n```\n\n**Ejemplo:**\n\n```py\na = 3\nprint('A es positivo') if a > 0 else print('A es negativo') # Se cumple la primera condición, imprimirá 'A es positivo'\n```\n\n### Condicionales anidados\n\nLos condicionales pueden anidarse.\n\n```py\n# Sintaxis\nif condición:\n # código\n if condición:\n # código\n```\n\n**Ejemplo:**\n\n```py\na = 0\nif a > 0:\n if a % 2 == 0:\n print('A es un número positivo y par')\n else:\n print('A es un número positivo')\nelif a == 0:\n print('A es cero')\nelse:\n print('A es un número negativo')\n```\n\nPodemos usar el operador lógico *and* para evitar escribir condicionales anidados.\n\n### If y operadores lógicos\n\n```py\n# Sintaxis\nif condición and condición:\n # código\n```\n\n**Ejemplo:**\n\n```py\na = 0\nif a > 0 and a % 2 == 0:\n print('A es un número positivo y par')\nelif a > 0 and a % 2 != 0:\n print('A es un número positivo')\nelif a == 0:\n print('A es cero')\nelse:\n print('A es un número negativo')\n```\n\n### If y operador lógico Or\n\n```py\n# Sintaxis\nif condición or condición:\n # código\n```\n\n**Ejemplo:**\n\n```py\nuser = 'James'\naccess_level = 3\nif user == 'admin' or access_level >= 4:\n print('Acceso concedido!')\nelse:\n print('Acceso denegado!')\n```\n\n🌕 Lo estás haciendo muy bien. Nunca te rindas; las cosas grandiosas requieren tiempo. Acabas de completar el desafío del Día 9; estás a 9 pasos en tu camino hacia lo grande. Haz ahora algunos ejercicios para entrenar tu mente y tu cuerpo.\n\n## 💻 Ejercicios - Día 9\n\n### Ejercicios: Nivel 1\n\n1. Usa input para obtener la edad del usuario (por ejemplo: \"Introduce tu edad:\"). Si el usuario tiene 18 años o más, muestra: 'Ya tienes la edad suficiente para aprender a conducir.' Si es menor, muestra cuántos años le faltan. Ejemplo de salida:\n\n ```sh\n Introduce tu edad: 30\n Ya tienes la edad suficiente para aprender a conducir.\n Salida:\n Introduce tu edad: 15\n Aún necesitas esperar 3 años para aprender a conducir.\n ```\n\n2. Usa if…else para comparar my_age y your_age. ¿Quién es mayor (yo o tú)? Usa input(\"Introduce tu edad:\") para obtener la edad. Puedes usar condicionales anidados para imprimir 'año' cuando la diferencia sea 1, 'años' para diferencias mayores, y un mensaje personalizado si my_age = your_age. Salida de ejemplo:\n\n ```sh\n Introduce tu edad: 30\n Tienes 5 años más que yo.\n ```\n\n3. Pide al usuario dos números con input. Si a > b, imprime 'a es mayor que b'; si a < b, imprime 'a es menor que b'; si son iguales, imprime 'a es igual a b'.\n\n```sh\nIntroduce el primer número: 4\nIntroduce el segundo número: 3\n4 es mayor que 3\n```\n\n### Ejercicios: Nivel 2\n\n1. Escribe un código que asigne una calificación según la nota del estudiante:\n\n ```sh\n 80-100, A\n 70-79, B\n 60-69, C\n 50-59, D\n 0-49, F\n ```\n\n2. Comprueba si es otoño, invierno, primavera o verano. Si el usuario introduce:\n Septiembre, Octubre o Noviembre → otoño.\n Diciembre, Enero o Febrero → invierno.\n Marzo, Abril o Mayo → primavera.\n Junio, Julio u Agosto → verano.\n3. La siguiente lista contiene algunas frutas:\n\n ```py\n fruits = ['banana', 'orange', 'mango', 'lemon']\n ```\n\n Si una fruta no está en la lista, añádela e imprime la lista modificada. Si ya existe, imprime 'La fruta ya está en la lista'.\n\n### Ejercicios: Nivel 3\n\n1. Aquí hay un diccionario persona. ¡Siéntete libre de modificarlo!\n\n```py\nperson = {\n 'first_name': 'Asabeneh',\n 'last_name': 'Yetayeh',\n 'age': 250,\n 'country': 'Finlandia',\n 'is_married': True,\n 'skills': ['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address': {\n 'street': 'Calle Espacial',\n 'zipcode': '02210'\n }\n}\n```\n\n- Comprueba si existe la clave skills en el diccionario; si existe, imprime la habilidad central de la lista skills.\n- Comprueba si existe la clave skills; si existe, verifica si la persona tiene la habilidad 'Python' e imprime el resultado.\n- Si las habilidades son sólo JavaScript y React, imprime 'Es desarrollador frontend'; si incluyen Node, Python y MongoDB, imprime 'Es desarrollador backend'; si incluyen React, Node y MongoDB, imprime 'Es desarrollador full-stack'; en caso contrario, imprime 'Título desconocido' — puedes anidar más condiciones para mayor precisión.\n- Si la persona está casada y vive en Finlandia, imprime la siguiente línea:\n\n```py\nprint('Asabeneh Yetayeh vive en Finlandia. Está casado.')\n```\n\n🎉 ¡Felicidades! 🎉\n\n[<< Día 8](./08_dictionaries_sp.md) | [Día 10 >>](./10_loops_sp.md)\n"
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\n\n[<< Día 9](./09_conditionals_sp.md) | [Día 11 >>](./11_functions_sp.md)\n\n\n\n\n- [📘 Día 10](#-día-10)\n - [Bucles](#bucles)\n - [Bucle while](#bucle-while)\n - [break y continue - parte 1](#break-y-continue---parte-1)\n - [Bucle for](#bucle-for)\n - [break y continue - parte 2](#break-y-continue---parte-2)\n - [Función range()](#función-range)\n - [Bucles for anidados](#bucles-for-anidados)\n - [for y else](#for-y-else)\n - [Sentencia pass](#sentencia-pass)\n - [💻 Ejercicios - Día 10](#-ejercicios---día-10)\n - [Ejercicios: Nivel 1](#ejercicios-nivel-1)\n - [Ejercicios: Nivel 2](#ejercicios-nivel-2)\n - [Ejercicios: Nivel 3](#ejercicios-nivel-3)\n\n# 📘 Día 10\n\n## Bucles\n\nLa vida está llena de ciclos. En programación realizamos muchas tareas repetitivas. Los lenguajes de programación usan bucles para gestionar tareas repetitivas; en Python hay principalmente dos tipos de bucles:\n1. Bucle while\n2. Bucle for\n\n### Bucle while\n\nUsamos la palabra clave `while` para crear un bucle while. Repite un bloque de código mientras la condición se cumpla. Cuando la condición se vuelve falsa, el bucle termina y se ejecuta el código que sigue.\n\n```python\n# Sintaxis\nwhile condition:\n # código\n```\n\n**Ejemplo:**\n\n```python\ncount = 0\nwhile count < 5:\n print(count)\n count = count + 1\n# prints from 0 to 4\n```\n\nEn el bucle anterior, cuando count llegue a 5 la condición se vuelve falsa y el bucle se detiene.\n\nSi queremos ejecutar un bloque cuando la condición sea falsa, podemos usar la palabra clave `else`.\n\n```python\n # syntax\nwhile condition:\n code goes here\nelse:\n code goes here\n```\n\n**Ejemplo:**\n\n```python\ncount = 0\nwhile count < 5:\n print(count)\n count = count + 1\nelse:\n print(count)\n```\n\nCuando count sea 5 la condición será falsa, el bucle terminará y se ejecutará el bloque else; por tanto se imprimirá 5.\n\n### break y continue - parte 1\n\n* break: cuando queremos salir del bucle usamos la palabra clave \\break`.`\n\n```python\n# syntax\nwhile condition:\n code goes here\n if another_condition:\n break\n```\n\n**Example:**\n\n```python\ncount = 0\nwhile count < 5:\n print(count)\n count = count + 1\n if count == 3:\n break\n```\nEl while anterior solo imprimirá 0, 1, 2; cuando count llegue a 3 el bucle terminará.\n- Continue: cuando queremos saltarnos la iteración actual y continuar con la siguiente usamos la palabra clave `continue`.\n\n```python\n # syntax\nwhile condition:\n code goes here\n if another_condition:\n continue\n```\n\n**Ejemplo:**\n\n```python\ncount = 0\nwhile count < 5:\n if count == 3:\n count = count + 1\n continue\n print(count)\n count = count + 1\n```\n\nEl while anterior imprimirá 0, 1, 2, 4 (3 se saltó).\n\n### Bucle for\n\nLa palabra clave `for` se usa para crear bucles for. Es similar a otros lenguajes, pero con diferencias sintácticas. Se usa para iterar sobre secuencias (listas, tuplas, diccionarios, conjuntos, cadenas, etc.).\n\n- Bucle for para listas\n\n```python\n# syntax\nfor iterator in lst:\n code goes here\n```\n\n**Ejemplo:**\n\n```python\nnumbers = [0, 1, 2, 3, 4, 5]\nfor number in numbers: # number es un nombre temporal que referencia el elemento de la lista dentro del bucle\n print(number) # number se imprimirá línea por línea, de 0 a 5\n```\n\n- Bucle for para cadenas\n\n```python\n# syntax\nfor iterator in string:\n code goes here\n```\n\n**Ejemplo:**\n\n```python\nlanguage = 'Python'\nfor letter in language:\n print(letter)\n\nfor i in range(len(language)):\n print(language[i])\n```\n\n- Bucle for para tuplas\n\n```python\n# syntax\nfor iterator in tpl:\n code goes here\n```\n\n**Ejemplo:**\n\n```python\nnumbers = (0, 1, 2, 3, 4, 5)\nfor number in numbers:\n print(number)\n```\n\n- Bucle for para diccionarios\n Al iterar, se recorrerán las claves del diccionario.\n\n```python\n # syntax\nfor iterator in dct:\n code goes here\n```\n\n**Ejemplo:**\n\n```python\nperson = {\n 'first_name':'Asabeneh',\n 'last_name':'Yetayeh',\n 'age':250,\n 'country':'Finland',\n 'is_marred':True,\n 'skills':['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address':{\n 'street':'Space street',\n 'zipcode':'02210'\n }\n}\nfor key in person:\n print(key) # sólo imprime las claves\n\nfor key, value in person.items():\n print(key, value) # así podemos acceder a claves y valores durante la iteración\n```\n\n- Bucle for para conjuntos\n\n```python\n# syntax\nfor iterator in st:\n code goes here\n```\n\n**Ejemplo:**\n\n```python\nit_companies = {'Facebook', 'Google', 'Microsoft', 'Apple', 'IBM', 'Oracle', 'Amazon'}\nfor company in it_companies:\n print(company)\n```\n\n### break y continue - parte 2\n\nPista:\n_break_: cuando queremos terminar el bucle antes de completarlo usamos `break`.\n\n```python\n# syntax\nfor iterator in sequence:\n code goes here\n if condition:\n break\n```\n\n**Ejemplo:**\n\n```python\nnumbers = (0,1,2,3,4,5)\nfor number in numbers:\n print(number) # imprime 0, 1, 2, 3\n if number == 3:\n break\n```\nEn el ejemplo anterior, cuando number sea 3 el bucle terminará.\n\n_continue_: cuando queremos saltarnos la iteración actual y continuar con la siguiente usamos la palabra clave `continue`.\n\n```python\n # syntax\nfor iterator in sequence:\n code goes here\n if condition:\n continue\n```\n\n**Ejemplo:**\n\n```python\nnumbers = (0,1,2,3,4,5)\nfor number in numbers:\n print(number)\n if number == 3:\n continue\n print('Next number should be ', number + 1) if number != 5 else print(\"loop's end\") # En resumen: para condiciones cortas se puede usar if y else en línea\nprint('outside the loop')\n```\nEn el ejemplo anterior, cuando number es 3, las instrucciones posteriores dentro del bucle se saltan y si hay más elementos por recorrer, continúa con la siguiente iteración.\n\n### Función range()\n\nLa función `range()` genera una secuencia de números. La forma _range(start, end, step)_ acepta tres parámetros: inicio, fin y paso. Por defecto inicio es 0 y el paso es 1. Se necesita al menos un parámetro (el valor de fin).\n\nUsando `range()` para generar secuencias\n\n```python\nlst = list(range(11)) \nprint(lst) # [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\nst = set(range(1, 11)) # start y stop, paso por defecto 1\nprint(st) # {1, 2, 3, 4, 5, 6, 7, 8, 9, 10}\n\nlst = list(range(0,11,2))\nprint(lst) # [0, 2, 4, 6, 8, 10]\nst = set(range(0,11,2))\nprint(st) # {0, 2, 4, 6, 8, 10}\n```\n\n```python\n# syntax\nfor iterator in range(start, end, step):\n```\n\n**Ejemplo:**\n\n```python\nfor number in range(11):\n print(number) # imprime 0 a 10, no incluye 11.\n```\n\n### Bucles for anidados\n\nPodemos anidar un bucle dentro de otro; a esto se le llama bucle anidado.\n\n```python\n# syntax\nfor x in y:\n for t in x:\n print(t)\n```\n\n**Ejemplo:**\n\n```python\nperson = {\n 'first_name': 'Asabeneh',\n 'last_name': 'Yetayeh',\n 'age': 250,\n 'country': 'Finland',\n 'is_marred': True,\n 'skills': ['JavaScript', 'React', 'Node', 'MongoDB', 'Python'],\n 'address': {\n 'street': 'Space street',\n 'zipcode': '02210'\n }\n}\nfor key in person:\n if key == 'skills':\n for skill in person['skills']:\n print(skill)\n```\n\n### for y else\n\nSi queremos ejecutar un bloque de código al terminar el bucle, podemos usar la palabra clave `else`.\n\n```python\n# syntax\nfor iterator in range(start, end, step):\n do something\nelse:\n print('The loop ended')\n```\n\n**Ejemplo:**\n\n```python\nfor number in range(11):\n print(number) # prints 0 to 10, not including 11\nelse:\n print('The loop stops at', number)\n```\n\n### Sentencia pass\n\nEn Python, cuando se requiere una instrucción (por ejemplo después de `:`) pero no queremos ejecutar código, usamos `pass` para evitar errores. También sirve como marcador para rellenar más adelante.\n\n**Ejemplo:**\n\n```python\nfor number in range(6):\n pass\n```\n\n🌕 Has dado un gran paso — ¡bien hecho! Acabas de completar el desafío del Día 10; estás a 10 pasos en tu camino hacia lo grande. Ahora hagamos algunos ejercicios para entrenar la mente y los músculos.\n\n## 💻 Ejercicios - Día 10\n\n### Ejercicios: Nivel 1\n\n1. Implementa iteraciones de 0 a 10 usando while y for.\n2. Implementa iteraciones de 10 a 0 usando while y for.\n3. Escribe un bucle que llame a `print()` 7 veces para producir este triángulo:\n ```py\n #\n ##\n ###\n ####\n #####\n ######\n #######\n ```\n\n4. Usa bucles anidados para producir la siguiente salida:\n\n ```sh\n # # # # # # # #\n # # # # # # # #\n # # # # # # # #\n # # # # # # # #\n # # # # # # # #\n # # # # # # # #\n # # # # # # # #\n # # # # # # # #\n ```\n5. Usando un bucle, produce la siguiente salida:\n ```sh\n 0 x 0 = 0\n 1 x 1 = 1\n 2 x 2 = 4\n 3 x 3 = 9\n 4 x 4 = 16\n 5 x 5 = 25\n 6 x 6 = 36\n 7 x 7 = 49\n 8 x 8 = 64\n 9 x 9 = 81\n 10 x 10 = 100\n ```\n6. Recorre con for la lista `['Python', 'Numpy','Pandas','Django', 'Flask']` e imprime cada elemento.\n7. Recorre con for de 0 a 100 e imprime todos los números pares.\n8. Recorre con for de 0 a 100 e imprime todos los números impares.\n\n### Ejercicios: Nivel 2\n\n1. Usa un for para sumar los números de 0 a 100.\n ```sh\n The sum of all numbers is 5050.\n ```\n2. Usa un for para sumar por separado los impares y los pares de 0 a 100.\n ```sh\n The sum of all odd numbers is 2500. And the sum of all even numbers is 2550.\n ```\n\n### Ejercicios: Nivel 3\n\n1. Ve a la carpeta data y usa el archivo [countries.py](https://github.com/Asabeneh/30-Days-Of-Python/blob/master/data/countries.py). Itera los países y extrae aquellos que contienen la cadena `land`.\n2. Dada la lista `fruits = ['banana', 'orange', 'mango', 'lemon']`, invierte los elementos usando un bucle.\n3. Ve a la carpeta data y usa el archivo [countries-data.py](https://github.com/Asabeneh/30-Days-Of-Python/blob/master/data/countries-data.py).\n 1. ¿Cuántos idiomas distintos hay en los datos?\n 2. ¿Cuál es el idioma usado por más países?\n 3. Encuentra los diez países con mayor población.\n\n🎉 ¡Felicidades! 🎉\n\n[<< Día 9](./09_conditionals_sp.md) | [Día 11 >>](./11_functions_sp.md)"
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\n\n[<< Día 10](./10_loops_sp.md) | [Día 12 >>](./12_modules_sp.md)\n\n\n\n- [📘 Día 11](#-día-11)\n - [Funciones](#funciones)\n - [Definir funciones](#definir-funciones)\n - [Declarar y llamar a una función](#declarar-y-llamar-a-una-función)\n - [Función sin parámetros](#función-sin-parámetros)\n - [Funciones que retornan valores - Parte 1](#funciones-que-retornan-valores---parte-1)\n - [Funciones con parámetros](#funciones-con-parámetros)\n - [Pasar argumentos por clave y valor](#pasar-argumentos-por-clave-y-valor)\n - [Funciones que retornan valores - Parte 2](#funciones-que-retornan-valores---parte-2)\n - [Funciones con parámetros por defecto](#funciones-con-parámetros-por-defecto)\n - [Número arbitrario de argumentos](#número-arbitrario-de-argumentos)\n - [Parámetros por defecto y arbitrarios en funciones](#parámetros-por-defecto-y-arbitrarios-en-funciones)\n - [Función como parámetro de otra función](#función-como-parámetro-de-otra-función)\n - [💻 Ejercicios: Día 11](#-ejercicios-día-11)\n - [Ejercicios: Nivel 1](#ejercicios-nivel-1)\n - [Ejercicios: Nivel 2](#ejercicios-nivel-2)\n - [Ejercicios: Nivel 3](#ejercicios-nivel-3)\n\n# 📘 Día 11\n\n## Funciones\n\nHasta ahora hemos aprendido muchas funciones integradas de Python. En esta sección nos centraremos en funciones definidas por el usuario. ¿Qué es una función? Antes de crear funciones, entendamos qué es y por qué las necesitamos.\n\n### Definir funciones\n\nUna función es un bloque de código reutilizable o una sentencia de programación que realiza una tarea específica. Para definir o declarar una función, Python provee la palabra clave def. La sintaxis para definir funciones es la siguiente. El código dentro de la función solo se ejecuta cuando la llamamos o la invocamos.\n\n### Declarar y llamar a una función\n\nCuando creamos una función, decimos que la declaramos. Cuando la usamos, decimos que la llamamos o invocamos. Las funciones pueden tener parámetros o no.\n\n```py\n# Sintaxis\n# Declarar una función\ndef function_name():\n codes\n codes\n# Llamar a una función\nfunction_name()\n```\n\n### Función sin parámetros\n\nUna función puede declararse sin parámetros.\n\n**Ejemplo:**\n\n```py\ndef generate_full_name ():\n first_name = 'Asabeneh'\n last_name = 'Yetayeh'\n space = ' '\n full_name = first_name + space + last_name\n print(full_name)\ngenerate_full_name () # Llamar a una función\n\ndef add_two_numbers ():\n num_one = 2\n num_two = 3\n total = num_one + num_two\n print(total)\nadd_two_numbers()\n```\n\n### Funciones que retornan valores - Parte 1\n\nUna función también puede devolver un valor; si una función no tiene return, devuelve None. Reescribamos las funciones anteriores usando return. A partir de ahora, cuando llamemos a la función y la imprimamos, obtendremos un valor.\n\n```py\ndef generate_full_name ():\n first_name = 'Asabeneh'\n last_name = 'Yetayeh'\n space = ' '\n full_name = first_name + space + last_name\n return full_name\nprint(generate_full_name())\n\ndef add_two_numbers ():\n num_one = 2\n num_two = 3\n total = num_one + num_two\n return total\nprint(add_two_numbers())\n```\n\n### Funciones con parámetros\n\nEn una función podemos pasar diferentes tipos de datos (números, cadenas, booleanos, listas, tuplas, diccionarios o sets) como parámetros.\n\n- Parámetro único: si una función necesita un parámetro, la llamamos con un argumento.\n\n```py\n # Sintaxis\n # Declarar una función\n def function_name(parameter):\n codes\n codes\n # Llamar a la función\n print(function_name(argument))\n```\n\n**Ejemplo:**\n\n```py\ndef greetings (name):\n message = name + ', welcome to Python for Everyone!'\n return message\n\nprint(greetings('Asabeneh'))\n\ndef add_ten(num):\n ten = 10\n return num + ten\nprint(add_ten(90))\n\ndef square_number(x):\n return x * x\nprint(square_number(2))\n\ndef area_of_circle (r):\n PI = 3.14\n area = PI * r ** 2\n return area\nprint(area_of_circle(10))\n\ndef sum_of_numbers(n):\n total = 0\n for i in range(n+1):\n total+=i\n print(total)\nprint(sum_of_numbers(10)) # 55\nprint(sum_of_numbers(100)) # 5050\n```\n\n- Dos parámetros: una función puede no tener parámetros o tener uno o varios. Si necesita dos parámetros, la llamamos con dos argumentos.\n\n```py\n # Sintaxis\n # Declarar una función\n def function_name(para1, para2):\n codes\n codes\n # Llamar a la función\n print(function_name(arg1, arg2))\n```\n\n**Ejemplo:**\n\n```py\ndef generate_full_name (first_name, last_name):\n space = ' '\n full_name = first_name + space + last_name\n return full_name\nprint('Full Name: ', generate_full_name('Asabeneh','Yetayeh'))\n\ndef sum_two_numbers (num_one, num_two):\n sum = num_one + num_two\n return sum\nprint('Sum of two numbers: ', sum_two_numbers(1, 9))\n\ndef calculate_age (current_year, birth_year):\n age = current_year - birth_year\n return age;\n\nprint('Age: ', calculate_age(2021, 1819))\n\ndef weight_of_object (mass, gravity):\n weight = str(mass * gravity)+ ' N' # El valor necesita convertirse a cadena primero\n return weight\nprint('Weight of an object in Newtons: ', weight_of_object(100, 9.81))\n```\n\n### Pasar argumentos por clave y valor\n\nSi pasamos argumentos por clave=valor, el orden de los parámetros no importa.\n\n```py\n# Sintaxis\n# Declarar una función\ndef function_name(para1, para2):\n codes\n codes\n# Llamar a la función\nprint(function_name(para1 = 'John', para2 = 'Doe')) # el orden de los parámetros no importa\n```\n\n**Ejemplo:**\n\n```py\ndef print_fullname(firstname, lastname):\n space = ' '\n full_name = firstname + space + lastname\n print(full_name)\nprint(print_fullname(firstname = 'Asabeneh', lastname = 'Yetayeh'))\n\ndef add_two_numbers (num1, num2):\n total = num1 + num2\n print(total)\nprint(add_two_numbers(num2 = 3, num1 = 2)) # el orden no importa\n```\n\n### Funciones que retornan valores - Parte 2\n\nSi no retornamos un valor en una función, por defecto devuelve _None_. Para devolver un valor usamos la palabra clave _return_ seguida de la variable a retornar. Podemos devolver cualquier tipo de dato desde una función.\n\n- Devolver cadenas:\n **Ejemplo:**\n\n```py\ndef print_name(firstname):\n return firstname\nprint_name('Asabeneh') # Asabeneh\n\ndef print_full_name(firstname, lastname):\n space = ' '\n full_name = firstname + space + lastname\n return full_name\nprint_full_name(firstname='Asabeneh', lastname='Yetayeh')\n```\n\n- Devolver números:\n\n**Ejemplo:**\n\n```py\ndef add_two_numbers (num1, num2):\n total = num1 + num2\n return total\nprint(add_two_numbers(2, 3))\n\ndef calculate_age (current_year, birth_year):\n age = current_year - birth_year\n return age;\nprint('Age: ', calculate_age(2019, 1819))\n```\n\n- Devolver booleanos:\n **Ejemplo:**\n\n```py\ndef is_even (n):\n if n % 2 == 0:\n print('even')\n return True # la instrucción return detiene la ejecución adicional en la función\n return False\nprint(is_even(10)) # True\nprint(is_even(7)) # False\n```\n\n- Devolver listas:\n **Ejemplo:**\n\n```py\ndef find_even_numbers(n):\n evens = []\n for i in range(n + 1):\n if i % 2 == 0:\n evens.append(i)\n return evens\nprint(find_even_numbers(10))\n```\n\n### Funciones con parámetros por defecto\n\nA veces pasamos valores por defecto a los parámetros. Si no proporcionamos un argumento al llamar la función, se usa el valor por defecto.\n\n```py\n# Sintaxis\n# Declarar una función\ndef function_name(param = value):\n codes\n codes\n# Llamar a la función\nfunction_name()\nfunction_name(arg)\n```\n\n**Ejemplo:**\n\n```py\ndef greetings (name = 'Peter'):\n message = name + ', welcome to Python for Everyone!'\n return message\nprint(greetings())\nprint(greetings('Asabeneh'))\n\ndef generate_full_name (first_name = 'Asabeneh', last_name = 'Yetayeh'):\n space = ' '\n full_name = first_name + space + last_name\n return full_name\n\nprint(generate_full_name())\nprint(generate_full_name('David','Smith'))\n\ndef calculate_age (birth_year,current_year = 2021):\n age = current_year - birth_year\n return age;\nprint('Age: ', calculate_age(1821))\n\ndef weight_of_object (mass, gravity = 9.81):\n weight = str(mass * gravity)+ ' N' # gravedad promedio en la superficie de la Tierra\n return weight\nprint('Weight of an object in Newtons: ', weight_of_object(100)) # 9.81 - gravedad promedio en la Tierra\nprint('Weight of an object in Newtons: ', weight_of_object(100, 1.62)) # gravedad en la Luna\n```\n\n### Número arbitrario de argumentos\n\nSi no sabemos cuántos argumentos se pasarán a la función, podemos usar un parámetro con * para aceptar un número arbitrario de argumentos.\n\n```py\n# Sintaxis\n# Declarar una función\ndef function_name(*args):\n codes\n codes\n# Llamar a la función\nfunction_name(param1, param2, param3,..)\n```\n\n**Ejemplo:**\n\n```py\ndef sum_all_nums(*nums):\n total = 0\n for num in nums:\n total += num # equivalente a total = total + num\n return total\nprint(sum_all_nums(2, 3, 5)) # 10\n```\n\n### Parámetros por defecto y arbitrarios en funciones\n\n```py\ndef generate_groups (team,*args):\n print(team)\n for i in args:\n print(i)\nprint(generate_groups('Team-1','Asabeneh','Brook','David','Eyob'))\n```\n\n### Función como parámetro de otra función\n\n```py\n# Puedes pasar una función como argumento\ndef square_number (n):\n return n * n\ndef do_something(f, x):\n return f(x)\nprint(do_something(square_number, 3)) # 27\n```\n\n🌕 Has avanzado mucho. ¡Sigue así! Has completado el desafío del día 11 y ya llevas 11 pasos en el camino al éxito. Ahora realiza algunos ejercicios para ejercitar la mente y la práctica.\n\n## Testimonios\n\nEs hora de expresar tu opinión sobre el autor y 30DaysOfPython. Puedes dejar tu testimonio en este [enlace](https://testimonify.herokuapp.com/).\n\n## 💻 Ejercicios: Día 11\n\n### Ejercicios: Nivel 1\n\n1. Declara una función _add_two_numbers_. Debe aceptar dos parámetros y devolver su suma.\n2. La fórmula del área de un círculo es: area = π x r x r. Escribe una función _area_of_circle_ que la calcule.\n3. Escribe una función llamada add_all_nums que acepte un número arbitrario de argumentos y sume todos. Verifica que todos los elementos sean de tipo numérico. Si no, devuelve un mensaje apropiado.\n4. La temperatura en Celsius (°C) se puede convertir a Fahrenheit (°F) con: °F = (°C x 9/5) + 32. Escribe una función _convert_celsius_to_fahrenheit_.\n5. Escribe una función llamada check_season que acepte un mes y devuelva la estación: otoño, invierno, primavera o verano.\n6. Escribe una función llamada calculate_slope que devuelva la pendiente de una ecuación lineal.\n7. La ecuación cuadrática se calcula como: ax² + bx + c = 0. Escribe una función _solve_quadratic_eqn_ que calcule las soluciones.\n8. Declara una función llamada print_list que acepte una lista y imprima cada elemento.\n9. Declara una función llamada reverse_list que acepte un arreglo y devuelva su reverso (usa un bucle).\n\n```py\nprint(reverse_list([1, 2, 3, 4, 5]))\n# [5, 4, 3, 2, 1]\nprint(reverse_list1([\"A\", \"B\", \"C\"]))\n# [\"C\", \"B\", \"A\"]\n```\n\n10. Declara una función capitalize_list_items que acepte una lista y devuelva una lista con los elementos en mayúscula.\n11. Declara una función add_item que acepte una lista y un ítem. Debe devolver la lista con el ítem agregado al final.\n\n```py\nfood_staff = ['Potato', 'Tomato', 'Mango', 'Milk'];\nprint(add_item(food_staff, 'Meat')) # ['Potato', 'Tomato', 'Mango', 'Milk','Meat'];\nnumbers = [2, 3, 7, 9];\nprint(add_item(numbers, 5)) [2, 3, 7, 9, 5]\n```\n\n12. Declara una función remove_item que acepte una lista y un ítem. Debe devolver la lista con el ítem eliminado.\n\n```py\nfood_staff = ['Potato', 'Tomato', 'Mango', 'Milk'];\nprint(remove_item(food_staff, 'Mango')) # ['Potato', 'Tomato', 'Milk'];\nnumbers = [2, 3, 7, 9];\nprint(remove_item(numbers, 3)) # [2, 7, 9]\n```\n\n13. Declara una función sum_of_numbers que acepte un número y sume todos los números en ese rango.\n\n```py\nprint(sum_of_numbers(5)) # 15\nprint(sum_all_numbers(10)) # 55\nprint(sum_all_numbers(100)) # 5050\n```\n\n14. Declara una función sum_of_odds que acepte un número y sume todos los impares en ese rango.\n15. Declara una función sum_of_even que acepte un número y sume todos los pares en ese rango.\n\n### Ejercicios: Nivel 2\n\n1. Declara una función evens_and_odds que acepte un entero positivo y calcule la cantidad de pares e impares en ese número.\n\n```py\n print(evens_and_odds(100))\n # La cantidad de números pares es 50.\n # La cantidad de números impares es 50.\n```\n\n2. Llama a tu función factorial que acepte un entero y devuelva su factorial.\n3. Llama a tu función _is_empty_ que acepte un argumento y verifique si está vacío.\n4. Escribe distintas funciones que acepten listas y calculen: media, mediana, moda, rango, varianza y desviación estándar.\n\n### Ejercicios: Nivel 3\n\n1. Escribe una función is_prime que verifique si un número es primo.\n2. Escribe una función que verifique si todos los ítems en una lista son únicos.\n3. Escribe una función que verifique si todos los ítems en una lista son del mismo tipo de dato.\n4. Escribe una función que verifique si una variable proporcionada es un nombre de variable válido en Python.\n5. Accede al archivo de datos countries-data.py.\n\n- Crea una función llamada the_most_spoken_languages que devuelva las 10 o 20 lenguas más habladas en el mundo, ordenadas de mayor a menor.\n- Crea una función llamada the_most_populated_countries que devuelva los 10 o 20 países más poblados del mundo, ordenados de mayor a menor.\n\n🎉 ¡Felicidades! 🎉\n\n[<< Día 10](./10_loops_sp.md) | [Día 12 >>](./12_modules_sp.md)\n"
},
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"path": "Spanish/12_modules_sp.md",
"content": "
\n\n[<< Día 11](./11_functions_sp.md) | [Día 13 >>](./13_list_comprehension_sp.md)\n\n\n\n- [📘 Día 12](#-día-12)\n - [Módulos](#módulos)\n - [¿Qué es un módulo?](#¿qué-es-un-módulo?)\n - [Crear módulos](#crear-módulos)\n - [Importar módulos](#importar-módulos)\n - [Importar funciones desde un módulo](#importar-funciones-desde-un-módulo)\n - [Importar funciones y renombrarlas](#importar-funciones-y-renombrarlas)\n - [Importar módulos incorporados](#importar-módulos-incorporados)\n - [Módulo OS](#módulo-os)\n - [Módulo sys](#módulo-sys)\n - [Módulo statistics](#módulo-statistics)\n - [Módulo math](#módulo-math)\n - [Módulo string](#módulo-string)\n - [Módulo random](#módulo-random)\n - [💻 Ejercicios: Día 12](#-ejercicios-día-12)\n - [Ejercicios: Nivel 1](#ejercicios-nivel-1)\n - [Ejercicios: Nivel 2](#ejercicios-nivel-2)\n - [Ejercicios: Nivel 3](#ejercicios-nivel-3)\n\n# 📘 Día 12\n\n## Módulos\n\n### ¿Qué es un módulo?\n\nUn módulo es un archivo que contiene un conjunto de código o funciones que se pueden incluir en una aplicación. Un módulo puede ser un archivo con una sola variable, una función o una biblioteca de gran escala.\n\n### Crear módulos\n\nPara crear un módulo, escribimos código en un script de Python y lo guardamos con extensión .py. En la carpeta del proyecto crea un archivo llamado mymodule.py. Escribamos algo de código en ese archivo.\n\n```py\n# archivo mymodule.py\ndef generate_full_name(firstname, lastname):\n return firstname + ' ' + lastname\n```\n\nEn el directorio del proyecto crea un archivo main.py e importa mymodule.py.\n\n### Importar módulos\n\nPara importar archivos usamos la palabra clave import y el nombre del archivo.\n\n```py\n# archivo main.py\nimport mymodule\nprint(mymodule.generate_full_name('Asabeneh', 'Yetayeh')) # Asabeneh Yetayeh\n```\n\n### Importar funciones desde un módulo\n\nPodemos tener muchas funciones en un archivo y podemos importar cada una por separado.\n\n```py\n# archivo main.py\nfrom mymodule import generate_full_name, sum_two_nums, person, gravity\nprint(generate_full_name('Asabneh','Yetayeh'))\nprint(sum_two_nums(1,9))\nmass = 100\nweight = mass * gravity\nprint(weight)\nprint(person['firstname'])\n```\n\n### Importar funciones y renombrarlas\n\nDurante la importación también podemos renombrar nombres.\n\n```py\n# archivo main.py\nfrom mymodule import generate_full_name as fullname, sum_two_nums as total, person as p, gravity as g\nprint(fullname('Asabneh','Yetayeh'))\nprint(total(1, 9))\nmass = 100\nweight = mass * g\nprint(weight)\nprint(p)\nprint(p['firstname'])\n```\n\n## Importar módulos incorporados\n\nAl igual que otros lenguajes, podemos importar módulos usando la palabra clave import. A continuación importamos algunos módulos incorporados que usamos con frecuencia. Algunos módulos comunes son: math, datetime, os, sys, random, statistics, collections, json, re\n\n### Módulo OS\n\nEl módulo os de Python permite automatizar muchas tareas del sistema operativo. El módulo OS ofrece funciones para crear, cambiar directorio de trabajo, eliminar directorios (carpetas), obtener su contenido y reconocer/cambiar el directorio actual.\n\n```py\n# importar módulo\nimport os\n# crear directorio\nos.mkdir('directory_name')\n# cambiar el directorio actual\nos.chdir('path')\n# obtener el directorio actual\nos.getcwd()\n# eliminar directorio\nos.rmdir()\n```\n\n### Módulo sys\n\nEl módulo sys provee funciones y variables para interactuar con diferentes partes del entorno de ejecución de Python. La función sys.argv devuelve la lista de argumentos de la línea de comandos pasados al script de Python. El elemento en el índice 0 de esa lista es siempre el nombre del script, el índice 1 es el primer argumento pasado desde la línea de comandos.\n\nEjemplo archivo script.py:\n\n```py\nimport sys\n#print(sys.argv[0], argv[1],sys.argv[2]) # esta línea imprimirá: nombre_archivo argumento1 argumento2\nprint('Welcome {}. Enjoy {} challenge!'.format(sys.argv[1], sys.argv[2]))\n```\n\nPara ver cómo funciona el script, en la línea de comandos escribe:\n\n```sh\npython script.py Asabeneh 30DaysOfPython\n```\n\nResultado:\n\n```sh\nWelcome Asabeneh. Enjoy 30DayOfPython challenge!\n```\n\nAlgunos comandos útiles de sys:\n\n```py\n# salir del script\nsys.exit()\n# conocer el tamaño máximo de un entero\nsys.maxsize\n# conocer la ruta de módulos\nsys.path\n# conocer la versión de Python en uso\nsys.version\n```\n\n### Módulo statistics\n\nEl módulo statistics proporciona funciones de estadísticas para datos numéricos. Algunas funciones comunes definidas en este módulo: mean, median, mode, stdev, etc.\n\n```py\nfrom statistics import * # importar todo del módulo statistics\nages = [20, 20, 4, 24, 25, 22, 26, 20, 23, 22, 26]\nprint(mean(ages)) # ~22.9\nprint(median(ages)) # 23\nprint(mode(ages)) # 20\nprint(stdev(ages)) # ~2.3\n```\n\n### Módulo math\n\nContiene muchas operaciones matemáticas y constantes.\n\n```py\nimport math\nprint(math.pi) # 3.141592653589793, constante pi\nprint(math.sqrt(2)) # 1.4142135623730951, raíz cuadrada\nprint(math.pow(2, 3)) # 8.0, potencia\nprint(math.floor(9.81)) # 9, redondeo hacia abajo\nprint(math.ceil(9.81)) # 10, redondeo hacia arriba\nprint(math.log10(100)) # 2, logaritmo base 10\n```\n\nAhora que hemos importado el módulo math con muchas funciones útiles, podemos ver qué funciones contiene usando help(math) o dir(math). Si sólo queremos importar funciones específicas podemos hacerlo así:\n\n```py\nfrom math import pi\nprint(pi)\n```\n\nTambién podemos importar múltiples funciones:\n\n```py\nfrom math import pi, sqrt, pow, floor, ceil, log10\nprint(pi) # 3.141592653589793\nprint(sqrt(2)) # 1.4142135623730951\nprint(pow(2, 3)) # 8.0\nprint(floor(9.81)) # 9\nprint(ceil(9.81)) # 10\nprint(math.log10(100)) # 2\n```\n\nSi queremos importar todas las funciones del módulo matemático podemos usar *.\n\n```py\nfrom math import *\nprint(pi) # 3.141592653589793, constante pi\nprint(sqrt(2)) # 1.4142135623730951, raíz cuadrada\nprint(pow(2, 3)) # 8.0, potencia\nprint(floor(9.81)) # 9, redondeo hacia abajo\nprint(ceil(9.81)) # 10, redondeo hacia arriba\nprint(math.log10(100)) # 2\n```\n\nTambién podemos renombrar funciones al importarlas.\n\n```py\nfrom math import pi as PI\nprint(PI) # 3.141592653589793\n```\n\n### Módulo string\n\nEl módulo string es muy útil. Los siguientes ejemplos muestran algunos usos.\n\n```py\nimport string\nprint(string.ascii_letters) # abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ\nprint(string.digits) # 0123456789\nprint(string.punctuation) # !\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~\n```\n\n### Módulo random\n\nAhora que sabes importar módulos, familiaricémonos con random. El módulo random nos da números aleatorios entre 0 y 0.9999. El módulo tiene muchas funciones; aquí usamos random y randint.\n\n```py\nfrom random import random, randint\nprint(random()) # no necesita parámetros; devuelve un valor entre 0 y 0.9999\nprint(randint(5, 20)) # devuelve un entero aleatorio en [5, 20] (inclusive)\n```\n\n🌕 ¡Has llegado muy lejos. Sigue así! Acabas de completar el desafío del Día 12 y has dado 12 pasos hacia algo grandioso. Ahora ejercita tu mente y tus músculos.\n\n## 💻 Ejercicios: Día 12\n\n### Ejercicios: Nivel 1\n\n1. Escribe una función que genere un random_user_id de seis caracteres/dígitos.\n ```py\n print(random_user_id());\n '1ee33d'\n ```\n2. Modifica la tarea anterior. Declara una función llamada user_id_gen_by_user. No acepta argumentos, pero pide dos entradas: una es la cantidad de caracteres por ID y la otra es cuántos IDs generar.\n\n```py\nprint(user_id_gen_by_user()) # entrada del usuario: 5 5\n#salida:\n#kcsy2\n#SMFYb\n#bWmeq\n#ZXOYh\n#2Rgxf\n\nprint(user_id_gen_by_user()) # 16 5\n#1GCSgPLMaBAVQZ26\n#YD7eFwNQKNs7qXaT\n#ycArC5yrRupyG00S\n#UbGxOFI7UXSWAyKN\n#dIV0SSUTgAdKwStr\n```\n\n3. Escribe una función llamada rgb_color_gen. Debe generar un color RGB (cada valor en el rango 0-255).\n\n```py\nprint(rgb_color_gen())\n# rgb(125,244,255) - la salida debe estar en este formato\n```\n\n### Ejercicios: Nivel 2\n\n1. Escribe una función list_of_hexa_colors que devuelva una lista con cualquier cantidad de colores hexadecimales (seis dígitos hexadecimales después de #; el sistema hex usa 0-9 y a-f).\n2. Escribe una función list_of_rgb_colors que devuelva una lista con cualquier cantidad de colores RGB.\n3. Escribe una función generate_colors que pueda generar cualquier cantidad de colores hexadecimales o RGB.\n\n```py\n generate_colors('hexa', 3) # ['#a3e12f','#03ed55','#eb3d2b']\n generate_colors('hexa', 1) # ['#b334ef']\n generate_colors('rgb', 3) # ['rgb(5, 55, 175','rgb(50, 105, 100','rgb(15, 26, 80']\n generate_colors('rgb', 1) # ['rgb(33,79, 176)']\n```\n\n### Ejercicios: Nivel 3\n\n1. Llama a tu función shuffle_list, que recibe una lista y devuelve la lista mezclada.\n2. Escribe una función que devuelva una lista de siete números aleatorios únicos en el rango 0-9.\n\n🎉 ¡Felicidades! 🎉\n\n[<< Día 11](./11_functions_sp.md) | [Día 13 >>](./13_list_comprehension_sp.md)\n"
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"path": "Spanish/13_list_comprehension_sp.md",
"content": "
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30 Días de Python: Día 13 - Comprensiones de listas
\n\n[<< Día 12](./12_modules_sp.md) | [Día 14 >>](./14_higher_order_functions_sp.md)\n\n\n\n- [📘 Día 13](#📘-día-13)\n - [Comprensiones de listas](#comprensiones-de-listas)\n - [Funciones lambda](#funciones-lambda)\n - [Crear una función lambda](#crear-una-función-lambda)\n - [Funciones lambda dentro de otra función](#lambda-dentro-de-otra-función)\n - [💻 Ejercicios: Día 13](#💻-ejercicios-día-13)\n\n# 📘 Día 13\n\n## Comprensiones de listas\n\nEn Python, las comprensiones de listas son una forma concisa de crear listas a partir de secuencias. Es una manera corta de crear nuevas listas a partir de secuencias. Las comprensiones de listas son más rápidas que iterar sobre listas con un bucle for.\n\n```py\n# sintaxis\n[i for i in iterable if expresión]\n```\n\n**Ejemplo 1**\n\nPor ejemplo, si quieres convertir una cadena en una lista de caracteres, puedes hacerlo de varias formas. Veamos algunas:\n\n```py\n# un método\nlanguage = 'Python'\nlst = list(language) # convertir la cadena en lista\nprint(type(lst)) # list\nprint(lst) # ['P', 'y', 't', 'h', 'o', 'n']\n\n# segunda forma: comprensión de listas\nlst = [i for i in language]\nprint(type(lst)) # list\nprint(lst) # ['P', 'y', 't', 'h', 'o', 'n']\n```\n\n**Ejemplo 2**\n\nPor ejemplo, si quieres generar una lista de números:\n\n```py\n# generar números\nnumbers = [i for i in range(11)] # genera números de 0 a 10\nprint(numbers) # [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\n\n# también puedes hacer operaciones matemáticas durante la iteración\nsquares = [i * i for i in range(11)]\nprint(squares) # [0, 1, 4, 9, 16, 25, 36, 49, 64, 81, 100]\n\n# también se pueden generar listas de tuplas\nnumbers = [(i, i * i) for i in range(11)]\nprint(numbers) # [(0, 0), (1, 1), (2, 4), (3, 9), (4, 16), (5, 25)]\n```\n\n**Ejemplo 3**\n\nLas comprensiones de listas pueden combinarse con expresiones if:\n\n```py\n# generar números pares\neven_numbers = [i for i in range(21) if i % 2 == 0] # genera pares de 0 a 20\nprint(even_numbers) # [0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20]\n\n# generar números impares\nodd_numbers = [i for i in range(21) if i % 2 != 0] # genera impares de 0 a 20\nprint(odd_numbers) # [1, 3, 5, 7, 9, 11, 13, 15, 17, 19]\n\n# filtrar números: obtengamos los pares positivos\nnumbers = [-8, -7, -3, -1, 0, 1, 3, 4, 5, 7, 6, 8, 10]\npositive_even_numbers = [i for i in range(21) if i % 2 == 0 and i > 0]\nprint(positive_even_numbers) # [2, 4, 6, 8, 10, 12, 14, 16, 18, 20]\n\n# aplanar una lista 2D\nlist_of_lists = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]\nflattened_list = [number for row in list_of_lists for number in row]\nprint(flattened_list) # [1, 2, 3, 4, 5, 6, 7, 8, 9]\n```\n\n## Funciones lambda\n\nLas funciones lambda son pequeñas funciones anónimas sin nombre. Pueden aceptar cualquier número de argumentos, pero solo una expresión. Las funciones lambda son similares a las funciones anónimas en JavaScript. Son útiles cuando necesitamos una función anónima dentro de otra función.\n\n### Crear una función lambda\n\nPara crear una función lambda usamos la palabra clave lambda, seguido de uno o más parámetros y luego una expresión. La función lambda no usa return explícito; devuelve la expresión implícitamente.\n\n```py\n# sintaxis\nx = lambda param1, param2, param3: param1 + param2 + param3\nprint(x(arg1, arg2, arg3))\n```\n\n**Ejemplo:**\n\n```py\n# función nombrada\ndef add_two_nums(a, b):\n return a + b\n\nprint(add_two_nums(2, 3)) # 5\n\n# con lambda\nadd_two_nums = lambda a, b: a + b\nprint(add_two_nums(2, 3)) # 5\n\n# lambda autoejecutable\nprint((lambda a, b: a + b)(2, 3)) # 5\n\nsquare = lambda x: x ** 2\nprint(square(3)) # 9\ncube = lambda x: x ** 3\nprint(cube(3)) # 27\n\n# múltiples variables\nmultiple_variable = lambda a, b, c: a ** 2 - 3 * b + 4 * c\nprint(multiple_variable(5, 5, 3)) # 22\n```\n\n### Funciones lambda dentro de otra función\n\nUso de lambda dentro de otra función:\n\n```py\ndef power(x):\n return lambda n: x ** n\n\ncube = power(2)(3) # la función power ahora se usa con dos pares de paréntesis\nprint(cube) # 8\ntwo_power_of_five = power(2)(5)\nprint(two_power_of_five) # 32\n```\n\n🌕 Sigue con el buen trabajo. Mantente motivado; el cielo es tu límite. Has completado el desafío del Día 13 y has dado 13 pasos hacia algo grandioso. Ahora ejercita tu mente y sigue practicando.\n\n## 💻 Ejercicios: Día 13\n\n1. Usa una comprensión de listas para filtrar los números negativos y ceros de la siguiente lista:\n ```py\n numbers = [-4, -3, -2, -1, 0, 2, 4, 6]\n ```\n2. Aplana la siguiente lista de listas a una lista unidimensional:\n\n ```py\n list_of_lists = [[[1, 2, 3]], [[4, 5, 6]], [[7, 8, 9]]]\n\n Salida:\n [1, 2, 3, 4, 5, 6, 7, 8, 9]\n ```\n\n3. Crea la siguiente lista de tuplas usando una comprensión de listas:\n ```py\n [(0, 1, 0, 0, 0, 0, 0),\n (1, 1, 1, 1, 1, 1, 1),\n (2, 1, 2, 4, 8, 16, 32),\n (3, 1, 3, 9, 27, 81, 243),\n (4, 1, 4, 16, 64, 256, 1024),\n (5, 1, 5, 25, 125, 625, 3125),\n (6, 1, 6, 36, 216, 1296, 7776),\n (7, 1, 7, 49, 343, 2401, 16807),\n (8, 1, 8, 64, 512, 4096, 32768),\n (9, 1, 9, 81, 729, 6561, 59049),\n (10, 1, 10, 100, 1000, 10000, 100000)]\n ```\n4. Aplana la siguiente estructura en una nueva lista:\n ```py\n countries = [[('Finlandia', 'Helsinki')], [('Suecia', 'Estocolmo')], [('Noruega', 'Oslo')]]\n Salida:\n [['Finlandia', 'FIN', 'Helsinki'], ['Suecia', 'SWE', 'Estocolmo'], ['Noruega', 'NOR', 'Oslo']]\n ```\n5. Convierte la siguiente lista en una lista de diccionarios:\n ```py\n countries = [[('Finlandia', 'Helsinki')], [('Suecia', 'Estocolmo')], [('Noruega', 'Oslo')]]\n Salida:\n [{'País': 'Finlandia', 'Ciudad': 'Helsinki'},\n {'País': 'Suecia', 'Ciudad': 'Estocolmo'},\n {'País': 'Noruega', 'Ciudad': 'Oslo'}]\n ```\n6. Convierte la siguiente lista en una lista de cadenas concatenadas:\n ```py\n names = [[('Asabeneh', 'Yetayeh')], [('David', 'Smith')], [('Donald', 'Trump')], [('Bill', 'Gates')]]\n Salida:\n ['Asabeneh Yetayeh', 'David Smith', 'Donald Trump', 'Bill Gates']\n ```\n7. Escribe una función lambda que calcule la pendiente o la ordenada al origen de una función lineal.\n\n🎉 ¡Felicidades! 🎉\n\n[<< Día 12](./12_modules_sp.md) | [Día 14 >>](./14_higher_order_functions_sp.md)\n"
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"path": "Spanish/14_higher_order_functions_sp.md",
"content": "
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30 Días de Python: Día 14 - Funciones de orden superior
\n\n[<< Día 13](./13_list_comprehension_sp.md) | [Día 15 >>](./15_python_type_errors_cn_sp.md)\n\n\n\n- [📘 Día 14](#-día-14)\n - [Funciones de orden superior](#funciones-de-orden-superior)\n - [Funciones como parámetros](#funciones-como-parámetros)\n - [Funciones como valor de retorno](#funciones-como-valor-de-retorno)\n - [Closures en Python](#closures-en-python)\n - [Decoradores en Python](#decoradores-en-python)\n - [Crear decoradores](#crear-decoradores)\n - [Aplicar varios decoradores a una función](#aplicar-varios-decoradores-a-una-función)\n - [Aceptar parámetros en decoradores](#aceptar-parámetros-en-decoradores)\n - [Funciones integradas de orden superior](#funciones-integradas-de-orden-superior)\n - [Python - función map](#python---función-map)\n - [Python - función filter](#python---función-filter)\n - [Python - función reduce](#python---función-reduce)\n - [💻 Ejercicios: Día 14](#-ejercicios-día-14)\n - [Ejercicios: Básico](#ejercicios-básico)\n - [Ejercicios: Intermedio](#ejercicios-intermedio)\n - [Ejercicios: Avanzado](#ejercicios-avanzado)\n\n# 📘 Día 14\n\n## Funciones de orden superior\n\nEn Python, las funciones son tratadas como ciudadanos de primera clase; se pueden hacer las siguientes operaciones con funciones:\n\n- Una función puede recibir una o más funciones como parámetros\n- Una función puede ser el valor de retorno de otra función\n- Una función puede ser modificada\n- Una función puede asignarse a una variable\n\nEn esta sección discutiremos:\n\n1. Pasar funciones como parámetros\n2. Devolver funciones como valores de retorno\n3. Usar closures y decoradores en Python\n\n### Funciones como parámetros\n\n```py\ndef sum_numbers(nums): # función normal\n return sum(nums) # usa la función incorporada sum\n\ndef higher_order_function(f, lst): # pasar función como argumento\n summation = f(lst)\n return summation\nresult = higher_order_function(sum_numbers, [1, 2, 3, 4, 5])\nprint(result) # 15\n```\n\n### Funciones como valor de retorno\n\n```py\ndef square(x): # función que devuelve el cuadrado\n return x ** 2\n\ndef cube(x): # función que devuelve el cubo\n return x ** 3\n\ndef absolute(x): # función que devuelve el valor absoluto\n if x >= 0:\n return x\n else:\n return -(x)\n\ndef higher_order_function(type): # función de orden superior que devuelve una función\n if type == 'square':\n return square\n elif type == 'cube':\n return cube\n elif type == 'absolute':\n return absolute\n\nresult = higher_order_function('square')\nprint(result(3)) # 9\nresult = higher_order_function('cube')\nprint(result(3)) # 27\nresult = higher_order_function('absolute')\nprint(result(-3)) # 3\n```\n\nEn los ejemplos anteriores se observa que la función de orden superior devuelve distintas funciones según el parámetro pasado.\n\n## Closures en Python\n\nPython permite que una función anidada acceda al ámbito de su función envolvente externa. Esto se conoce como closure. Un closure en Python se crea al anidar una función dentro de otra función envolvente y devolver la función interna. Veamos un ejemplo.\n\n**Ejemplo:**\n\n```py\ndef add_ten():\n ten = 10\n def add(num):\n return num + ten\n return add\n\nclosure_result = add_ten()\nprint(closure_result(5)) # 15\nprint(closure_result(10)) # 20\n```\n\n## Decoradores en Python\n\nUn decorador es un patrón de diseño que permite añadir nueva funcionalidad a un objeto sin modificar su estructura. Los decoradores normalmente se usan aplicándolos antes de la definición de la función que se desea decorar.\n\n### Crear decoradores\n\nPara crear un decorador necesitamos una función externa que contenga una función envoltura interna.\n\n**Ejemplo:**\n\n```py\n# función normal\ndef greeting():\n return 'Welcome to Python'\n\ndef uppercase_decorator(function):\n def wrapper():\n func = function()\n make_uppercase = func.upper()\n return make_uppercase\n return wrapper\n\ng = uppercase_decorator(greeting)\nprint(g()) # WELCOME TO PYTHON\n\n# Implementando lo anterior con sintaxis de decorador\n\n'''Esta función decoradora es una función de orden superior que acepta una función como argumento'''\ndef uppercase_decorator(function):\n def wrapper():\n func = function()\n make_uppercase = func.upper()\n return make_uppercase\n return wrapper\n\n@uppercase_decorator\ndef greeting():\n return 'Welcome to Python'\nprint(greeting()) # WELCOME TO PYTHON\n```\n\n### Aplicar varios decoradores a una función\n\n```py\n'''Estas funciones decoradoras son funciones de orden superior que reciben funciones como argumento'''\n\n# primer decorador\ndef uppercase_decorator(function):\n def wrapper():\n func = function()\n make_uppercase = func.upper()\n return make_uppercase\n return wrapper\n\n# segundo decorador\ndef split_string_decorator(function):\n def wrapper():\n func = function()\n splitted_string = func.split()\n return splitted_string\n return wrapper\n\n@split_string_decorator\n@uppercase_decorator # en este caso el orden importa, ya que .upper() no funciona sobre una lista\ndef greeting():\n return 'Welcome to Python'\nprint(greeting()) # ['WELCOME', 'TO', 'PYTHON']\n```\n\n### Aceptar parámetros en decoradores\n\nA menudo necesitamos que nuestras funciones acepten parámetros; por eso definimos decoradores que también los aceptan.\n\n```py\ndef decorator_with_parameters(function):\n def wrapper_accepting_parameters(para1, para2, para3):\n function(para1, para2, para3)\n print(\"I live in {}\".format(para3))\n return wrapper_accepting_parameters\n\n@decorator_with_parameters\ndef print_full_name(first_name, last_name, country):\n print(\"I am {} {}. I love to teach.\".format(\n first_name, last_name, country))\n\nprint_full_name(\"Asabeneh\", \"Yetayeh\",'Finland')\n```\n\n## Funciones integradas de orden superior\n\nEn esta sección veremos algunas funciones integradas de orden superior como map(), filter() y reduce().\nLas funciones lambda se pueden pasar como argumentos; su caso de uso ideal es con map, filter y reduce.\n\n### Python - función map\n\nmap() es una función integrada que recibe una función y un iterable como parámetros.\n\n```py\n # sintaxis\n map(function, iterable)\n```\n\n**Ejemplo 1**\n\n```py\nnumbers = [1, 2, 3, 4, 5] # iterable\ndef square(x):\n return x ** 2\nnumbers_squared = map(square, numbers)\nprint(list(numbers_squared)) # [1, 4, 9, 16, 25]\n# Usemos lambda\nnumbers_squared = map(lambda x : x ** 2, numbers)\nprint(list(numbers_squared)) # [1, 4, 9, 16, 25]\n```\n\n**Ejemplo 2**\n\n```py\nnumbers_str = ['1', '2', '3', '4', '5'] # iterable\nnumbers_int = map(int, numbers_str)\nprint(list(numbers_int)) # [1, 2, 3, 4, 5]\n```\n\n**Ejemplo 3**\n\n```py\nnames = ['Asabeneh', 'Lidiya', 'Ermias', 'Abraham'] # iterable\n\ndef change_to_upper(name):\n return name.upper()\n\nnames_upper_cased = map(change_to_upper, names)\nprint(list(names_upper_cased)) # ['ASABENEH', 'LIDIYA', 'ERMIAS', 'ABRAHAM']\n\n# Usemos lambda\nnames_upper_cased = map(lambda name: name.upper(), names)\nprint(list(names_upper_cased)) # ['ASABENEH', 'LIDIYA', 'ERMIAS', 'ABRAHAM']\n```\n\nmap itera sobre el iterable y devuelve un nuevo iterable transformado.\n\n### Python - función filter\n\nfilter() llama a la función especificada que retorna un valor booleano para cada elemento del iterable y filtra los elementos que cumplen la condición.\n\n```py\n # sintaxis\n filter(function, iterable)\n```\n\n**Ejemplo 1**\n\n```py\n# filtremos solo los pares\nnumbers = [1, 2, 3, 4, 5] # iterable\n\ndef is_even(num):\n if num % 2 == 0:\n return True\n return False\n\neven_numbers = filter(is_even, numbers)\nprint(list(even_numbers)) # [2, 4]\n```\n\n**Ejemplo 2**\n\n```py\nnumbers = [1, 2, 3, 4, 5] # iterable\n\ndef is_odd(num):\n if num % 2 != 0:\n return True\n return False\n\nodd_numbers = filter(is_odd, numbers)\nprint(list(odd_numbers)) # [1, 3, 5]\n```\n\n```py\n# filtrar nombres largos\nnames = ['Asabeneh', 'Lidiya', 'Ermias', 'Abraham'] # iterable\ndef is_name_long(name):\n if len(name) > 7:\n return True\n return False\n\nlong_names = filter(is_name_long, names)\nprint(list(long_names)) # ['Asabeneh']\n```\n\n### Python - función reduce\n\nreduce() se define en el módulo functools; es necesario importarla desde allí. Al igual que map y filter, recibe una función y un iterable. Sin embargo, no devuelve otro iterable sino un único valor acumulado.\n\n**Ejemplo 1**\n\n```py\nnumbers_str = ['1', '2', '3', '4', '5'] # iterable\ndef add_two_nums(x, y):\n return int(x) + int(y)\n\ntotal = reduce(add_two_nums, numbers_str)\nprint(total) # 15\n```\n\n## 💻 Ejercicios: Día 14\n\n```py\ncountries = ['Estonia', 'Finland', 'Sweden', 'Denmark', 'Norway', 'Iceland']\nnames = ['Asabeneh', 'Lidiya', 'Ermias', 'Abraham']\nnumbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\n```\n\n### Ejercicios: Básico\n\n1. Explica la diferencia entre map, filter y reduce.\n2. Explica la diferencia entre funciones de orden superior, closures y decoradores.\n3. Define la función que llama (ver ejemplo).\n4. Imprime cada país de la lista countries usando un bucle for.\n5. Imprime cada nombre de la lista names usando un bucle for.\n6. Imprime cada número de la lista numbers usando un bucle for.\n\n### Ejercicios: Intermedio\n\n1. Usa map para convertir cada país en countries a mayúsculas y genera una nueva lista.\n2. Usa map para elevar al cuadrado cada número en numbers y genera una nueva lista.\n3. Usa map para convertir cada nombre en names a mayúsculas y genera una nueva lista.\n4. Usa filter para filtrar países que contienen 'land'.\n5. Usa filter para filtrar países con exactamente seis caracteres.\n6. Usa filter para filtrar países con seis o más caracteres.\n7. Usa filter para filtrar países que comienzan con 'E'.\n8. Encadena dos o más iteradores de lista (por ejemplo arr.map(callback).filter(callback).reduce(callback)).\n9. Declara una función get_string_lists que reciba una lista y devuelva una lista con solo los elementos de tipo cadena.\n10. Usa reduce para sumar todos los números en la lista numbers.\n11. Usa reduce para concatenar todos los países en una oración: Estonia, Finland, Sweden, Denmark, Norway, and Iceland are north European countries.\n12. Declara una función categorize_countries que retorne una lista de países que siguen un patrón común (puedes ver la lista de países en el archivo countries.js del repositorio, por ejemplo 'land', 'ia', 'island', 'stan').\n13. Crea una función que devuelva un diccionario donde las claves sean la primera letra de los nombres de país y el valor sea el número de países que comienzan con esa letra.\n14. Declara una función get_first_ten_countries que devuelva los primeros diez países de la lista countries.js en la carpeta data.\n15. Declara una función get_last_ten_countries que devuelva los últimos diez países de la lista.\n\n### Ejercicios: Avanzado\n\n1. Usando el archivo countries_data.py (https://github.com/Asabeneh/30-Days-Of-Python/blob/master/data/countries-data.py), completa lo siguiente:\n - Ordena los países por nombre, capital y población.\n - Ordena y obtiene los diez idiomas más usados.\n - Ordena y obtiene los diez países con mayor población.\n\n🎉 ¡Felicidades! 🎉\n\n[<< Día 13](./13_list_comprehension_sp.md) | [Día 15 >>](./15_python_type_errors_cn_sp.md)\n"
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"path": "Spanish/15_python_type_errors_sp.md",
"content": "# Desafío de programación Python: Día 15 - Errores (excepciones) en Python\n\n- [Día 15](#día-15)\n - [Tipos de error en Python](#tipos-de-error-en-python)\n - [SyntaxError (Error de sintaxis)](#syntaxerror-error-de-sintaxis)\n - [NameError (Error de nombre)](#nameerror-error-de-nombre)\n - [IndexError (Error de índice)](#indexerror-error-de-índice)\n - [ModuleNotFoundError (Módulo no encontrado)](#modulenotfounderror-módulo-no-encontrado)\n - [AttributeError (Error de atributo)](#attributeerror-error-de-atributo)\n - [KeyError (Error de clave)](#keyerror-error-de-clave)\n - [TypeError (Error de tipo)](#typeerror-error-de-tipo)\n - [ImportError (Error de importación)](#importerror-error-de-importación)\n - [ValueError (Error de valor)](#valueerror-error-de-valor)\n - [ZeroDivisionError (Error de división por cero)](#zerodivisionerror-error-de-división-por-cero)\n - [💻 Ejercicios - Día 15](#-ejercicios---día-15)\n\n# 📘 Día 15\n\n## Tipos de error en Python\n\nAl escribir código, con frecuencia cometemos errores tipográficos u otros errores comunes. Si nuestro código falla, el intérprete de Python muestra un mensaje que nos da retroalimentación sobre dónde ocurrió el problema y cuál es el tipo de error. A veces incluso sugiere posibles soluciones. Conocer los distintos tipos de errores en el lenguaje nos ayudará a depurar más rápido y a mejorar nuestras habilidades de programación.\n\nRevisemos los tipos de error más comunes uno por uno. Primero, abre el intérprete interactivo de Python. Ve a la terminal de tu equipo e ingresa 'python'. Se abrirá el intérprete interactivo de Python.\n\n### SyntaxError (Error de sintaxis)\n\n**Ejemplo 1: SyntaxError**\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> print 'hello world'\n File \"\", line 1\n print 'hello world'\n ^\nSyntaxError: Missing parentheses in call to 'print'. Did you mean print('hello world')?\n>>>\n```\n\nComo ves, cometimos un error de sintaxis porque olvidamos encerrar la cadena entre paréntesis; Python incluso sugiere la corrección. Arreglémoslo.\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> print 'hello world'\n File \"\", line 1\n print 'hello world'\n ^\nSyntaxError: Missing parentheses in call to 'print'. Did you mean print('hello world')?\n>>> print('hello world')\nhello world\n>>>\n```\n\nEse fue un SyntaxError. Tras corregirlo, el código se ejecuta correctamente. Veamos otros tipos de errores.\n\n### NameError (Error de nombre)\n\n**Ejemplo 1: NameError**\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> print(age)\nTraceback (most recent call last):\n File \"\", line 1, in \nNameError: name 'age' is not defined\n>>>\n```\n\nEl mensaje indica que el nombre age no está definido. En efecto, no hemos declarado age pero intentamos imprimirlo. Solucionémoslo declarando la variable y asignándole un valor.\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> print(age)\nTraceback (most recent call last):\n File \"\", line 1, in \nNameError: name 'age' is not defined\n>>> age = 25\n>>> print(age)\n25\n>>>\n```\n\nEse fue un NameError. Lo depuramos definiendo la variable.\n\n### IndexError (Error de índice)\n\n**Ejemplo 1: IndexError**\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> numbers = [1, 2, 3, 4, 5]\n>>> numbers[5]\nTraceback (most recent call last):\n File \"\", line 1, in \nIndexError: list index out of range\n>>>\n```\n\nEn este ejemplo Python lanzó un IndexError porque los índices válidos de la lista son 0 a 4; el índice 5 está fuera de rango.\n\n### ModuleNotFoundError (Módulo no encontrado)\n\n**Ejemplo 1: ModuleNotFoundError**\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> import maths\nTraceback (most recent call last):\n File \"\", line 1, in \nModuleNotFoundError: No module named 'maths'\n>>>\n```\n\nAquí añadí intencionadamente una 's' extra a math, lo que produjo un ModuleNotFoundError. Corrijámoslo quitando la 's'.\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> import maths\nTraceback (most recent call last):\n File \"\", line 1, in \nModuleNotFoundError: No module named 'maths'\n>>> import math\n>>>\n```\n\nLo hemos corregido y ahora podemos usar el módulo math.\n\n### AttributeError (Error de atributo)\n\n**Ejemplo 1: AttributeError**\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> import maths\nTraceback (most recent call last):\n File \"\", line 1, in \nModuleNotFoundError: No module named 'maths'\n>>> import math\n>>> math.PI\nTraceback (most recent call last):\n File \"\", line 1, in \nAttributeError: module 'math' has no attribute 'PI'\n>>>\n```\n\nAquí intenté acceder a math.PI en lugar de math.pi, lo que produjo un AttributeError porque ese atributo no existe. Corrijámoslo usando el nombre correcto:\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> import maths\nTraceback (most recent call last):\n File \"\", line 1, in \nModuleNotFoundError: No module named 'maths'\n>>> import math\n>>> math.PI\nTraceback (most recent call last):\n File \"\", line 1, in \nAttributeError: module 'math' has no attribute 'PI'\n>>> math.pi\n3.141592653589793\n>>>\n```\n\nAhora la llamada devuelve el valor esperado.\n\n### KeyError (Error de clave)\n\n**Ejemplo 1: KeyError**\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> users = {'name':'Asab', 'age':250, 'country':'Finland'}\n>>> users['name']\n'Asab'\n>>> users['county']\nTraceback (most recent call last):\n File \"\", line 1, in \nKeyError: 'county'\n>>>\n```\n\nAquí hay un error de ortografía en la clave usada para obtener un valor del diccionario. Es un KeyError; la solución es usar la clave correcta.\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> user = {'name':'Asab', 'age':250, 'country':'Finland'}\n>>> user['name']\n'Asab'\n>>> user['county']\nTraceback (most recent call last):\n File \"\", line 1, in \nKeyError: 'county'\n>>> user['country']\n'Finland'\n>>>\n```\n\nError depurado; el código devuelve el resultado esperado.\n\n### TypeError (Error de tipo)\n\n**Ejemplo 1: TypeError**\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> 4 + '3'\nTraceback (most recent call last):\n File \"\", line 1, in \nTypeError: unsupported operand type(s) for +: 'int' and 'str'\n>>>\n```\n\nEn este caso aparece un TypeError porque no podemos sumar un entero y una cadena. Una solución es convertir la cadena a int o float; otra es convertir el entero a cadena para concatenarlos. Probemos la primera solución:\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> 4 + '3'\nTraceback (most recent call last):\n File \"\", line 1, in \nTypeError: unsupported operand type(s) for +: 'int' and 'str'\n>>> 4 + int('3')\n7\n>>> 4 + float('3')\n7.0\n>>>\n```\n\nEl error desaparece y obtenemos el resultado esperado.\n\n### ImportError (Error de importación)\n\n**Ejemplo 1: ImportError**\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> from math import power\nTraceback (most recent call last):\n File \"\", line 1, in \nImportError: cannot import name 'power' from 'math'\n>>>\n```\n\nEl módulo math no tiene una función llamada power; la función correcta es pow. Corrijámoslo:\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> from math import power\nTraceback (most recent call last):\n File \"\", line 1, in \nImportError: cannot import name 'power' from 'math'\n>>> from math import pow\n>>> pow(2,3)\n8.0\n>>>\n```\n\n### ValueError (Error de valor)\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> int('12a')\nTraceback (most recent call last):\n File \"\", line 1, in \nValueError: invalid literal for int() with base 10: '12a'\n>>>\n```\n\nNo podemos convertir la cadena dada a número porque contiene la letra 'a'.\n\n### ZeroDivisionError (Error de división por cero)\n\n```python\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> 1/0\nTraceback (most recent call last):\n File \"\", line 1, in \nZeroDivisionError: division by zero\n>>>\n```\n\nNo podemos dividir un número por cero.\n\nHemos revisado varios tipos de errores en Python; para más información, consulta la documentación oficial sobre excepciones en Python. Si te acostumbras a leer los mensajes de error, podrás corregir tus bugs rápidamente y convertirte en un mejor programador.\n\n🌕 Vas progresando. Has completado la mitad del camino hacia algo genial. Ahora haz algunos ejercicios para entrenar tu cerebro y tus manos.\n\n## 💻 Ejercicios - Día 15\n\n1. Abre tu intérprete interactivo de Python y prueba todos los ejemplos mostrados en esta sección.\n\n🎉 ¡Felicidades! 🎉\n\n[<< Día 14](./14_higher_order_functions_sp.md) | [Día 16 >>](./16_python_datetime_sp.md)"
},
{
"path": "Spanish/16_python_datetime_sp.md",
"content": "# 30 Días de Python: Día 16 - datetime en Python\n\n- [Día 16](#-día-16)\n - [Python *datetime*](#python-datetime)\n - [Obtener información de *datetime*](#obtener-información-de-datetime)\n - [Formatear fecha con *strftime*](#formatear-fecha-con-strftime)\n - [Convertir cadena a fecha con *strptime*](#convertir-cadena-a-fecha-con-strptime)\n - [Usar *date* desde *datetime*](#usar-date-desde-datetime)\n - [Representar tiempo con objetos *time*](#representar-tiempo-con-objetos-time)\n - [Calcular la diferencia entre dos puntos en el tiempo](#calcular-la-diferencia-entre-dos-puntos-en-el-tiempo)\n - [Calcular diferencias con *timedelta*](#calcular-diferencias-con-timedelta)\n - [💻 Ejercicios - Día 16](#-ejercicios---día-16)\n\n# 📘 Día 16\n\n## Python *datetime*\n\nPython tiene un módulo _datetime_ para trabajar con fechas y horas.\n\n```py\nimport datetime\nprint(dir(datetime))\n['MAXYEAR', 'MINYEAR', '__builtins__', '__cached__', '__doc__', '__file__', '__loader__', '__name__', '__package__', '__spec__', 'date', 'datetime', 'datetime_CAPI', 'sys', 'time', 'timedelta', 'timezone', 'tzinfo']\n```\n\nCon los comandos incorporados dir o help puedes ver las funciones disponibles de un módulo. Como ves, el módulo datetime tiene muchas clases y funciones; nos centraremos en _date_, _datetime_, _time_ y _timedelta_. Veámoslas una a una.\n\n### Obtener información de *datetime*\n\n```py\nfrom datetime import datetime\nnow = datetime.now()\nprint(now) # 2021-07-08 07:34:46.549883\nday = now.day # 8\nmonth = now.month # 7\nyear = now.year # 2021\nhour = now.hour # 7\nminute = now.minute # 38\nsecond = now.second\ntimestamp = now.timestamp()\nprint(day, month, year, hour, minute)\nprint('timestamp', timestamp)\nprint(f'{day}/{month}/{year}, {hour}:{minute}') # 8/7/2021, 7:38\n```\n\nEl timestamp, o Unix timestamp, es el número de segundos transcurridos desde el 1 de enero de 1970 UTC.\n\n### Formatear fecha con *strftime*\n\n```py\nfrom datetime import datetime\nnew_year = datetime(2020, 1, 1)\nprint(new_year) # 2020-01-01 00:00:00\nday = new_year.day\nmonth = new_year.month\nyear = new_year.year\nhour = new_year.hour\nminute = new_year.minute\nsecond = new_year.second\nprint(day, month, year, hour, minute) #1 1 2020 0 0\nprint(f'{day}/{month}/{year}, {hour}:{minute}') # 1/1/2020, 0:0\n\n```\n\nUsa el método *strftime* para formatear fechas y horas; la documentación de formatos está [aquí](https://strftime.org/).\n\n```py\nfrom datetime import datetime\n# fecha y hora actual\nnow = datetime.now()\nt = now.strftime(\"%H:%M:%S\")\nprint(\"Hora:\", t)\ntime_one = now.strftime(\"%m/%d/%Y, %H:%M:%S\")\n# formato mm/dd/YY H:M:S\nprint(\"Formato uno:\", time_one)\ntime_two = now.strftime(\"%d/%m/%Y, %H:%M:%S\")\n# formato dd/mm/YY H:M:S\nprint(\"Formato dos:\", time_two)\n```\n\n```sh\nHora: 01:05:01\nFormato uno: 12/05/2019, 01:05:01\nFormato dos: 05/12/2019, 01:05:01\n```\n\nA continuación se muestran los símbolos de _strftime_ usados para formatear tiempos, como se ve en la imagen de referencia.\n\n\n\n### Convertir cadena a fecha con *strptime*\nAquí hay una [guía](https://www.programiz.com/python-programming/datetime/strptimet) que ayuda a entender los formatos.\n\n```py\nfrom datetime import datetime\ndate_string = \"5 December, 2019\"\nprint(\"date_string =\", date_string)\ndate_object = datetime.strptime(date_string, \"%d %B, %Y\")\nprint(\"date_object =\", date_object)\n```\n\n```sh\ndate_string = 5 December, 2019\ndate_object = 2019-12-05 00:00:00\n```\n\n### Usar *date* desde *datetime*\n\n```py\nfrom datetime import date\nd = date(2020, 1, 1)\nprint(d)\nprint('Fecha actual:', d.today()) # fecha actual\n# objeto date de hoy\ntoday = date.today()\nprint(\"Año actual:\", today.year) # 2019\nprint(\"Mes actual:\", today.month) # 12\nprint(\"Día actual:\", today.day) # 5\n```\n\n### Representar tiempo con objetos *time*\n\n```py\nfrom datetime import time\n# time(hour = 0, minute = 0, second = 0)\na = time()\nprint(\"a =\", a)\n# time(hour, minute y second)\nb = time(10, 30, 50)\nprint(\"b =\", b)\n# time(hour, minute y second)\nc = time(hour=10, minute=30, second=50)\nprint(\"c =\", c)\n# time(hour, minute, second, microsecond)\nd = time(10, 30, 50, 200555)\nprint(\"d =\", d)\n```\n\nSalida: \na = 00:00:00 \nb = 10:30:50 \nc = 10:30:50 \nd = 10:30:50.200555\n\n### Calcular la diferencia entre dos puntos en el tiempo\n\n```py\ntoday = date(year=2019, month=12, day=5)\nnew_year = date(year=2020, month=1, day=1)\ntime_left_for_newyear = new_year - today\n# Tiempo hasta año nuevo: 27 days, 0:00:00\nprint('Tiempo hasta año nuevo: ', time_left_for_newyear)\n\nt1 = datetime(year = 2019, month = 12, day = 5, hour = 0, minute = 59, second = 0)\nt2 = datetime(year = 2020, month = 1, day = 1, hour = 0, minute = 0, second = 0)\ndiff = t2 - t1\nprint('Tiempo hasta año nuevo:', diff) # Tiempo hasta año nuevo: 26 days, 23:01:00\n```\n\n### Calcular diferencias con *timedelta*\n\n```py\nfrom datetime import timedelta\nt1 = timedelta(weeks=12, days=10, hours=4, seconds=20)\nt2 = timedelta(days=7, hours=5, minutes=3, seconds=30)\nt3 = t1 - t2\nprint(\"t3 =\", t3)\n```\n\n```sh\ndate_string = 5 December, 2019\ndate_object = 2019-12-05 00:00:00\nt3 = 86 days, 22:56:50\n```\n\n🌕 Eres increíble. Has avanzado 16 pasos hacia la excelencia. Ahora haz algunos ejercicios para entrenar tu mente y tus manos.\n\n## 💻 Ejercicios - Día 16\n\n1. Obtén el día, mes, año, hora, minuto y timestamp actuales desde el módulo datetime.\n2. Formatea la fecha actual con el formato: \"%m/%d/%Y, %H:%M:%S\"\n3. Hoy es 5 de diciembre de 2019. Convierte esa cadena de fecha a un objeto datetime.\n4. Calcula la diferencia entre ahora y el próximo año nuevo.\n5. Calcula la diferencia entre el 1 de enero de 1970 y ahora.\n6. Piensa: ¿para qué puedes usar el módulo datetime? Por ejemplo:\n - Análisis de series temporales\n - Obtener timestamps para eventos en una aplicación\n - Añadir la fecha de publicación en un blog\n\n🎉 ¡Felicidades! 🎉\n\n[<< Día 15](./15_python_type_errors_sp.md) | [Día 17 >>](./17_exception_handling_sp.md)"
},
{
"path": "Spanish/17_exception_handling_sp.md",
"content": "# 30 Días de Python: Día 17 - Manejo de excepciones\n\n- [Día 17](#-día-17)\n - [Manejo de excepciones](#manejo-de-excepciones)\n - [Empacar y desempacar parámetros en Python](#empacar-y-desempacar-parámetros-en-python)\n - [Desempaquetado](#desempaquetado)\n - [Desempaquetar listas](#desempaquetar-listas)\n - [Desempaquetar diccionarios](#desempaquetar-diccionarios)\n - [Empaquetado](#empaquetado)\n - [Empaquetar listas](#empaquetar-listas)\n - [Empaquetar diccionarios](#empaquetar-diccionarios)\n - [Expandir en Python](#expandir-en-python)\n - [Enumerar (enumerate)](#enumerar-enumerate)\n - [Zip](#zip)\n - [Ejercicios: Día 17](#ejercicios-día-17)\n\n# 📘 Día 17\n\n## Manejo de excepciones\n\nPython utiliza _try_ y _except_ para manejar errores de forma elegante. Salir de forma controlada (o manejar errores con elegancia) es una buena práctica: el programa detecta una condición de error y la maneja adecuadamente, normalmente mostrando un mensaje descriptivo en la terminal o en un registro. Las excepciones suelen deberse a factores externos al programa (entrada errónea, nombre de archivo incorrecto, archivo no encontrado, fallos de I/O, etc.). El manejo adecuado de excepciones evita que las aplicaciones se bloqueen.\n\nEn la sección anterior hemos cubierto los distintos tipos de errores en Python. Si usamos _try_ y _except_ correctamente, podemos impedir que esos errores hagan que el programa falle.\n\n\n\n```py\ntry:\n # si todo va bien, se ejecuta el código en este bloque\nexcept:\n # si ocurre un error, se ejecuta el código en este bloque\n```\n\n**Ejemplo:**\n\n```py\ntry:\n print(10 + '5')\nexcept:\n print('Ocurrió un error')\n```\n\nEn el ejemplo anterior, el segundo operando es una cadena. Podemos convertirlo a int o float para sumarlo a un número; si no lo hacemos, se ejecutará el bloque _except_.\n\n**Ejemplo:**\n\n```py\ntry:\n name = input('Introduce tu nombre:')\n year_born = input('¿En qué año naciste?:')\n age = 2019 - year_born\n print(f'Eres {name}. Tu edad es {age}.')\nexcept:\n print('Ocurrió un error')\n```\n\n```sh\nOcurrió un error\n```\n\nEn el ejemplo anterior, se ejecuta el bloque de excepción, pero no sabemos exactamente qué pasó. Para identificar el problema podemos capturar tipos de excepción concretos.\n\nEn el siguiente ejemplo capturamos y mostramos el tipo de error:\n\n```py\ntry:\n name = input('Introduce tu nombre:')\n year_born = input('¿En qué año naciste?:')\n age = 2019 - year_born\n print(f'Eres {name}. Tu edad es {age}.')\nexcept TypeError:\n print('Se produjo un error de tipo (TypeError)')\nexcept ValueError:\n print('Se produjo un ValueError')\nexcept ZeroDivisionError:\n print('Se produjo una división por cero (ZeroDivisionError)')\n```\n\n```sh\nIntroduce tu nombre:Asabeneh\n¿En qué año naciste?:1920\nSe produjo un error de tipo (TypeError)\n```\n\nEn el ejemplo anterior la salida será _TypeError_. Ahora añadamos bloques adicionales:\n\n```py\ntry:\n name = input('Introduce tu nombre:')\n year_born = input('¿En qué año naciste?:')\n age = 2019 - int(year_born)\n print(f'Eres {name}. Tu edad es {age}.')\nexcept TypeError:\n print('Se produjo un error de tipo (TypeError)')\nexcept ValueError:\n print('Se produjo un ValueError')\nexcept ZeroDivisionError:\n print('Se produjo una división por cero (ZeroDivisionError)')\nelse:\n print('Este bloque se ejecuta normalmente después de try')\nfinally:\n print('Este bloque siempre se ejecuta.')\n```\n\n```sh\nIntroduce tu nombre:Asabeneh\n¿En qué año naciste?:1920\nEres Asabeneh. Tu edad es 99.\nEste bloque se ejecuta normalmente después de try\nEste bloque siempre se ejecuta.\n```\n\nTambién podemos simplificar el manejo de excepción así:\n\n```py\ntry:\n name = input('Introduce tu nombre:')\n year_born = input('¿En qué año naciste?:')\n age = 2019 - int(year_born)\n print(f'Eres {name}. Tu edad es {age}.')\nexcept Exception as e:\n print(e)\n```\n\n## Empacar y desempacar parámetros en Python\n\nUsamos dos operadores:\n\n- * para tuplas/listas\n- ** para diccionarios\n\nVeamos un ejemplo. Supongamos que una función acepta parámetros separados, pero nosotros tenemos una lista. Podemos desempaquetarla y convertirla en argumentos.\n\n### Desempaquetado\n\n#### Desempaquetar listas\n\n```py\ndef sum_of_five_nums(a, b, c, d, e):\n return a + b + c + d + e\n\nlst = [1, 2, 3, 4, 5]\nprint(sum_of_five_nums(lst)) # TypeError: sum_of_five_nums() missing 4 required positional arguments: 'b', 'c', 'd', and 'e'\n```\n\nAl ejecutar lo anterior ocurre un error porque la función espera números separados, no una lista. Desempaquetemos la lista:\n\n```py\ndef sum_of_five_nums(a, b, c, d, e):\n return a + b + c + d + e\n\nlst = [1, 2, 3, 4, 5]\nprint(sum_of_five_nums(*lst)) # 15\n```\n\nTambién podemos usar desempaquetado con range(), que acepta inicio y fin:\n\n```py\nnumbers = range(2, 7) # llamada normal con parámetros separados\nprint(list(numbers)) # [2, 3, 4, 5, 6]\nargs = [2, 7]\nnumbers = range(*args) # llamada usando los parámetros desempaquetados desde la lista\nprint(list(numbers)) # [2, 3, 4, 5, 6]\n```\n\nTambién podemos usar desempaquetado en asignaciones:\n\n```py\ncountries = ['Finland', 'Sweden', 'Norway', 'Denmark', 'Iceland']\nfin, sw, nor, *rest = countries\nprint(fin, sw, nor, rest) # Finland Sweden Norway ['Denmark', 'Iceland']\nnumbers = [1, 2, 3, 4, 5, 6, 7]\none, *middle, last = numbers\nprint(one, middle, last) # 1 [2, 3, 4, 5, 6] 7\n```\n\n#### Desempaquetar diccionarios\n\n```py\ndef unpacking_person_info(name, country, city, age):\n return f'{name} vive en {city}, {country}. Tiene {age} años.'\ndct = {'name':'Asabeneh', 'country':'Finland', 'city':'Helsinki', 'age':250}\nprint(unpacking_person_info(**dct)) # Asabeneh vive en Helsinki, Finland. Tiene 250 años.\n```\n\n### Empaquetado\n\nA veces no sabemos cuántos argumentos nos pasarán a una función. Podemos usar empaquetado para aceptar un número variable de argumentos.\n\n### Empaquetar listas\n\n```py\ndef sum_all(*args):\n s = 0\n for i in args:\n s += i\n return s\nprint(sum_all(1, 2, 3)) # 6\nprint(sum_all(1, 2, 3, 4, 5, 6, 7)) # 28\n```\n\n#### Empaquetar diccionarios\n\n```py\ndef packing_person_info(**kwargs):\n # comprobar el tipo de kwargs: es un dict\n # print(type(kwargs))\n # imprimir los pares clave-valor\n for key in kwargs:\n print(f\"{key} = {kwargs[key]}\")\n return kwargs\n\nprint(packing_person_info(name=\"Asabeneh\",\n country=\"Finland\", city=\"Helsinki\", age=250))\n```\n\n```sh\nname = Asabeneh\ncountry = Finland\ncity = Helsinki\nage = 250\n{'name': 'Asabeneh', 'country': 'Finland', 'city': 'Helsinki', 'age': 250}\n```\n\n## Expandir en Python\n\nAl igual que en JavaScript, Python permite expandir listas usando el operador *. Veámoslo:\n\n```py\nlst_one = [1, 2, 3]\nlst_two = [4, 5, 6, 7]\nlst = [0, *lst_one, *lst_two]\nprint(lst) # [0, 1, 2, 3, 4, 5, 6, 7]\n```\n\n## Enumerar (enumerate)\n\nSi necesitamos los índices de una lista, usamos la función integrada enumerate.\n\n```py\nfor index, item in enumerate([20, 30, 40]):\n print(index, item)\n```\n\n```py\nfor index, i in enumerate(countries):\n print('hola')\n if i == 'Finland':\n print(f'El país {i} está en el índice {index}')\n```\n\n```sh\n0 20\n1 30\n2 40\n```\n\n## Zip\n\nA veces necesitamos combinar listas. Observa el ejemplo:\n\n```py\nfruits = ['banana', 'orange', 'mango', 'lemon', 'lime'] \nvegetables = ['Tomato', 'Potato', 'Cabbage','Onion', 'Carrot']\nfruits_and_veges = []\nfor f, v in zip(fruits, vegetables):\n fruits_and_veges.append({'fruit':f, 'veg':v})\n\nprint(fruits_and_veges)\n```\n\n```sh\n[{'fruit': 'banana', 'veg': 'Tomato'}, {'fruit': 'orange', 'veg': 'Potato'}, {'fruit': 'mango', 'veg': 'Cabbage'}, {'fruit': 'lemon', 'veg': 'Onion'}, {'fruit': 'lime', 'veg': 'Carrot'}]\n```\n\n## Ejercicios: Día 17\n\n1. Crea en _countries.py_ funciones que usen los datos de _countries_data.py_:\n - una función para encontrar los 10 idiomas más usados\n - una función para encontrar los 10 países más poblados\n\n🎉 ¡Felicidades! 🎉\n\n[<< Día 16](./16_python_datetime_sp.md) | [Día 18 >>](./18_regular_expressions_sp.md)"
},
{
"path": "Spanish/18_regular_expressions_sp.md",
"content": "# 30 Días de Python: Día 18 - Expresiones regulares\n\n- [Día 18](#-día-18)\n - [Expresiones regulares](#expresiones-regulares)\n - [Módulo *re*](#módulo-re)\n - [Métodos en el módulo *re*](#métodos-en-el-módulo-re)\n - [Match (coincidencia al inicio)](#match-coincidencia-al-inicio)\n - [Search (búsqueda)](#search-búsqueda)\n - [Buscar todas las coincidencias con *findall*](#buscar-todas-las-coincidencias-con-findall)\n - [Reemplazar subcadenas](#reemplazar-subcadenas)\n - [Usar RegEx para dividir el texto](#usar-regex-para-dividir-texto)\n - [Construir patrones RegEx](#construir-patrones-regex)\n - [Corchetes](#corchetes)\n - [Caracteres de escape en RegEx (\\\\)](#caracteres-de-escape-en-regex)\n - [Una o más veces (+)](#una-o-más-veces-+)\n - [Punto (.)](#punto-)\n - [Cero o más veces (*)](#cero-o-más-veces-)\n - [Cero o una vez (?)](#cero-o-una-vez-?)\n - [Cuantificadores en RegEx](#cuantificadores-en-regex)\n - [Circunflejo (^) en RegEx](#circunflejo-^)\n - [💻 Ejercicios: Día 18](#-ejercicios-día-18)\n - [Ejercicios: Nivel 1](#ejercicios-nivel-1)\n - [Ejercicios: Nivel 2](#ejercicios-nivel-2)\n - [Ejercicios: Nivel 3](#ejercicios-nivel-3)\n\n# 📘 Día 18\n\n## Expresiones regulares\n\nLas expresiones regulares (RegEx) son cadenas de texto especiales que ayudan a encontrar patrones en los datos. RegEx se puede usar para comprobar la existencia de ciertos patrones en diferentes tipos de datos. Para usar RegEx en Python debemos importar el módulo llamado *re*.\n\n### Módulo *re*\n\nUna vez importado el módulo, podemos usarlo para detectar o buscar patrones.\n\n```py\nimport re\n```\n\n### Métodos en el módulo *re*\n\nPara buscar patrones usamos diferentes conjuntos de caracteres y funciones de *re*, que permiten buscar coincidencias dentro de una cadena.\n\n- *re.match()*: busca solo al inicio de la cadena; devuelve un objeto Match si hay coincidencia, sino None.\n- *re.search*: busca en cualquier parte de la cadena (incluyendo textos multilínea); devuelve el primer objeto Match encontrado o None.\n- *re.findall*: devuelve una lista con todas las coincidencias.\n- *re.split*: acepta una cadena y la divide en los puntos donde hay coincidencia, devolviendo una lista.\n- *re.sub*: reemplaza una o más coincidencias en una cadena.\n\n#### Match (coincidencia al inicio)\n\n```py\n# sintaxis\nre.match(substring, string, re.I)\n# substring es una cadena o patrón, string es el texto donde buscamos, re.I indica ignorar mayúsculas/minúsculas\n```\n\n```py\nimport re\n\ntxt = 'I love to teach python and javaScript'\n# Devuelve un objeto Match con span y match\nmatch = re.match('I love to teach', txt, re.I)\nprint(match) # \n# Podemos usar span para obtener la posición inicial y final como tupla\nspan = match.span()\nprint(span) # (0, 15)\n# Tomamos inicio y fin desde span\nstart, end = span\nprint(start, end) # 0, 15\nsubstring = txt[start:end]\nprint(substring) # I love to teach\n```\n\nDel ejemplo anterior se ve que el patrón buscado es *I love to teach*. La función match **solo** devuelve un objeto si el texto comienza con ese patrón.\n\n```py\nimport re\n\ntxt = 'I love to teach python and javaScript'\nmatch = re.match('I like to teach', txt, re.I)\nprint(match) # None\n```\n\nEsa cadena no comienza con *I like to teach*, por eso match devuelve None.\n\n#### Search (búsqueda)\n\n```py\n# sintaxis\nre.search(substring, string, re.I)\n# substring es un patrón, string es el texto donde buscamos, re.I es la bandera para ignorar mayúsculas/minúsculas\n```\n\n```py\nimport re\n\ntxt = '''Python is the most beautiful language that a human being has ever created.\nI recommend python for a first programming language'''\n\n# Devuelve un objeto Match con span y match\nmatch = re.search('first', txt, re.I)\nprint(match) # \n# Podemos usar span para obtener inicio y fin como tupla\nspan = match.span()\nprint(span) # (100, 105)\n# Tomamos inicio y fin\nstart, end = span\nprint(start, end) # 100 105\nsubstring = txt[start:end]\nprint(substring) # first\n```\n\nComo puedes ver, search es más potente que match porque busca en todo el texto. search devuelve la primera coincidencia; para obtener todas las coincidencias usamos findall.\n\n#### Buscar todas las coincidencias con *findall*\n\n*findall()* devuelve todas las coincidencias como una lista.\n\n```py\ntxt = '''Python is the most beautiful language that a human being has ever created.\nI recommend python for a first programming language'''\n\n# Devuelve una lista\nmatches = re.findall('language', txt, re.I)\nprint(matches) # ['language', 'language']\n```\n\nLa palabra *language* aparece dos veces en el texto. Practiquemos más: vamos a buscar 'Python' y 'python' en el texto:\n\n```py\ntxt = '''Python is the most beautiful language that a human being has ever created.\nI recommend python for a first programming language'''\n\n# Devuelve una lista\nmatches = re.findall('python', txt, re.I)\nprint(matches) # ['Python', 'python']\n```\n\nUsando re.I se ignora mayúsculas/minúsculas. Si no usamos la bandera, podemos escribir el patrón de otras formas:\n\n```py\ntxt = '''Python is the most beautiful language that a human being has ever created.\nI recommend python for a first programming language'''\n\nmatches = re.findall('Python|python', txt)\nprint(matches) # ['Python', 'python']\n\n#\nmatches = re.findall('[Pp]ython', txt)\nprint(matches) # ['Python', 'python']\n```\n\n#### Reemplazar subcadenas\n\n```py\ntxt = '''Python is the most beautiful language that a human being has ever created.\nI recommend python for a first programming language'''\n\nmatch_replaced = re.sub('Python|python', 'JavaScript', txt, re.I)\nprint(match_replaced) # JavaScript is the most beautiful language that a human being has ever created.\n# o bien\nmatch_replaced = re.sub('[Pp]ython', 'JavaScript', txt, re.I)\nprint(match_replaced) # JavaScript is the most beautiful language that a human being has ever created.\n```\n\nOtro ejemplo: el siguiente texto es difícil de leer por los símbolos '%'. Reemplazarlos por cadena vacía limpia el texto.\n\n```py\ntxt = '''%I a%m te%%a%%che%r% a%n%d %% I l%o%ve te%ach%ing. \nT%he%re i%s n%o%th%ing as r%ewarding a%s e%duc%at%i%ng a%n%d e%m%p%ow%er%ing p%e%o%ple.\nI fo%und te%a%ching m%ore i%n%t%er%%es%ting t%h%an any other %jobs. \nD%o%es thi%s m%ot%iv%a%te %y%o%u to b%e a t%e%a%cher?'''\n\nmatches = re.sub('%', '', txt)\nprint(matches)\n```\n\n```sh\nI am teacher and I love teaching.\nThere is nothing as rewarding as educating and empowering people. \nI found teaching more interesting than any other jobs. Does this motivate you to be a teacher?\n```\n\n## Usar RegEx para dividir el texto\n\n```py\ntxt = '''I am teacher and I love teaching.\nThere is nothing as rewarding as educating and empowering people.\nI found teaching more interesting than any other jobs.\nDoes this motivate you to be a teacher?'''\nprint(re.split('\\n', txt)) # dividir usando \\n - salto de línea\n```\n\n```sh\n['I am teacher and I love teaching.', 'There is nothing as rewarding as educating and empowering people.', 'I found teaching more interesting than any other jobs.', 'Does this motivate you to be a teacher?']\n```\n\n## Construir patrones RegEx\n\nPara declarar una cadena usamos comillas simples o dobles. Para declarar un patrón RegEx usamos una cadena raw, escrita como r''.\nEl siguiente patrón reconoce solo 'apple' en minúsculas; para ignorar mayúsculas/minúsculas reescribimos el patrón o añadimos la bandera re.I.\n\n```py\nimport re\n\nregex_pattern = r'apple'\ntxt = 'Apple and banana are fruits. An old cliche says an apple a day a doctor way has been replaced by a banana a day keeps the doctor far far away. '\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['apple']\n\n# Para ignorar mayúsculas/minúsculas, añadimos la bandera\nmatches = re.findall(regex_pattern, txt, re.I)\nprint(matches) # ['Apple', 'apple']\n# o podemos usar un conjunto de caracteres\nregex_pattern = r'[Aa]pple' # esto permite Apple o apple\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['Apple', 'apple']\n```\n\n* []: un conjunto de caracteres\n - [a-c] significa a o b o c\n - [a-z] cualquier letra de a a z\n - [A-Z] cualquier letra de A a Z\n - [0-3] 0 o 1 o 2 o 3\n - [0-9] cualquier dígito del 0 al 9\n - [A-Za-z0-9] cualquier carácter alfanumérico: a-z, A-Z o 0-9\n\n### Corchetes\n\nPractiquemos más con corchetes. Recuerda usar re.I para búsquedas sin distinción entre mayúsculas y minúsculas.\n\n```py\nregex_pattern = r'[Aa]pple|[Bb]anana' # Apple o apple o Banana o banana\ntxt = 'Apple and banana are fruits. An old cliche says an apple a day a doctor way has been replaced by a banana a day keeps the doctor far far away.'\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['Apple', 'banana', 'apple', 'banana']\n```\n\nUsando corchetes y alternación:\n```py\nregex_pattern = r'[a-zA-Z0-9]' # caracteres a-z, A-Z, 0-9\ntxt = 'Apple and banana are fruits. An old cliche says an apple a day a doctor way has been replaced by a banana a day keeps the doctor far far away.'\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['A', 'p', 'p', 'l', 'e', 'a', 'n', 'd', 'b', 'a', 'n', 'a', 'n', 'a', 'a', 'r', 'e',...]\n\nregex_pattern = r'\\d' # \\d es un metacarácter que representa dígitos\ntxt = 'This regular expression example was made on December 6, 2019 and revised on July 8, 2021'\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['6', '2', '0', '1', '9', '8', '2', '0', '2', '1']\n\nregex_pattern = r'\\d+' # \\d+ dígitos uno o más\ntxt = 'This regular expression example was made on December 6, 2019 and revised on July 8, 2021'\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['6', '2019', '8', '2021']\n```\n\n### Caracteres de escape en RegEx (\\\\)\n\n```py\nregex_pattern = r'\\d+' # \\d dígito, + uno o más\ntxt = 'This regular expression example was made on December 6, 2019 and revised on July 8, 2021'\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['6', '2019', '8', '2021']\n```\n\nPara buscar la barra invertida '\\' en sí usamos doble backslash:\n```py\nregex_pattern = r'\\\\d' # busca literal '\\d'\ntxt = 'This regular expression example was made on December 6, 2019 and revised on July 8, 2021'\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # []\n```\n\nSi no hay '\\d' literal en el texto, no se encuentran coincidencias.\n\n### Una o más veces (+)\n\n```py\nregex_pattern = r'\\d+' # \\d dígito, + uno o más\ntxt = 'This regular expression example was made on December 6, 2019 and revised on July 8, 2021'\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['6', '2019', '8', '2021']\n```\n\n### Punto (.)\n\n```py\nregex_pattern = r'[a].' # a seguido de cualquier carácter (excepto nueva línea)\ntxt = '''Apple and banana are fruits'''\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['an', 'an', 'an', 'a ', 'ar']\n\nregex_pattern = r'[a].+' # a seguido de cualquier carácter una o más veces\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['and banana are fruits']\n```\n\n### Cero o más veces (*)\n\nCero o más. Observa con atención el ejemplo.\n\n```py\nregex_pattern = r'[a].*' # a seguido de cualquier carácter cero o más veces\ntxt = '''Apple and banana are fruits'''\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['and banana are fruits']\n```\n\n### Cero o una vez (?)\n\nCero o una vez: puede existir o no.\n\n```py\ntxt = '''I am not sure if there is a convention how to write the word e-mail.\nSome people write it as email others may write it as Email or E-mail.'''\nregex_pattern = r'[Ee]-?mail' # ? indica cero o una vez\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['e-mail', 'email', 'Email', 'E-mail']\n```\n\n### Cuantificadores en RegEx\n\nCon llaves podemos especificar la longitud del patrón:\n```py\ntxt = 'This regular expression example was made on December 6, 2019 and revised on July 8, 2021'\nregex_pattern = r'\\d{4}' # exactamente 4 dígitos\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['2019', '2021']\n\ntxt = 'This regular expression example was made on December 6, 2019 and revised on July 8, 2021'\nregex_pattern = r'\\d{1,4}' # entre 1 y 4 dígitos\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['6', '2019', '8', '2021']\n```\n\n### Circunflejo (^) en RegEx\n\n- Indicar inicio\n\n```py\ntxt = 'This regular expression example was made on December 6, 2019 and revised on July 8, 2021'\nregex_pattern = r'^This' # ^ indica que empieza con 'This'\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['This']\n```\n\n- Negación dentro de corchetes\n\n```py\ntxt = 'This regular expression example was made on December 6, 2019 and revised on July 8, 2021'\nregex_pattern = r'[^A-Za-z ]+' # ^ dentro de [] significa negación: no A-Z, no a-z, no espacio\nmatches = re.findall(regex_pattern, txt)\nprint(matches) # ['6,', '2019', '8,', '2021']\n```\n\n## 💻 Ejercicios: Día 18\n\n### Ejercicios: Nivel 1\n\n1. ¿Qué es una expresión regular?\n2. ¿Qué es una variable de expresión regular (regex variable)?\n3. Recrea patrones que:\n a) Encuentren citas que contengan la palabra *talent* en un libro,\n b) Encuentren fechas en formato _DD-MM-YYYY_, por ejemplo 12-01-2021,\n c) Encuentren verbos en tiempo -ing en un texto.\n\n### Ejercicios: Nivel 2\n\n1. Escribe un patrón que valide un nombre de variable válido en Python.\n2. Limpia el siguiente texto eliminando etiquetas HTML.\n```python\ntext = '''\nHTML\nHypertext Markup Language (HTML) is the standard markup language for documents designed to be displayed in a web browser. It can be assisted by technologies such as Cascading Style Sheets (CSS) and scripting languages such as JavaScript.\n\nWeb browsers receive HTML documents from a web server or from local storage and render the documents into multimedia web pages. HTML describes the structure of a web page semantically and originally included cues for the appearance of the document.\n\nHTML elements are the building blocks of HTML pages. With HTML constructs, images and other objects such as interactive forms may be embedded into the rendered page. HTML provides a means to create structured documents by denoting structural semantics for text such as headings, paragraphs, lists, links, quotes and other items. HTML elements are delineated by tags, written using angle brackets. Tags such as and directly introduce content into the page. Other tags such as
surround and provide information about document text and may include other tags as sub-elements. Browsers do not display the HTML tags, but use them to interpret the content of the page.\n\nHTML can embed programs written in a scripting language such as JavaScript, which affects the behavior and content of web pages. Inclusion of CSS defines the look and layout of content. The World Wide Web Consortium (W3C), former maintainer of the HTML and current maintainer of the CSS standards, has encouraged the use of CSS over explicit presentational HTML since 1997.\n'''\n```\n\n### Ejercicios: Nivel 3\n\n1. Limpia el siguiente texto y, tras limpiarlo, calcula las tres palabras más frecuentes:\n\n```python\nparagraph = '''I love teaching. If you do not love teaching what else can you love. I love Python if you do not love something which can give you all the capabilities to develop an application what else can you love.'''\n```\n\n2. El siguiente texto contiene varias direcciones de correo electrónico. Escribe un patrón que encuentre o extraiga las direcciones de email válidas:\n\n```py\nemail_address = '''\nasabeneh@gmail.com\nalex@yahoo.com\nkofi@yahoo.com\ndoe@arc.gov\nasabeneh.com\nasabeneh@gmail\nalex@yahoo\n'''\n```\n\n🎉 ¡Felicidades! 🎉\n\n[<< Día 17](./17_exception_handling_sp.md) | [Día 19 >>](./19_file_handling_sp.md)"
},
{
"path": "Spanish/19_file_handling_sp.md",
"content": "# 30 Días de Python: Día 19 - Manejo de archivos\n\n- [Día 19](#-día-19)\n - [Manejo de archivos](#manejo-de-archivos)\n - [Abrir un archivo para lectura](#abrir-un-archivo-para-lectura)\n - [Abrir un archivo para escritura y actualización](#abrir-un-archivo-para-escritura-y-actualización)\n - [Eliminar archivos](#eliminar-archivos)\n - [Tipos de archivos](#tipos-de-archivos)\n - [Archivos con extensión txt](#archivos-con-extensión-txt)\n - [Archivos con extensión json](#archivos-con-extensión-json)\n - [Convertir JSON a diccionario](#convertir-json-a-diccionario)\n - [Convertir diccionario a JSON](#convertir-diccionario-a-json)\n - [Guardar como archivo JSON](#guardar-como-archivo-json)\n - [Archivos con extensión csv](#archivos-con-extensión-csv)\n - [Archivos con extensión xlsx](#archivos-con-extensión-xlsx)\n - [Archivos con extensión xml](#archivos-con-extensión-xml)\n - [💻 Ejercicios: Día 19](#-ejercicios-día-19)\n - [Ejercicios: Nivel 1](#ejercicios-nivel-1)\n - [Ejercicios: Nivel 2](#ejercicios-nivel-2)\n - [Ejercicios: Nivel 3](#ejercicios-nivel-3)\n\n# 📘 Día 19\n\n## Manejo de archivos\n\nHasta ahora hemos visto distintos tipos de datos en Python. Normalmente almacenamos datos en distintos formatos de archivo. Además de manejar archivos, en esta sección veremos diferentes formatos (.txt, .json, .xml, .csv, .tsv, .excel). Primero, familiaricémonos con el manejo de archivos usando un formato común (.txt).\n\nEl manejo de archivos es una parte importante de la programación; nos permite crear, leer, actualizar y eliminar archivos. En Python usamos la función incorporada _open()_ para manipular archivos.\n\n```py\n# sintaxis\nopen('filename', mode) # mode(r, a, w, x, t, b) puede ser lectura, escritura o actualización\n```\n\n- \"r\" - lectura - valor por defecto. Abre el archivo solo para lectura; si no existe genera un error.\n- \"a\" - append (añadir) - abre el archivo para agregar contenido al final; crea el archivo si no existe.\n- \"w\" - escritura - abre el archivo para escribir, sobrescribe si existe; crea el archivo si no existe.\n- \"x\" - crear - crea el archivo; si existe genera un error.\n- \"t\" - texto - valor por defecto. Modo texto.\n- \"b\" - binario - modo binario (por ejemplo para imágenes).\n\n### Abrir un archivo para lectura\n\nEl modo por defecto de _open_ es lectura, así que no es necesario especificar 'r' o 'rt'. He creado un archivo llamado reading_file_example.txt en el directorio files. Veamos:\n\n```py\nf = open('./files/reading_file_example.txt')\nprint(f) # <_io.TextIOWrapper name='./files/reading_file_example.txt' mode='r' encoding='UTF-8'>\n```\n\nComo en el ejemplo, al imprimir el objeto archivo obtenemos información sobre él. Un archivo abierto permite distintos métodos de lectura: _read()_, _readline_, _readlines_. Debemos cerrar el archivo con _close()_ cuando terminemos.\n\n- _read()_: lee todo el texto como una cadena. Podemos limitar el número de caracteres pasando un entero a *read(number)*.\n\n```py\nf = open('./files/reading_file_example.txt')\ntxt = f.read()\nprint(type(txt))\nprint(txt)\nf.close()\n```\n\n```sh\n# salida\n\nThis is an example to show how to open a file and read.\nThis is the second line of the text.\n```\n\nEn lugar de imprimir todo el texto, podemos leer solamente los primeros 10 caracteres:\n\n```py\nf = open('./files/reading_file_example.txt')\ntxt = f.read(10)\nprint(type(txt))\nprint(txt)\nf.close()\n```\n\n```sh\n# salida\n\nThis is an\n```\n\n- _readline()_: lee solo la primera línea\n\n```py\nf = open('./files/reading_file_example.txt')\nline = f.readline()\nprint(type(line))\nprint(line)\nf.close()\n```\n\n```sh\n# salida\n\nThis is an example to show how to open a file and read.\n```\n\n- _readlines()_: lee todo el texto línea por línea y devuelve una lista de líneas\n\n```py\nf = open('./files/reading_file_example.txt')\nlines = f.readlines()\nprint(type(lines))\nprint(lines)\nf.close()\n```\n\n```sh\n# salida\n\n['This is an example to show how to open a file and read.\\n', 'This is the second line of the text.']\n```\n\nOtra forma de obtener todas las líneas como lista es usar _splitlines()_:\n\n```py\nf = open('./files/reading_file_example.txt')\nlines = f.read().splitlines()\nprint(type(lines))\nprint(lines)\nf.close()\n```\n\n```sh\n# salida\n\n['This is an example to show how to open a file and read.', 'This is the second line of the text.']\n```\n\nDebemos cerrar los archivos después de abrirlos. Es fácil olvidarse; por eso existe la construcción _with_ que cierra automáticamente:\n\n```py\nwith open('./files/reading_file_example.txt') as f:\n lines = f.read().splitlines()\n print(type(lines))\n print(lines)\n```\n\n```sh\n# salida\n\n['This is an example to show how to open a file and read.', 'This is the second line of the text.']\n```\n\n### Abrir un archivo para escritura y actualización\n\nPara escribir en un archivo hay que pasar el modo a _open()_:\n\n- \"a\" - append - añade al final; crea el archivo si no existe.\n- \"w\" - write - sobrescribe el contenido; crea el archivo si no existe.\n\nAñadamos texto al archivo que hemos estado leyendo:\n\n```py\nwith open('./files/reading_file_example.txt','a') as f:\n f.write('Este texto debe añadirse al final')\n```\n\nSi el archivo no existe, el siguiente ejemplo creará uno nuevo:\n\n```py\nwith open('./files/writing_file_example.txt','w') as f:\n f.write('Este texto será escrito en el nuevo archivo creado')\n```\n\n### Eliminar archivos\n\nComo vimos anteriormente, podemos crear y eliminar directorios con el módulo _os_. Para eliminar archivos también usamos _os_.\n\n```py\nimport os\nos.remove('./files/example.txt')\n```\n\nSi el archivo no existe, remove lanzará un error, por lo que es mejor comprobar:\n\n```py\nimport os\nif os.path.exists('./files/example.txt'):\n os.remove('./files/example.txt')\nelse:\n print('El archivo no existe')\n```\n\n## Tipos de archivos\n\n### Archivos con extensión txt\n\nLos archivos _txt_ son un formato muy común; ya vimos su uso más arriba. Ahora pasemos a JSON.\n\n### Archivos con extensión json\n\nJSON significa JavaScript Object Notation. Es básicamente una representación en cadena de un objeto JavaScript o de un diccionario Python.\n\n_Ejemplo:_\n\n```py\n# diccionario\nperson_dct= {\n \"name\":\"Asabeneh\",\n \"country\":\"Finland\",\n \"city\":\"Helsinki\",\n \"skills\":[\"JavaScript\", \"React\",\"Python\"]\n}\n# JSON: la forma en cadena del diccionario\nperson_json = \"{'name': 'Asabeneh', 'country': 'Finland', 'city': 'Helsinki', 'skills': ['JavaScrip', 'React', 'Python']}\"\n# Usamos triple comillas para que sea multilínea y más legible\nperson_json = '''{\n \"name\":\"Asabeneh\",\n \"country\":\"Finland\",\n \"city\":\"Helsinki\",\n \"skills\":[\"JavaScript\", \"React\",\"Python\"]\n}'''\n```\n\n### Convertir JSON a diccionario\n\nPara convertir JSON a diccionario importamos el módulo json y usamos _loads_.\n\n```py\nimport json\n# JSON\nperson_json = '''{\n \"name\": \"Asabeneh\",\n \"country\": \"Finland\",\n \"city\": \"Helsinki\",\n \"skills\": [\"JavaScript\", \"React\", \"Python\"]\n}'''\n# Convertir la cadena JSON a diccionario\nperson_dct = json.loads(person_json)\nprint(type(person_dct))\nprint(person_dct)\nprint(person_dct['name'])\n```\n\n```sh\n# salida\n\n{'name': 'Asabeneh', 'country': 'Finland', 'city': 'Helsinki', 'skills': ['JavaScrip', 'React', 'Python']}\nAsabeneh\n```\n\n### Convertir diccionario a JSON\n\nPara convertir un diccionario a JSON usamos _dumps_.\n\n```py\nimport json\n# diccionario en Python\nperson = {\n \"name\": \"Asabeneh\",\n \"country\": \"Finland\",\n \"city\": \"Helsinki\",\n \"skills\": [\"JavaScript\", \"React\", \"Python\"]\n}\n# convertir diccionario a cadena JSON\nperson_json = json.dumps(person, indent=4) # indent puede ser 2, 4, 8; formatea la salida\nprint(type(person_json))\nprint(person_json)\n```\n\n```sh\n# salida\n\n{\n \"name\": \"Asabeneh\",\n \"country\": \"Finland\",\n \"city\": \"Helsinki\",\n \"skills\": [\n \"JavaScript\",\n \"React\",\n \"Python\"\n ]\n}\n```\n\n### Guardar como archivo JSON\n\nTambién podemos guardar los datos en un archivo JSON:\n\n```py\nimport json\n# diccionario en Python\nperson = {\n \"name\": \"Asabeneh\",\n \"country\": \"Finland\",\n \"city\": \"Helsinki\",\n \"skills\": [\"JavaScript\", \"React\", \"Python\"]\n}\nwith open('./files/json_example.json', 'w', encoding='utf-8') as f:\n json.dump(person, f, ensure_ascii=False, indent=4)\n```\n\nEn el ejemplo usamos encoding y ensure_ascii para manejar caracteres no ASCII. Ejemplo con caracteres no ASCII:\n\n```py\nimport json\nperson = {\n \"name\": \"Mark Firenze\",\n \"country\": \"Spain\",\n \"city\": \"Madrid\",\n \"skills\": [\"JavaScript\", \"React\", \"Python\"]\n}\nwith open('./files/json_example.json', 'w', encoding='utf-8') as f:\n json.dump(person, f, ensure_ascii=False, indent=4)\n```\n\nLeamos el archivo JSON que acabamos de crear:\n\n```py\nimport json\nwith open('./files/json_example.json', 'r', encoding='utf-8') as f:\n person = json.load(f)\n print(person)\n```\n\n```sh\n# salida\n{'name': 'Mark Firenze', 'country': 'Spain', 'city': 'Madrid', 'skills': ['JavaScript', 'React', 'Python']}\n```\n\n### Archivos con extensión csv\n\nCSV significa Comma Separated Values (valores separados por comas). Es un formato sencillo para datos tabulares (como hojas de cálculo o bases de datos) muy común en ciencia de datos.\n\n_Ejemplo CSV:_\n\n```csv\n\"name\",\"country\",\"city\",\"skills\"\n\"Asabeneh\",\"Finland\",\"Helsinki\",\"JavaScript\"\n```\n\nEjemplo de lectura:\n\n```py\nimport csv\nwith open('./files/csv_example.csv') as f:\n csv_reader = csv.reader(f, delimiter=',') # w+ crea el archivo si no existe\n line_count = 0\n for row in csv_reader:\n if line_count == 0:\n print(f'Encabezados: {\", \".join(row)}')\n line_count += 1\n else:\n print(f'{row[0]} viene de {row[1]}, {row[2]}. Conoce {row[3]}')\n line_count += 1\n print(f'Procesadas {line_count} líneas.')\n```\n\n```sh\n# salida:\nEncabezados: name, country, city, skills\nAsabeneh viene de Finland, Helsinki. Conoce JavaScript\nProcesadas 2 líneas.\n```\n\nTambién podemos escribir CSV:\n\n```py\nimport csv\nwith open('./files/csv_example.csv', 'w', encoding='UTF8', newline='') as f:\n writer = csv.writer(f)\n # escribir encabezados\n writer.writerow(['name', 'country', 'city', 'skills'])\n # escribir datos\n writer.writerow(['Asabeneh', 'Finland', 'Helsinki', 'JavaScript'])\n```\n\n### Archivos con extensión xlsx\n\nPara leer archivos Excel necesitamos instalar la librería xlrd (u otras alternativas). Ejemplo:\n\n```py\nimport xlrd\nexcel_book = xlrd.open_workbook('sample.xls')\nprint(excel_book.nsheets)\nprint(excel_book.sheet_names)\n```\n\n### Archivos con extensión xml\n\nXML es un lenguaje de marcado similar a HTML. Permite etiquetas personalizadas y se usa para datos estructurados. En Python hay varias librerías; aquí usamos xml.etree.ElementTree.\n\n_Ejemplo XML:_\n\n```xml\n\n\n Asabeneh\n Finland\n Helsinki\n \n JavaScript\n React\n Python\n \n\n```\n\nUsamos xml.etree.ElementTree para parsear:\n\n```py\nimport xml.etree.ElementTree as ET\ntree = ET.parse('./files/xml_example.xml')\nroot = tree.getroot()\nprint('Etiqueta raíz:', root.tag)\nprint('Atributos:', root.attrib)\nfor child in root:\n print('Campo: ', child.tag)\n```\n\n```sh\n# salida\nEtiqueta raíz: person\nAtributos: {'gender': 'female'}\nCampo: name\nCampo: country\nCampo: city\nCampo: skills\n```\n\nObtener más detalles:\n\n```py\nimport xml.etree.ElementTree as ET\ntree = ET.parse('./files/xml_example.xml')\nroot = tree.getroot()\nprint('Etiqueta raíz:', root.tag)\nprint('Atributos:', root.attrib)\nfor child in root:\n print('Campo: ', child.tag)\n if child.tag != 'skills':\n print(child.text)\n else:\n for skill in child:\n print(skill.text)\n```\n\n```sh\n# salida\nEtiqueta raíz: person\nAtributos: {'gender': 'female'}\nfield: name\nAsabeneh\nfield: country\nFinland\nfield: city\nHelsinki\nfield: skills\nJavaScript\nReact\nPython\n```\n\n## 💻 Ejercicios: Día 19\n\n### Ejercicios: Nivel 1\n\n1. Escribe una función que reciba un parámetro (nombre de archivo) y cuente el número de palabras del archivo.\n2. Lee el archivo obama_speech.txt y cuenta las palabras.\n3. Lee michelle_obama_speech.txt y cuenta las palabras.\n4. Lee donald_speech.txt y cuenta las palabras.\n5. Lee melina_trump_speech.txt y cuenta las palabras.\n\n### Ejercicios: Nivel 2\n\n1. Extrae todos los archivos Python del directorio del curso:\n a) Recorre la carpeta 30DaysOfPython, extrae todos los archivos .py y guarda sus nombres en files_list.txt\n b) Crea un script llamado find_python.py que pueda ejecutarse desde la línea de comandos\n c) Añade una opción --version para manejar argumentos de línea de comandos\n\n### Ejercicios: Nivel 3\n\n1. Crea un archivo JSON a partir del siguiente dataset:\n ```py\n python_libraries = [\n {\n \"nombre_librería\": \"Django\",\n \"creador\": \"Adrian Holovaty\",\n \"primer_año_lanzamiento\": 2005,\n \"versión\": \"4.0.2\",\n \"uso\": \"Desarrollo web\",\n \"descripción\": \"Django permite construir aplicaciones web mejores y más rápido.\"\n },\n {\n \"nombre_librería\": \"Flask\",\n \"creador\": \"Armin Ronacher\",\n \"primer_año_lanzamiento\": 2010,\n \"versión\": \"2.0.2\",\n \"uso\": \"Desarrollo web\",\n \"descripción\": \"Flask es un micro framework WSGI para aplicaciones web.\"\n },\n {\n \"nombre_librería\": \"NumPy\",\n \"creador\": \"Travis Oliphant\",\n \"primer_año_lanzamiento\": 2005,\n \"versión\": \"1.22.0\",\n \"uso\": \"Cómputo científico\",\n \"descripción\": \"NumPy es la biblioteca fundamental para el cómputo científico en Python.\"\n },\n {\n \"nombre_librería\": \"Pandas\",\n \"creador\": \"Wes McKinney\",\n \"primer_año_lanzamiento\": 2008,\n \"versión\": \"1.4.0\",\n \"uso\": \"Análisis de datos\",\n \"descripción\": \"pandas es una librería open source para análisis y manipulación de datos.\"\n },\n {\n \"nombre_librería\": \"Matplotlib\",\n \"creador\": \"John D. Hunter\",\n \"primer_año_lanzamiento\": 2003,\n \"versión\": \"3.5.1\",\n \"uso\": \"Visualización de datos\",\n \"descripción\": \"Matplotlib es una librería para crear visualizaciones estáticas, animadas e interactivas en Python.\"\n }\n ]\n ```\n\n🎉 ¡Felicidades! 🎉\n\n[<< Día 18](./18_regular_expressions_sp.md) | [Día 20 >>](./20_python_package_manager_sp.md)"
},
{
"path": "Spanish/20_python_package_manager_sp.md",
"content": "# 30 Días de Python: Día 20 - PIP\n\n- [Día 20](#-día-20)\n - [Python PIP - Gestor de paquetes de Python](#python-pip---gestor-de-paquetes-de-python)\n - [¿Qué es PIP?](#¿qué-es-pip)\n - [Instalar PIP](#instalar-pip)\n - [Instalar paquetes con pip](#instalar-paquetes-con-pip)\n - [Desinstalar paquetes](#desinstalar-paquetes)\n - [Lista de paquetes](#lista-de-paquetes)\n - [Mostrar información del paquete](#mostrar-información-del-paquete)\n - [PIP Freeze](#pip-freeze)\n - [Leer datos desde una URL](#leer-datos-desde-una-url)\n - [Crear paquetes](#crear-paquetes)\n - [Más información sobre paquetes](#más-información-sobre-paquetes)\n - [Ejercicios: Día 20](#ejercicios-día-20)\n\n# 📘 Día 20\n\n## Python PIP - Gestor de paquetes de Python\n\n### ¿Qué es PIP?\n\nPIP significa Preferred Installer Program, que en español puede traducirse como «programa de instalación preferido». Usamos _pip_ para instalar paquetes de Python.\nUn paquete es una colección de módulos (o subpaquetes) que podemos instalar y luego importar en nuestras aplicaciones.\nEn la práctica, en lugar de reescribir utilidades comunes, instalamos paquetes útiles y los importamos.\n\n### Instalar PIP\n\nSi aún no tienes pip instalado, instálalo ahora. En la terminal o símbolo del sistema ejecuta:\n\n```sh\npip install pip\n```\n\nComprueba si pip está instalado con:\n\n```sh\npip --version\n```\n\n```py\npip --version\n# ejemplo de salida:\n# pip 21.1.3 from /usr/local/lib/python3.7/site-packages/pip (python 3.9.6)\n```\n\nSi ves un número diferente, significa que pip está instalado en tu sistema.\n\n### Instalar paquetes con pip\n\nProbemos a instalar _numpy_, una librería numérica de Python muy usada en ciencia de datos y aprendizaje automático.\n\n- NumPy ofrece:\n - Potentes arrays N-dimensionales\n - Operaciones vectorizadas (broadcasting)\n - Herramientas para integrar con C/C++ y Fortran\n - Funciones de álgebra lineal, transformadas de Fourier y generadores aleatorios\n\n```sh\npip install numpy\n```\n\nEjemplo de uso en el intérprete de Python:\n\n```py\n>>> import numpy\n>>> numpy.version.version\n'1.20.1'\n>>> lst = [1, 2, 3, 4, 5]\n>>> np_arr = numpy.array(lst)\n>>> np_arr\narray([1, 2, 3, 4, 5])\n>>> len(np_arr)\n5\n>>> np_arr * 2\narray([ 2, 4, 6, 8, 10])\n>>> np_arr + 2\narray([3, 4, 5, 6, 7])\n```\n\nPandas es otra librería muy usada para estructuras de datos y análisis. Instalémosla:\n\n```sh\npip install pandas\n```\n\n```py\n>>> import pandas\n```\n\nEsta sección no pretende profundizar en NumPy o Pandas, sino solo mostrar cómo instalar e importar paquetes.\n\nHay módulos de la librería estándar, por ejemplo _webbrowser_, que permiten abrir sitios web. No necesitan instalación.\n\n```py\nimport webbrowser # módulo para abrir sitios web\n\n# lista de URLs de ejemplo\nurl_lists = [\n 'http://www.python.org',\n 'https://www.linkedin.com/in/asabeneh/',\n 'https://github.com/Asabeneh',\n 'https://twitter.com/Asabeneh',\n]\n\n# abrir cada URL en una nueva pestaña\nfor url in url_lists:\n webbrowser.open_new_tab(url)\n```\n\n### Desinstalar paquetes\n\nPara eliminar un paquete instalado:\n\n```sh\npip uninstall packagename\n```\n\n### Lista de paquetes\n\nPara listar los paquetes instalados en tu entorno:\n\n```sh\npip list\n```\n\n### Mostrar información del paquete\n\nPara ver información de un paquete:\n\n```sh\npip show packagename\n```\n\nEjemplo:\n\n```sh\npip show pandas\n```\n\nSalida de ejemplo:\n\n```txt\nName: pandas\nVersion: 1.2.3\nSummary: Powerful data structures for data analysis, time series, and statistics\nHome-page: http://pandas.pydata.org\nAuthor: None\nAuthor-email: None\nLicense: BSD\nLocation: /usr/local/lib/python3.7/site-packages\nRequires: python-dateutil, pytz, numpy\nRequired-by:\n```\n\nSi quieres más detalles puedes añadir --verbose.\n\n### PIP Freeze\n\nGenera una lista de paquetes instalados y sus versiones (útil para requirements.txt):\n\n```sh\npip freeze\n```\n\nSalida de ejemplo:\n\n```txt\ndocutils==0.11\nJinja2==2.7.2\nMarkupSafe==0.19\nPygments==1.6\nSphinx==1.2.2\n```\n\n### Leer datos desde una URL\n\nA veces queremos leer datos desde una URL (por ejemplo APIs que devuelven JSON). Para eso usamos el paquete _requests_.\n\nInstálalo con:\n\n```sh\npip install requests\n```\n\nEn requests veremos métodos y atributos como _get()_, _status_code_, _headers_, _text_, _json()_:\n - _get()_: solicita una URL y devuelve un objeto Response\n - _status_code_: código HTTP de la respuesta\n - _headers_: cabeceras de la respuesta\n - _text_: contenido en texto\n - _json()_: parsea JSON y devuelve estructuras de Python\n\nEjemplo leyendo un archivo de texto desde la web:\n\n```py\nimport requests # importar requests\n\nurl = 'https://www.w3.org/TR/PNG/iso_8859-1.txt' # URL con texto\n\nresponse = requests.get(url) # solicitar URL\nprint(response)\nprint(response.status_code) # código de estado, 200 indica éxito\nprint(response.headers) # cabeceras de la respuesta\nprint(response.text) # contenido en texto\n```\n\nEjemplo leyendo una API que devuelve JSON (API de países):\n\n```py\nimport requests\nurl = 'https://restcountries.eu/rest/v2/all' # API con información de países\nresponse = requests.get(url)\nprint(response) # objeto Response\nprint(response.status_code) # 200 indica éxito\ncountries = response.json()\nprint(countries[:1]) # imprimimos el primer país por brevedad\n```\n\nVeamos otro ejemplo con la API del Banco Mundial (datos de Etiopía):\n\n```py\nimport requests\nfrom pprint import pp # pretty print para mostrar resultados legibles\n\nurl = 'http://api.worldbank.org/countries/et?format=json' # API del Banco Mundial para Etiopía\nresponse = requests.get(url)\nprint(response) # objeto Response\nprint(response.status_code) # 200 indica éxito\nethiopia_data = response.json()\npp(ethiopia_data) # mostrar datos de forma legible\n```\n\n### Crear paquetes\n\nTambién podemos crear nuestros propios paquetes y subirlos a PyPI. Ejemplo simple: crea un directorio llamado mypackage con un __init__.py (puede estar vacío) y los siguientes módulos.\n\n```py\n# mypackage/arithmetics.py\ndef add_numbers(*args):\n total = 0\n for num in args:\n total += num\n return total\n\ndef subtract(a, b):\n return (a - b)\n\ndef multiple(a, b):\n return a * b\n\ndef division(a, b):\n return a / b\n\ndef remainder(a, b):\n return a % b\n\ndef power(a, b):\n return a ** b\n```\n\n```py\n# mypackage/greet.py\ndef greet_person(firstname, lastname):\n return f'{firstname} {lastname}, welcome to 30DaysOfPython Challenge!'\n```\n\n__init__.py no es estrictamente necesario en Python ≥3.3, pero se recomienda para compatibilidad.\n\nUsando el paquete:\n\n```py\nfrom mypackage import arithmetics\nprint(arithmetics.add_numbers(1, 2, 3, 5))\nprint(arithmetics.subtract(5, 3))\nprint(arithmetics.multiple(5, 3))\nprint(arithmetics.division(5, 3))\nprint(arithmetics.remainder(5, 3))\nprint(arithmetics.power(5, 3))\n\nfrom mypackage import greet\nprint(greet.greet_person('Juan', 'Pérez'))\n```\n\n### Más información sobre paquetes\n\n- Python tiene paquetes y módulos incorporados; otros deben instalarse.\n- pip es la herramienta recomendada para instalar y gestionar paquetes desde PyPI.\n- Para capturar las dependencias de un proyecto usa pip freeze > requirements.txt.\n- Para desinstalar: pip uninstall packagename o pip uninstall -r requirements.txt.\n- Virtualenv (y venv) permiten crear entornos aislados:\n - Instalar virtualenv: pip install virtualenv\n - Crear entornos aislados evita conflictos entre proyectos.\n\n## Ejercicios: Día 20\n\n1. Lee sobre entornos virtuales, crea uno e instala al menos un paquete dentro del entorno.\n\n2. Usa una API de países para obtener todos los datos y encuentra los 10 países más poblados.\n\n3. Encuentra todos los países cuyo idioma oficial sea inglés (código 'eng') a partir de los datos de la API.\n\n4. A partir de los datos de la API, encuentra los 10 países con mayor superficie.\n\n5. Encuentra todos los países recién listados (o filtrados según la API) y ordénalos por capital.\n\n🎉 ¡Felicidades! 🎉\n\n[<< Día 19](./19_file_handling_sp.md) | [Día 21 >>](./21_classes_and_objects_sp.md)"
},
{
"path": "Spanish/21_classes_and_objects_sp.md",
"content": "# 30 Días de Python: Día 21 - Clases y Objetos\n\n- [Día 21](#-día-21)\n - [Clases y objetos](#clases-y-objetos)\n - [Crear una clase](#crear-una-clase)\n - [Crear un objeto](#crear-un-objeto)\n - [Constructor de clase](#constructor-de-clase)\n - [Métodos de instancia](#métodos-de-instancia)\n - [Valores por defecto de los objetos](#valores-por-defecto-de-los-objetos)\n - [Modificar valores por defecto de la clase](#modificar-valores-por-defecto-de-la-clase)\n - [Herencia](#herencia)\n - [Sobrescribir métodos de la clase padre](#sobrescribir-métodos-de-la-clase-padre)\n - [💻 Ejercicios: Día 21](#-ejercicios-día-21)\n - [Ejercicios: Nivel 1](#ejercicios-nivel-1)\n - [Ejercicios: Nivel 2](#ejercicios-nivel-2)\n - [Ejercicios: Nivel 3](#ejercicios-nivel-3)\n\n# 📘 Día 21\n\n## Clases y objetos\n\nPython es un lenguaje orientado a objetos. En Python todo es un objeto con atributos y métodos. Los números, cadenas, listas, diccionarios, tuplas, conjuntos, etc. que usamos en programas son instancias de las clases incorporadas correspondientes. Creamos clases para definir objetos. Una clase es como un constructor de objetos o un \"molde\" para crear objetos. Instanciamos una clase para crear un objeto. La clase define las propiedades y el comportamiento, mientras que el objeto representa la instancia.\n\nDesde el inicio de este reto hemos estado usando clases y objetos sin darnos cuenta. Cada elemento en un programa Python es un objeto perteneciente a alguna clase. Veamos que todo en Python pertenece a una clase:\n\n```py\nasabeneh@Asabeneh:~$ python\nPython 3.9.6 (default, Jun 28 2021, 15:26:21)\n[Clang 11.0.0 (clang-1100.0.33.8)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n>>> num = 10\n>>> type(num)\n\n>>> string = 'string'\n>>> type(string)\n\n>>> boolean = True\n>>> type(boolean)\n\n>>> lst = []\n>>> type(lst)\n\n>>> tpl = ()\n>>> type(tpl)\n\n>>> set1 = set()\n>>> type(set1)\n\n>>> dct = {}\n>>> type(dct)\n\n```\n\n### Crear una clase\n\nPara crear una clase usamos la palabra clave class seguida del nombre de la clase y dos puntos. El nombre de la clase debe usar CamelCase.\n\n```sh\n# sintaxis\nclass NombreClase:\n # código aquí\n```\n\n**Ejemplo:**\n\n```py\nclass Person:\n pass\nprint(Person)\n```\n\n```sh\n<__main__.Person object at 0x10804e510>\n```\n\n### Crear un objeto\n\nCreamos un objeto llamando a la clase:\n\n```py\np = Person()\nprint(p)\n```\n\n### Constructor de clase\n\nEn el ejemplo anterior creamos un objeto de la clase Person. Sin embargo, una clase sin constructor no es muy útil en la práctica. Usamos el método especial __init__ como constructor en Python. __init__ recibe self, que es la referencia a la instancia actual.\n\n**Ejemplo:**\n\n```py\nclass Person:\n def __init__(self, name):\n # self permite ligar parámetros a la instancia\n self.name = name\n\np = Person('Asabeneh')\nprint(p.name)\nprint(p)\n```\n\n```sh\n# salida\nAsabeneh\n<__main__.Person object at 0x2abf46907e80>\n```\n\nAñadamos más parámetros al constructor:\n\n```py\nclass Person:\n def __init__(self, firstname, lastname, age, country, city):\n self.firstname = firstname\n self.lastname = lastname\n self.age = age\n self.country = country\n self.city = city\n\np = Person('Asabeneh', 'Yetayeh', 250, 'Finland', 'Helsinki')\nprint(p.firstname)\nprint(p.lastname)\nprint(p.age)\nprint(p.country)\nprint(p.city)\n```\n\n```sh\n# salida\nAsabeneh\nYetayeh\n250\nFinland\nHelsinki\n```\n\n### Métodos de instancia\n\nUn objeto puede tener métodos, que son funciones pertenecientes a esa instancia.\n\n**Ejemplo:**\n\n```py\nclass Person:\n def __init__(self, firstname, lastname, age, country, city):\n self.firstname = firstname\n self.lastname = lastname\n self.age = age\n self.country = country\n self.city = city\n def person_info(self):\n return f'{self.firstname} {self.lastname} tiene {self.age} años. Vive en {self.city}, {self.country}.'\n\np = Person('Asabeneh', 'Yetayeh', 250, 'Finland', 'Helsinki')\nprint(p.person_info())\n```\n\n```sh\n# salida\nAsabeneh Yetayeh tiene 250 años. Vive en Helsinki, Finland.\n```\n\n### Valores por defecto de los objetos\n\nA veces queremos proporcionar valores por defecto a los parámetros del constructor para evitar errores cuando la clase se instancia sin argumentos.\n\n**Ejemplo:**\n\n```py\nclass Person:\n def __init__(self, firstname='Asabeneh', lastname='Yetayeh', age=250, country='Finland', city='Helsinki'):\n self.firstname = firstname\n self.lastname = lastname\n self.age = age\n self.country = country\n self.city = city\n\n def person_info(self):\n return f'{self.firstname} {self.lastname} tiene {self.age} años. Vive en {self.city}, {self.country}.'\n\np1 = Person()\nprint(p1.person_info())\np2 = Person('John', 'Doe', 30, 'Nomanland', 'Noman city')\nprint(p2.person_info())\n```\n\n```sh\n# salida\nAsabeneh Yetayeh tiene 250 años. Vive en Helsinki, Finland.\nJohn Doe tiene 30 años. Vive en Noman city, Nomanland.\n```\n\n### Modificar valores por defecto de la clase\n\nEn el siguiente ejemplo todos los parámetros del constructor tienen valores por defecto y añadimos un atributo skills y un método add_skill para añadir habilidades.\n\n```py\nclass Person:\n def __init__(self, firstname='Asabeneh', lastname='Yetayeh', age=250, country='Finland', city='Helsinki'):\n self.firstname = firstname\n self.lastname = lastname\n self.age = age\n self.country = country\n self.city = city\n self.skills = []\n\n def person_info(self):\n return f'{self.firstname} {self.lastname} tiene {self.age} años. Vive en {self.city}, {self.country}.'\n def add_skill(self, skill):\n self.skills.append(skill)\n\np1 = Person()\nprint(p1.person_info())\np1.add_skill('HTML')\np1.add_skill('CSS')\np1.add_skill('JavaScript')\np2 = Person('John', 'Doe', 30, 'Nomanland', 'Noman city')\nprint(p2.person_info())\nprint(p1.skills)\nprint(p2.skills)\n```\n\n```sh\n# salida\nAsabeneh Yetayeh tiene 250 años. Vive en Helsinki, Finland.\nJohn Doe tiene 30 años. Vive en Noman city, Nomanland.\n['HTML', 'CSS', 'JavaScript']\n[]\n```\n\n### Herencia\n\nLa herencia nos permite definir una clase que hereda el comportamiento de otra, facilitando la reutilización del código.\n\n```py\n# sintaxis\nclass NombreSubclase(NombreSuperclase):\n # código aquí\n```\n\nEjemplo:\n\n```py\nclass Student(Person):\n pass\n\ns1 = Student('Eyob', 'Yetayeh', 30, 'Finland', 'Helsinki')\ns2 = Student('Lidiya', 'Teklemariam', 28, 'Finland', 'Espoo')\nprint(s1.person_info())\ns1.add_skill('JavaScript')\ns1.add_skill('React')\ns1.add_skill('Python')\nprint(s1.skills)\nprint(s2.person_info())\ns2.add_skill('Organizing')\ns2.add_skill('Marketing')\ns2.add_skill('Digital Marketing')\nprint(s2.skills)\n```\n\n```sh\n# salida\nEyob Yetayeh tiene 30 años. Vive en Helsinki, Finland.\n['JavaScript', 'React', 'Python']\nLidiya Teklemariam tiene 28 años. Vive en Espoo, Finland.\n['Organizing', 'Marketing', 'Digital Marketing']\n```\n\nNo hemos definido nuevos métodos en Student, pero puede usar los métodos del padre Person. Student hereda el constructor __init__ y el método person_info de Person. Si queremos añadir comportamiento específico en la subclase, definimos nuevos métodos o redefinimos los existentes.\n\n```py\nclass Student(Person):\n def __init__(self, firstname='Asabeneh', lastname='Yetayeh', age=250, country='Finland', city='Helsinki', gender='male'):\n self.gender = gender\n super().__init__(firstname, lastname, age, country, city)\n def person_info(self):\n gender = 'él' if self.gender == 'male' else 'ella'\n return f'{self.firstname} {self.lastname} tiene {self.age} años. {gender.capitalize()} vive en {self.city}, {self.country}.'\n\ns1 = Student('Eyob', 'Yetayeh', 30, 'Finland', 'Helsinki', 'male')\ns2 = Student('Lidiya', 'Teklemariam', 28, 'Finland', 'Espoo', 'female')\nprint(s1.person_info())\ns1.add_skill('JavaScript')\ns1.add_skill('React')\ns1.add_skill('Python')\nprint(s1.skills)\nprint(s2.person_info())\ns2.add_skill('Organizing')\ns2.add_skill('Marketing')\ns2.add_skill('Digital Marketing')\nprint(s2.skills)\n```\n\n```sh\n# salida\nEyob Yetayeh tiene 30 años. Él vive en Helsinki, Finland.\n['JavaScript', 'React', 'Python']\nLidiya Teklemariam tiene 28 años. Ella vive en Espoo, Finland.\n['Organizing', 'Marketing', 'Digital Marketing']\n```\n\nPodemos usar super() o el nombre de la clase padre para invocar el comportamiento del padre. En el ejemplo anterior sobrescribimos el método person_info en la subclase con una implementación distinta.\n\n### Sobrescribir métodos de la clase padre\n\nComo se mostró, podemos sobrescribir un método del padre definiendo en la subclase un método con el mismo nombre.\n\n## 💻 Ejercicios: Día 21\n\n### Ejercicios: Nivel 1\n\n1. Python tiene un módulo llamado _statistics_ que podemos usar para calcular estadísticas. Ahora intentemos desarrollar una clase que calcule count, sum, min, max, range, mean, median, mode, standard deviation, variance, frequency distribution y describe.\n\n```py\nclass Statistics:\n def __init__(self, data=[]):\n self.data = data\n\n def count(self):\n # tu propia implementación\n pass\n\n def sum(self):\n # tu propia implementación\n pass\n\n def min(self):\n # tu propia implementación\n pass\n\n def max(self):\n # tu propia implementación\n pass\n\n def range(self):\n # tu propia implementación\n pass\n\n def mean(self):\n # tu propia implementación\n pass\n\n def median(self):\n # tu propia implementación\n pass\n\n def mode(self):\n # tu propia implementación\n pass\n\n def standard_deviation(self):\n # tu propia implementación\n pass\n\n def variance(self):\n # tu propia implementación\n pass\n\n def frequency_distribution(self):\n # tu propia implementación\n pass\n\n def describe(self):\n # tu propia implementación\n pass\n```\n\n```py\n# código de prueba\ndata = [31, 26, 34, 37, 27, 26, 32, 32, 26, 27, 27, 24, 32, 33, 27, 25, 26, 38, 37, 31, 34, 24, 33, 29, 26]\nstatistics = Statistics(data)\nprint('Count:', statistics.count()) # 25\nprint('Sum: ', statistics.sum()) # 730\nprint('Min: ', statistics.min()) # 24\nprint('Max: ', statistics.max()) # 38\nprint('Range: ', statistics.range()) # 14\nprint('Mean: ', statistics.mean()) # 29.2\nprint('Median: ', statistics.median()) # 27\nprint('Mode: ', statistics.mode()) # {'mode': 26, 'count': 5}\nprint('Standard Deviation: ', statistics.standard_deviation()) # 4.2\nprint('Variance: ', statistics.variance()) # 17.5\nprint('Frequency Distribution: ', statistics.frequency_distribution()) # [(24, 2), (25, 1), (26, 5), (27, 4), (29, 1), (31, 2), (32, 3), (33, 2), (34, 2), (37, 2), (38, 1)]\n```\n\n### Ejercicios: Nivel 2\n\n1. Crea una clase llamada PersonAccount. Debe tener firstname, lastname, incomes, expenses como atributos y métodos para añadir ingresos, añadir gastos y calcular el balance.\n\n### Ejercicios: Nivel 3\n\n1. El siguiente código es una función; conviértelo en una clase con comportamiento equivalente.\n\n```python\ndef print_products(*args, **kwargs):\n for product in args:\n print(product)\n print(kwargs)\n for key in kwargs:\n print(f\"{key}: {kwargs[key]}\")\n\nprint_products(\"apple\", \"banana\", \"orange\", vegetable=\"tomato\", juice=\"orange\")\n```\n\n```sh\napple\nbanana\norange\n{'vegetable': 'tomato', 'juice': 'orange'}\nvegetable: tomato\njuice: orange\n```\n\n2. En la clase PersonAccount diseña atributos firstname, lastname, incomes y expenses y añade métodos para calcular el ingreso neto de la persona.\n\n🎉 ¡Felicidades! 🎉\n\n[<< Día 20](./20_python_package_manager_sp.md) | [Día 22 >>](./22_web_scraping_sp.md)"
},
{
"path": "Spanish/22_web_scraping_sp.md",
"content": "# 30 Días de Python: Día 22 - Web scraping\n\n- [Día 22](#-día-22)\n - [Web scraping con Python](#web-scraping-con-python)\n - [¿Qué es el web scraping?](#qué-es-el-web-scraping)\n - [💻 Ejercicios: Día 22](#-ejercicios-día-22)\n\n# 📘 Día 22\n\n## Web scraping con Python\n\n### ¿Qué es el web scraping?\n\nInternet está lleno de datos que pueden utilizarse para distintos fines. Para recopilar esos datos necesitamos saber cómo extraerlos de sitios web.\n\nEl web scraping es el proceso de extraer y recopilar datos de sitios web y almacenarlos en una máquina local o en una base de datos.\n\nEn esta sección usaremos los paquetes requests y BeautifulSoup (versión 4).\n\nPara empezar necesitas _requests_,_beautifulsoup4_ y un _sitio web_:\n\n```sh\npip install requests\npip install beautifulsoup4\n```\n\nPara hacer scraping necesitas conocimientos básicos de etiquetas HTML y selectores CSS. Usamos etiquetas HTML,clases y/o IDs para localizar contenido en la página.\nImportemos requests y BeautifulSoup:\n\n```py\nimport requests\nfrom bs4 import BeautifulSoup\n```\n\nDeclaremos una variable url con el sitio que queremos scrapear:\n\n```py\nimport requests\nfrom bs4 import BeautifulSoup\nurl = 'https://archive.ics.uci.edu/ml/datasets.php'\n\n# Usamos requests.get para obtener datos de la URL\nresponse = requests.get(url)\n# Comprobar el estado\nstatus = response.status_code\nprint(status) # 200 indica éxito\n```\n\n```sh\n200\n```\n\nParsear el contenido con BeautifulSoup:\n\n```py\nimport requests\nfrom bs4 import BeautifulSoup\nurl = 'https://archive.ics.uci.edu/ml/datasets.php'\n\nresponse = requests.get(url)\ncontent = response.content # obtenemos todo el contenido del sitio\nsoup = BeautifulSoup(content, 'html.parser') # BeautifulSoup nos permite parsear el HTML\nprint(soup.title) # UCI Machine Learning Repository: Data Sets\nprint(soup.title.get_text()) # UCI Machine Learning Repository: Data Sets\nprint(soup.body) # muestra el cuerpo completo de la página\nprint(response.status_code)\n\ntables = soup.find_all('table', {'cellpadding':'3'})\n# Localizamos tablas cuyo atributo cellpadding tenga el valor 3\n# Podemos usar id, class o etiquetas HTML para seleccionar elementos; consulta la documentación de BeautifulSoup para más información\ntable = tables[0] # el resultado es una lista; tomamos el primer elemento\nfor td in table.find('tr').find_all('td'):\n print(td.text)\n```\n\nSi ejecutas este código verás que la extracción está incompleta.Puedes continuar para completarla,ya que forma parte del ejercicio 1.\nConsulta la documentación de BeautifulSoup para más detalles: https://www.crummy.com/software/BeautifulSoup/bs4/doc/#quick-start\n\n🌕 Vas por muy buen camino.Solo te faltan ocho días para alcanzar una meta impresionante.Ahora haz los ejercicios para practicar.\n\n## 💻 Ejercicios: Día 22\n\n1. Raspa el siguiente sitio y guarda los datos como un archivo JSON (url = 'http://www.bu.edu/president/boston-university-facts-stats/').\n2. Extrae las tablas de esta URL (https://archive.ics.uci.edu/ml/datasets.php) y conviértelas a un archivo JSON.\n3. Raspa la tabla de presidentes y guarda los datos como JSON (https://en.wikipedia.org/wiki/List_of_presidents_of_the_United_States).Esta tabla no está muy bien estructurada,por lo que la extracción puede llevar tiempo.\n\n🎉 ¡Felicidades!🎉\n\n[<< Día 21](./21_classes_and_objects_sp.md) | [Día 23 >>](./23_virtual_environment_sp.md)"
},
{
"path": "Spanish/23_virtual_environment_sp.md",
"content": "# 30 Días de Python: Día 23 - Entornos virtuales\n\n- [Día 23](#-día-23)\n - [Configurar un entorno virtual](#configurar-un-entorno-virtual)\n - [💻 Ejercicios: Día 23](#-ejercicios-día-23)\n\n# 📘 Día 23\n\n## Configurar un entorno virtual\n\nAl comenzar un proyecto es recomendable usar un entorno virtual. Un entorno virtual nos permite crear un entorno aislado o independiente, evitando conflictos de dependencias entre proyectos. Si ejecutas pip freeze en la terminal verás todos los paquetes instalados en la máquina. Con virtualenv solo tendrás acceso a los paquetes instalados en ese entorno específico. Abre tu terminal e instala virtualenv:\n\n```sh\npip install virtualenv\n```\n\nDentro de la carpeta 30DaysOfPython crea un directorio llamado flask_project.\n\nUna vez instalado virtualenv, entra en la carpeta del proyecto y crea el entorno virtual:\n\nPara Mac/Linux:\n```sh\nvirtualenv venv\n```\n\nPara Windows:\n```sh\npython -m venv venv\n```\n\nA mí me gusta nombrar el entorno como venv, pero puedes elegir otro nombre. Usa ls (o dir en Windows) para comprobar que venv se creó:\n\n```sh\nls\n# venv/\n```\n\nActiva el entorno virtual desde la carpeta del proyecto:\n\nPara Mac/Linux:\n```sh\nsource venv/bin/activate\n```\n\nEn Windows la activación puede variar según PowerShell o Git Bash.\n\nPara Windows PowerShell:\n```sh\nvenv\\Scripts\\activate\n```\n\nPara Windows Git Bash:\n```sh\nvenv\\Scripts\\. activate\n```\n\nTras ejecutar el comando de activación,el prompt mostrará el nombre del entorno (venv) al inicio.Ejemplo:\n\n```sh\n(venv) user@host:~/Desktop/30DaysOfPython/flask_project$\n```\n\nAhora,si ejecutas pip freeze no verás los paquetes globales;solo los del entorno.Instalemos Flask para este proyecto:\n\n```sh\npip install Flask\n```\n\nDespués,comprobemos los paquetes instalados:\n\n```sh\npip freeze\n# ejemplo de salida:\n# Click==7.0\n# Flask==1.1.1\n# itsdangerous==1.1.0\n# Jinja2==2.10.3\n# MarkupSafe==1.1.1\n# Werkzeug==0.16.0\n```\n\nCuando termines,ejecuta deactivate para salir del entorno activo:\n\n```sh\ndeactivate\n```\n\nLos módulos necesarios para trabajar con Flask ya están instalados en el entorno del proyecto.Es buena práctica añadir venv al archivo .gitignore para no subir el entorno a GitHub.\n\n## 💻 Ejercicios: Día 23\n\n1. Crea un directorio de proyecto con un entorno virtual siguiendo el ejemplo anterior.\n\n🎉 ¡Felicidades! 🎉\n\n[<< Día 22](./22_web_scraping_sp.md) | [Día 24 >>](./24_statistics_sp.md)"
},
{
"path": "Spanish/24_statistics_sp.md",
"content": "# 30 Días de Python: Día 24 - Estadística\n\n- [Día 24](#-día-24)\n - [Análisis estadístico con Python](#análisis-estadístico-con-python)\n - [Estadística](#estadística)\n - [Datos](#datos)\n - [Módulo statistics](#módulo-statistics)\n- [NumPy](#numpy)\n - [Importar NumPy](#importar-numpy)\n - [Crear arrays con NumPy](#crear-arrays-con-numpy)\n - [Crear arrays enteros con NumPy](#crear-arrays-enteros-con-numpy)\n - [Crear arrays float con NumPy](#crear-arrays-float-con-numpy)\n - [Crear arrays booleanos con NumPy](#crear-arrays-booleanos-con-numpy)\n - [Crear arrays multidimensionales con NumPy](#crear-arrays-multidimensionales-con-numpy)\n - [Convertir arrays de NumPy a listas](#convertir-arrays-de-numpy-a-listas)\n - [Crear arrays desde tuplas](#crear-arrays-desde-tuplas)\n - [Forma (shape) de arrays de NumPy](#forma-shape-de-arrays-de-numpy)\n - [Tipo de datos de arrays de NumPy](#tipo-de-datos-de-arrays-de-numpy)\n - [Tamaño (size) de arrays de NumPy](#tamaño-size-de-arrays-de-numpy)\n - [Operaciones matemáticas con NumPy](#operaciones-matemáticas-con-numpy)\n - [Suma](#suma)\n\n# 📘 Día 24\n\n## Análisis estadístico con Python\n\n## Estadística\n\nLa estadística es la disciplina que estudia la recolección, organización, presentación, análisis, interpretación y comunicación de datos.\nLa estadística es una rama de las matemáticas y es un conocimiento previo recomendable para ciencia de datos y machine learning. Es un campo muy amplio; en esta sección nos centraremos solo en las partes más relevantes.\nAl completar este reto puedes avanzar hacia desarrollo web, análisis de datos, machine learning o ciencia de datos. En algún punto de tu carrera profesional te enfrentarás a datos que necesitan ser procesados. Tener nociones de estadística te ayudará a tomar decisiones basadas en datos: como dice el dicho, \"los datos nos hablan\".\n\n## Datos\n\n¿Qué son los datos? Los datos son cualquier conjunto de caracteres recogidos y transformados con algún propósito, usualmente para análisis. Pueden ser texto, números, imágenes, audio o vídeo. Si los datos carecen de contexto son poco útiles para humanos o máquinas. Para extraer significado necesitamos herramientas que los procesen.\n\nEl flujo de trabajo en análisis de datos, ciencia de datos o machine learning comienza siempre por los datos. Pueden provenir de fuentes externas o ser generados. Existen datos estructurados y no estructurados.\n\nLos datos pueden ser pequeños o masivos. Muchos de los formatos de datos que encontrarás ya se han presentado en la sección de manejo de archivos.\n\n## Módulo statistics\n\nEl módulo _statistics_ de Python ofrece funciones para cálculos estadísticos sobre datos numéricos. No compite con bibliotecas avanzadas de terceros (NumPy, SciPy) ni con paquetes profesionales de estadística, sino que provee funcionalidades a un nivel similar al de calculadoras científicas o gráficas.\n\n# NumPy\n\nComo lenguaje general, Python se potencia con librerías como numpy, scipy, matplotlib y pandas, transformándose en un entorno potente para computación científica.\n\nNumPy es la librería central para computación científica en Python; ofrece arrays multidimensionales de alto rendimiento y herramientas para operar con ellos.\n\nPara trabajar con notebooks es recomendable usar Jupyter. Puedes instalar Anaconda para disponer de Jupyter y muchas librerías preinstaladas.\n\n```sh\npip install numpy\n```\n\n## Importar NumPy\n\nSi usas Jupyter (recomendado), puedes seguir este notebook de ejemplo.\n\n```py\n# cómo importar numpy\nimport numpy as np\n# cómo comprobar la versión de numpy\nprint('numpy:', np.__version__)\n# ver métodos disponibles\nprint(dir(np))\n```\n\n## Crear arrays con NumPy\n\n### Crear arrays enteros con NumPy\n\n```py\n# crear una lista de Python\npython_list = [1,2,3,4,5]\n\n# comprobar tipo\nprint('Type:', type(python_list)) # \nprint(python_list) # [1, 2, 3, 4, 5]\n\ntwo_dimensional_list = [[0,1,2], [3,4,5], [6,7,8]]\nprint(two_dimensional_list) # [[0, 1, 2], [3, 4, 5], [6, 7, 8]]\n\n# crear un array NumPy desde la lista de Python\nnumpy_array_from_list = np.array(python_list)\nprint(type(numpy_array_from_list)) # \nprint(numpy_array_from_list) # array([1, 2, 3, 4, 5])\n```\n\n### Crear arrays float con NumPy\n\n```py\n# lista de Python\npython_list = [1,2,3,4,5]\n\nnumpy_array_from_list2 = np.array(python_list, dtype=float)\nprint(numpy_array_from_list2) # array([1., 2., 3., 4., 5.])\n```\n\n### Crear arrays booleanos con NumPy\n\n```py\nnumpy_bool_array = np.array([0, 1, -1, 0, 0], dtype=bool)\nprint(numpy_bool_array) # array([False, True, True, False, False])\n```\n\n### Crear arrays multidimensionales con NumPy\n\nUn array de NumPy puede tener múltiples filas y columnas:\n\n```py\ntwo_dimensional_list = [[0,1,2], [3,4,5], [6,7,8]]\nnumpy_two_dimensional_list = np.array(two_dimensional_list)\nprint(type(numpy_two_dimensional_list))\nprint(numpy_two_dimensional_list)\n```\n\n```sh\n\n[[0 1 2]\n [3 4 5]\n [6 7 8]]\n```\n\n### Convertir arrays de NumPy a listas\n\n```py\n# podemos usar tolist() para convertir un array a lista de Python\nnp_to_list = numpy_array_from_list.tolist()\nprint(type(np_to_list))\nprint('Array 1D:', np_to_list)\nprint('Array 2D: ', numpy_two_dimensional_list.tolist())\n```\n\n```sh\n\nArray 1D: [1, 2, 3, 4, 5]\nArray 2D: [[0, 1, 2], [3, 4, 5], [6, 7, 8]]\n```\n\n### Crear arrays desde tuplas\n\n```py\n# crear una tupla en Python\npython_tuple = (1,2,3,4,5)\nprint(type(python_tuple)) # \nprint('python_tuple: ', python_tuple) # python_tuple: (1, 2, 3, 4, 5)\n\nnumpy_array_from_tuple = np.array(python_tuple)\nprint(type(numpy_array_from_tuple)) # \nprint('numpy_array_from_tuple: ', numpy_array_from_tuple) # numpy_array_from_tuple: [1 2 3 4 5]\n```\n\n### Forma (shape) de arrays de NumPy\n\nEl método shape devuelve una tupla con la forma del array: filas y columnas. Si el array es 1D devuelve su longitud.\n\n```py\nnums = np.array([1, 2, 3, 4, 5])\nprint(nums)\nprint('Forma de nums: ', nums.shape)\nprint(numpy_two_dimensional_list)\nprint('Forma de numpy_two_dimensional_list: ', numpy_two_dimensional_list.shape)\nthree_by_four_array = np.array([[0, 1, 2, 3],\n [4,5,6,7],\n [8,9,10, 11]])\nprint(three_by_four_array.shape)\n```\n\n```sh\n[1 2 3 4 5]\nForma de nums: (5,)\n[[0 1 2]\n [3 4 5]\n [6 7 8]]\nForma de numpy_two_dimensional_list: (3, 3)\n(3, 4)\n```\n\n### Tipo de datos de arrays de NumPy\n\nTipos de datos: str, int, float, complex, bool, list, None\n\n```py\nint_lists = [-3, -2, -1, 0, 1, 2,3]\nint_array = np.array(int_lists)\nfloat_array = np.array(int_lists, dtype=float)\n\nprint(int_array)\nprint(int_array.dtype)\nprint(float_array)\nprint(float_array.dtype)\n```\n\n```sh\n[-3 -2 -1 0 1 2 3]\nint64\n[-3. -2. -1. 0. 1. 2. 3.]\nfloat64\n```\n\n### Tamaño (size) de arrays de NumPy\n\nPara conocer el número de elementos de un array utilizamos size:\n\n```py\nnumpy_array_from_list = np.array([1, 2, 3, 4, 5])\ntwo_dimensional_list = np.array([[0, 1, 2],\n [3, 4, 5],\n [6, 7, 8]])\n\nprint('Tamaño:', numpy_array_from_list.size) # 5\nprint('Tamaño:', two_dimensional_list.size) # 9\n```\n\n```sh\nTamaño: 5\nTamaño: 9\n```\n\n## Operaciones matemáticas con NumPy\n\nLos arrays de NumPy permiten operaciones vectorizadas sin necesidad de bucles.\n\nOperaciones disponibles:\n\n- Suma (+)\n- Resta (-)\n- Multiplicación (*)\n- División (/)\n- Módulo (%)\n- División entera (//)\n- Potencia (**)\n\n### Suma\n\n```py\nnumpy_array_from_list = np.array([1, 2, 3, 4, 5])\nprint('Array original: ', numpy_array_from_list)\nprint('Suma: ', numpy_array_from_list + 2)\nprint('Suma: ', np.add(numpy_array_from_list, 2))\n```\n\n```sh\nArray original: [1 2 3 4 5]\nSuma: [3 4 5 6 7]\nSuma: [3 4 5 6 7]\n```\n\n### Resta\n\n```py\nnumpy_array_from_list = np.array([1, 2, 3, 4, 5])\nprint('Array original: ', numpy_array_from_list)\nprint('Resta: ', numpy_array_from_list - 2)\nprint('Resta: ', np.subtract(numpy_array_from_list, 2))\n```\n\n```sh\nArray original: [1 2 3 4 5]\nResta: [-1 0 1 2 3]\nResta: [-1 0 1 2 3]\n```\n\n### Multiplicación\n\n```py\nnumpy_array_from_list = np.array([1, 2, 3, 4, 5])\nprint('Array original: ', numpy_array_from_list)\nprint('Multiplicación: ', numpy_array_from_list * 2)\nprint('Multiplicación: ', np.multiply(numpy_array_from_list, 2))\n```\n\n```sh\nArray original: [1 2 3 4 5]\nMultiplicación: [ 2 4 6 8 10]\nMultiplicación: [ 2 4 6 8 10]\n```\n\n### División\n\n```py\nnumpy_array_from_list = np.array([1, 2, 3, 4, 5])\nprint('Array original: ', numpy_array_from_list)\nprint('División: ', numpy_array_from_list / 2)\nprint('División: ', np.divide(numpy_array_from_list, 2))\n```\n\n```sh\nArray original: [1 2 3 4 5]\nDivisión: [0.5 1. 1.5 2. 2.5]\nDivisión: [0.5 1. 1.5 2. 2.5]\n```\n\n### Módulo\n\n```py\nnumpy_array_from_list = np.array([1, 2, 3, 4, 5])\nprint('Array original: ', numpy_array_from_list)\nprint('Módulo: ', numpy_array_from_list % 2)\nprint('Módulo: ', np.mod(numpy_array_from_list, 2))\n```\n\n```sh\nArray original: [1 2 3 4 5]\nMódulo: [1 0 1 0 1]\nMódulo: [1 0 1 0 1]\n```\n\n### División entera\n\n```py\nnumpy_array_from_list = np.array([1, 2, 3, 4, 5])\nprint('Array original: ', numpy_array_from_list)\nprint('División entera: ', numpy_array_from_list // 2)\nprint('División entera: ', np.floor_divide(numpy_array_from_list, 2))\n```\n\n```sh\nArray original: [1 2 3 4 5]\nDivisión entera: [0 1 1 2 2]\nDivisión entera: [0 1 1 2 2]\n```\n\n### Potencia\n\n```py\nnumpy_array_from_list = np.array([1, 2, 3, 4, 5])\nprint('Array original: ', numpy_array_from_list)\nprint('Potencia: ', numpy_array_from_list ** 2)\nprint('Potencia: ', np.power(numpy_array_from_list, 2))\n```\n\n```sh\nArray original: [1 2 3 4 5]\nPotencia: [ 1 4 9 16 25]\nPotencia: [ 1 4 9 16 25]\n```\n\n## Comprobar tipos de datos\n\n```py\nnumpy_int_arr = np.array([1, 2, 3, 4])\nnumpy_float_arr = np.array([1.1, 2.0, 3.2])\nnumpy_bool_arr = np.array([-3, -2, 0, 1, 2, 3], dtype='bool')\n\nprint(numpy_int_arr.dtype)\nprint(numpy_float_arr.dtype)\nprint(numpy_bool_arr.dtype)\n```\n\n```sh\nint64\nfloat64\nbool\n```\n\n## Convertir tipos\n\nPodemos convertir tipos con astype:\n\n```py\nnumpy_int_arr = np.array([1, 2, 3, 4], dtype='float')\nnumpy_int_arr.astype('int').dtype\nnumpy_float_arr = np.array([1.1, 2.0, 3.2])\nnumpy_float_arr.astype('int').dtype\nnumpy_int_arr = np.array([-3, -2, 0, 1, 2, 3])\nnumpy_int_arr.astype('bool').dtype\n```\n\n```sh\nint64\nint64\nbool\n```\n\n## Arrays multidimensionales\n\nUna de las ventajas de NumPy es el manejo de arrays multidimensionales:\n\n```py\ntwo_dimension_array = np.array([(1,2,3),(4,5,6), (7,8,9)])\nprint(type(two_dimension_array))\nprint(two_dimension_array)\nprint('Forma: ', two_dimension_array.shape)\nprint('Tamaño: ', two_dimension_array.size)\nprint('Tipo de datos: ', two_dimension_array.dtype)\n```\n\n```sh\n\n[[1 2 3]\n [4 5 6]\n [7 8 9]]\nForma: (3, 3)\nTamaño: 9\nTipo de datos: int64\n```\n\n### Acceder a elementos en arrays NumPy\n\n```py\ntwo_dimension_array = np.array([[1,2,3],[4,5,6], [7,8,9]])\nfirst_row = two_dimension_array[0]\nsecond_row = two_dimension_array[1]\nthird_row = two_dimension_array[2]\nprint('Primera fila:', first_row)\nprint('Segunda fila:', second_row)\nprint('Tercera fila: ', third_row)\n```\n\n```sh\nPrimera fila: [1 2 3]\nSegunda fila: [4 5 6]\nTercera fila: [7 8 9]\n```\n\nObtener columnas:\n\n```py\nfirst_column= two_dimension_array[:,0]\nsecond_column = two_dimension_array[:,1]\nthird_column = two_dimension_array[:,2]\nprint('Primera columna:', first_column)\nprint('Segunda columna:', second_column)\nprint('Tercera columna: ', third_column)\n```\n\n```sh\nPrimera columna: [1 4 7]\nSegunda columna: [2 5 8]\nTercera columna: [3 6 9]\n```\n\n## Slicing en arrays NumPy\n\nEl slicing es similar al de listas, pero admite dos dimensiones.\n\n```py\nnumpy_array_from_list = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])\nprint('Array original:', numpy_array_from_list)\n\n# primer parámetro: inicio\n# segundo parámetro: parada\n# tercer parámetro: paso\n\nten_first_items = numpy_array_from_list[0:10]\nprint('Primeras 10:', ten_first_items)\nfirst_five_items = numpy_array_from_list[:5]\nprint('Primeras 5:', first_five_items)\nlast_five_items = numpy_array_from_list[5:]\nprint('Últimas 5:', last_five_items)\n# índice negativo\nlast_five_items = numpy_array_from_list[-5:]\nprint('Últimas 5:', last_five_items)\n```\n\n```sh\nArray original: [ 1 2 3 4 5 6 7 8 9 10]\nPrimeras 10: [ 1 2 3 4 5 6 7 8 9 10]\nPrimeras 5: [1 2 3 4 5]\nÚltimas 5: [ 6 7 8 9 10]\nÚltimas 5: [ 6 7 8 9 10]\n```\n\nSeleccionar cada segundo elemento:\n\n```py\nevery_two_item = numpy_array_from_list[::2]\nprint('Cada dos elementos:', every_two_item)\n```\n\n```sh\nCada dos elementos: [1 3 5 7 9]\n```\n\nInvertir array:\n\n```py\nreversed_array = numpy_array_from_list[::-1]\nprint('Array invertido:', reversed_array)\n```\n\n```sh\nArray invertido: [10 9 8 7 6 5 4 3 2 1]\n```\n\nSlicing en 2D:\n\n```py\ntwo_dimension_array = np.array([[1,2,3],[4,5,6], [7,8,9]])\nprint(two_dimension_array)\nprint(two_dimension_array[1, 1])\nprint(two_dimension_array[1, 1:3])\nprint(two_dimension_array[1:3, 1:3])\n```\n\n```sh\n[[1 2 3]\n [4 5 6]\n [7 8 9]]\n5\n[5 6]\n[[5 6]\n [8 9]]\n```\n\n## Concatenación de arrays en NumPy\n\n```py\nfirst_array = np.array([1, 2, 3])\nsecond_array = np.array([4, 5, 6])\nthird_array = np.array([7, 8, 9])\nprint('Primer array:', first_array)\nprint('Segundo array:', second_array)\nprint('Tercer array:', third_array)\n```\n\n```sh\nPrimer array: [1 2 3]\nSegundo array: [4 5 6]\nTercer array: [7 8 9]\n```\n\n### Concatenación horizontal\n\n```py\nhorizontal_concat = np.hstack((first_array, second_array, third_array))\nprint('Concatenación horizontal:', horizontal_concat)\n```\n\n```sh\nConcatenación horizontal: [1 2 3 4 5 6 7 8 9]\n```\n\n### Concatenación vertical\n\n```py\nvertical_concat = np.vstack((first_array, second_array, third_array))\nprint('Concatenación vertical:', vertical_concat)\n```\n\n```sh\nConcatenación vertical:\n[[1 2 3]\n [4 5 6]\n [7 8 9]]\n```\n\n## Funciones comunes de NumPy\n\n### Mínimo, máximo, media, mediana y percentiles\n\n```py\nnumpy_array_from_list = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])\nprint('Mínimo:', numpy_array_from_list.min())\nprint('Máximo:', numpy_array_from_list.max())\nprint('Media:', numpy_array_from_list.mean())\n```\n\n🎉 ¡Felicidades! 🎉\n\n[<< Día 23](./23_virtual_environment_sp.md) | [Día 25 >>](./25_pandas_sp.md)"
},
{
"path": "Spanish/25_pandas_sp.md",
"content": "# 30 días de desafío de programación en Python: Día 25 - Pandas\n\n- [Día 25](#-día-25)\n - [Pandas](#pandas)\n - [InstalarPandas](#instalarpandas)\n - [ImportarPandas](#importarpandas)\n - [Crear serie de Pandas con índice por defecto](#crear-serie-de-pandas-con-índice-por-defecto)\n - [Crear serie de Pandas con índice personalizado](#crear-serie-de-pandas-con-índice-personalizado)\n - [Crear serie de Pandas a partir de un diccionario](#crear-serie-de-pandas-a-partir-de-un-diccionario)\n - [Crear serie de Pandas constante](#crear-serie-de-pandas-constante)\n - [Crear serie de Pandas con Linspace](#crear-serie-de-pandas-con-linspace)\n - [DataFrames](#dataframes)\n - [Crear DataFrame a partir de una lista de listas](#crear-dataframe-a-partir-de-una-lista-de-listas)\n - [Crear DataFrame a partir de un diccionario](#crear-dataframe-a-partir-de-un-diccionario)\n - [Crear DataFrame a partir de una lista de diccionarios](#crear-dataframe-a-partir-de-una-lista-de-diccionarios)\n - [Leer archivos CSV con Pandas](#leer-archivos-csv-con-pandas)\n - [Exploración de datos](#exploración-de-datos)\n - [Modificar DataFrame](#modificar-dataframe)\n - [Crear DataFrame](#crear-dataframe)\n - [Añadir nueva columna](#añadir-nueva-columna)\n - [Modificar valores de una columna](#modificar-valores-de-una-columna)\n - [Formatear columnas del DataFrame](#formatear-columnas-del-dataframe)\n - [Comprobar tipos de datos de columnas](#comprobar-tipos-de-datos-de-columnas)\n - [Indexación booleana](#indexación-booleana)\n - [Ejercicios: Día 25](#ejercicios-día-25)\n \n# 📘 Día 25\n\n## Pandas\n\nPandas es una librería open source, de alto rendimiento y fácil de usar para el manejo y análisis de estructuras de datos en Python.\nPandas aporta estructuras y herramientas para manejar datos tabulares: *Series* y *DataFrames*.\nPandas proporciona utilidades para operaciones de datos como:\n\n- reshape (remodelar)\n- merge (fusionar)\n- sort (ordenar)\n- slice (rebanar)\n- aggregate (agregar)\n- interpolate (interpolar)\n\nSi usas Anaconda no es necesario instalar pandas.\n\n### InstalarPandas\n\nPara Mac:\n```sh\npip install conda\nconda install pandas\n```\n\nPara Windows:\n```sh\npip install conda\npip install pandas\n```\n\nLas estructuras de datos de Pandas se basan en *Series* y *DataFrames*.\n\nUna *Serie* es una columna, mientras que un DataFrame es una tabla multidimensional compuesta por un conjunto de *Series*. Para crear una serie de Pandas, debemos usar un array unidimensional de NumPy o una lista de Python.\nVeamos un ejemplo de una serie:\n\nSerie de Pandas de nombres\n\n \n\nSerie de países\n\n \n\nSerie de ciudades\n\n\n\nComo puedes ver, una serie de Pandas es simplemente una columna de datos. Si queremos tener varias columnas, usamos un DataFrame. El siguiente ejemplo muestra un DataFrame de Pandas.\n\nVeamos un ejemplo de un DataFrame de Pandas:\n\n\n\nUn DataFrame es una colección de filas y columnas. Mira la tabla a continuación; tiene más columnas que el ejemplo anterior:\n\n\n\nA continuación, veremos cómo importar Pandas y cómo crear Series y DataFrames con Pandas.\n\n### Importar Pandas\n\n```python\nimport pandas as pd # importar pandas como pd\nimport numpy as np # importar numpy como np\n```\n\n### Crear serie de Pandas con índice por defecto\n\n```python\nnums = [1, 2, 3, 4,5]\ns = pd.Series(nums)\nprint(s)\n```\n\n```sh\n0 1\n1 2\n2 3\n3 4\n4 5\ndtype: int64\n```\n\n### Crear serie de Pandas con índice personalizado\n\n```python\nnums = [1, 2, 3, 4, 5]\ns = pd.Series(nums, index=[1, 2, 3, 4, 5])\nprint(s)\n```\n\n```sh\n1 1\n2 2\n3 3\n4 4\n5 5\ndtype: int64\n```\n\n```python\nfruits = ['Orange','Banana','Mango']\nfruits = pd.Series(fruits, index=[1, 2, 3])\nprint(fruits)\n```\n\n```sh\n1 Orange\n2 Banana\n3 Mango\ndtype: object\n```\n\n### Crear serie de Pandas a partir de un diccionario\n\n```python\ndct = {'name':'Asabeneh','country':'Finland','city':'Helsinki'}\n```\n\n```python\ns = pd.Series(dct)\nprint(s)\n```\n\n```sh\nname Asabeneh\ncountry Finland\ncity Helsinki\ndtype: object\n```\n\n### Crear serie de Pandas constante\n\n```python\ns = pd.Series(10, index = [1, 2, 3])\nprint(s)\n```\n\n```sh\n1 10\n2 10\n3 10\ndtype: int64\n```\n\n### Crear serie de Pandas con Linspace\n\n```python\ns = pd.Series(np.linspace(5, 20, 10)) # linspace(inicio, fin, número_de_elementos)\nprint(s)\n```\n\n```sh\n0 5.000000\n1 6.666667\n2 8.333333\n3 10.000000\n4 11.666667\n5 13.333333\n6 15.000000\n7 16.666667\n8 18.333333\n9 20.000000\ndtype: float64\n```\n\n## DataFrames\n\nPandas DataFrame se puede crear de diferentes maneras:\n\n- Crear a partir de una lista de listas\n- Crear a partir de un diccionario\n- Crear a partir de una lista de diccionarios\n- Crear a partir de un archivo CSV\n\n### Crear DataFrame a partir de una lista de listas\n\n```python\ndata = [\n ['Asabeneh', 'Finland', 'Helsinki'], \n ['David', 'UK', 'London'],\n ['John', 'Sweden', 'Stockholm']\n]\ndf = pd.DataFrame(data, columns=['Name', 'Country', 'City'])\nprint(df)\n```\n\n```sh\n Name Country City\n0 Asabeneh Finland Helsinki\n1 David UK London\n2 John Sweden Stockholm\n```\n\n### Crear DataFrame a partir de un diccionario\n\n```python\ndata = {'Name': ['Asabeneh', 'David', 'John'], 'Country':[\n 'Finland', 'UK', 'Sweden'], 'City': ['Helsinki', 'London', 'Stockholm']}\ndf = pd.DataFrame(data)\nprint(df)\n```\n\n```sh\n Name Country City\n0 Asabeneh Finland Helsinki\n1 David UK London\n2 John Sweden Stockholm\n```\n\n### Crear DataFrame a partir de una lista de diccionarios\n\n```python\ndata = [\n {'Name': 'Asabeneh', 'Country': 'Finland', 'City': 'Helsinki'},\n {'Name': 'David', 'Country': 'UK', 'City': 'London'},\n {'Name': 'John', 'Country': 'Sweden', 'City': 'Stockholm'}]\ndf = pd.DataFrame(data)\nprint(df)\n```\n\n```sh\n Name Country City\n0 Asabeneh Finland Helsinki\n1 David UK London\n2 John Sweden Stockholm\n```\n\n## Leer archivos CSV con Pandas\n\nLeamos el archivo en el directorio de datos, leeremos el archivo weight-height.csv pasando la ruta del archivo como parámetro a la función pd.read_csv(). Usemos el método head() para ver las primeras cinco filas.\n\n```python\nimport pandas as pd\n\ndf = pd.read_csv('./data/weight-height.csv')\nprint(df.head()) # por defecto muestra las primeras 5 filas\n```\n\n```sh\n Gender Height Weight\n0 Male 73.847017 241.893563\n1 Male 68.781904 162.310473\n2 Male 74.110105 212.740856\n3 Male 71.730978 220.042470\n4 Male 69.881796 206.349801\n```\n\nVeamos las últimas cinco filas usando el método tail():\n\n```python\nprint(df.tail()) # últimas 5 filas\n```\n\n```sh\n Gender Height Weight\n9995 Female 66.172652 136.777454\n9996 Female 67.067155 170.867906\n9997 Female 63.867992 128.475319\n9998 Female 69.034243 163.852461\n9999 Female 61.944246 113.649103\n```\n\n### Exploración de datos\n\nObtenemos el número de filas y columnas con la propiedad shape:\n```python\nprint(df.shape) # número de filas y columnas\n```\n\n```sh\n(10000, 3)\n```\n\nComo puedes ver, este conjunto de datos tiene 10000 filas y 3 columnas. Obtengamos más información sobre los datos:\n\n```python\nprint(df.columns) # nombres de las columnas\nprint(df.head(10)) # primeras 10 filas\nprint(df.tail(10)) # últimas 10 filas\nprint(df['Gender'].value_counts()) # contar cuántos hay de cada uno\nprint(df.describe()) # resumen estadístico de los datos\n```\n\n```sh\nIndex(['Gender', 'Height', 'Weight'], dtype='object')\n Gender Height Weight\n0 Male 73.847017 241.893563\n1 Male 68.781904 162.310473\n2 Male 74.110105 212.740856\n3 Male 71.730978 220.042470\n4 Male 69.881796 206.349801\n5 Male 68.767792 152.212156\n6 Male 67.961960 183.927889\n7 Male 68.563817 175.929316\n8 Male 71.267570 196.028855\n9 Male 72.040119 205.801386\n Gender Height Weight\n9990 Female 64.744846 139.725595\n9991 Female 62.109532 132.451630\n9992 Female 62.593008 130.727432\n9993 Female 62.100222 131.220717\n9994 Female 63.421888 133.330246\n9995 Female 66.172652 136.777454\n9996 Female 67.067155 170.867906\n9997 Female 63.867992 128.475319\n9998 Female 69.034243 163.852461\n9999 Female 61.944246 113.649103\nGender\nMale 5000\nFemale 5000\nName: count, dtype: int64\n Height Weight\ncount 10000.000000 10000.000000\nmean 66.367560 161.440357\nstd 3.847528 32.108439\nmin 54.263133 64.700127\n25% 63.505620 135.818051\n50% 66.318070 161.212928\n75% 69.174262 187.169525\nmax 78.998742 269.989699\n```\n\n## Modificar DataFrame\n\n### Crear DataFrame\n\nPrimero, creemos un DataFrame usando lo que aprendimos anteriormente:\n\n```python\n# importar pandas y numpy\nimport pandas as pd\nimport numpy as np\n# datos\ndata = [\n {\"Name\": \"Juan Pérez\", \"Country\":\"China\", \"City\":\"Shanghái\"},\n {\"Name\": \"Luis\", \"Country\":\"China\", \"City\":\"Pekín\"},\n {\"Name\": \"Carlos\", \"Country\":\"China\", \"City\":\"Cantón\"}]\n# crear DataFrame\ndf = pd.DataFrame(data)\nprint(df)\n```\n\n```sh\n Name Country City\n0 Juan Pérez China Shanghái\n1 Luis China Pekín\n2 Carlos China Cantón\n```\n\n### Añadir nueva columna\n\n```python\nweights = [74, 78, 69]\ndf['Weight'] = weights\ndf\n```\n\n```sh\n Name Country City Weight\n0 Juan Pérez China Shanghái 74\n1 Luis China Pekín 78\n2 Carlos China Cantón 69\n```\n\n```python\nheights = [173, 175, 169]\ndf['Height'] = heights\ndf\n```\n\n```sh\n Name Country City Weight Height\n0 Juan Pérez China Shanghái 74 173\n1 Luis China Pekín 78 175\n2 Carlos China Cantón 69 169\n```\n\n### Modificar valores de una columna\n\nPodemos modificar una columna de tres maneras:\n\n1. Asignación directa:\n```python\ndf['Name'] = ['Miguel', 'Ana', 'Sofía']\ndf\n```\n\n```sh\n Name Country City Weight Height\n0 Miguel China Shanghái 74 173\n1 Ana China Pekín 78 175\n2 Sofía China Cantón 69 169\n```\n\n2. Modificando con loc:\n```python\ndf.loc[1, 'Name'] = 'Lucía'\ndf\n```\n\n```sh\n Name Country City Weight Height\n0 Miguel China Shanghái 74 173\n1 Lucía China Pekín 78 175\n2 Sofía China Cantón 69 169\n```\n\n3. Modificando con iloc:\n```python\nprint('Datos originales:\\n', df)\ndf.iloc[1, 0] = 'Paco'\nprint('Datos modificados:\\n', df)\n```\n\n```sh\nDatos originales:\n Name Country City Weight Height\n0 Miguel China Shanghái 74 173\n1 Lucía China Pekín 78 175\n2 Sofía China Cantón 69 169\nDatos modificados:\n Name Country City Weight Height\n0 Miguel China Shanghái 74 173\n1 Paco China Pekín 78 175\n2 Sofía China Cantón 69 169\n```\n\n### Formatear columnas del DataFrame\n\n```python\n# añadir columna BMI: peso(kg) / altura^2(m). Redondear a 2 decimales.\ndf['BMI'] = np.round(df['Weight'] / ((df['Height'] * 0.01) ** 2), 2)\nprint(df)\n```\n\n```sh\n Name Country City Weight Height BMI\n0 Miguel China Shanghái 74 173 24.73\n1 Paco China Pekín 78 175 25.47\n2 Sofía China Cantón 69 169 24.16\n```\n\n## Comprobar tipos de datos de columnas\n\n```python\nprint(df.dtypes)\n```\n\n```sh\nName object\nCountry object\nCity object\nWeight int64\nHeight int64\nBMI float64\ndtype: object\n```\n\n### Indexación booleana\n\n```python\n# crear DataFrame\ndf = pd.DataFrame({\n 'name': ['Juan', 'Luis', 'Carlos', 'Pedro'],\n 'country': ['China', 'Estados Unidos', 'Reino Unido', 'España'],\n 'age': [25, 15, 22, 28],\n 'empleado': [True, False, True, False]\n})\n\nprint(df)\n```\n\n```sh\n name country age empleado\n0 Juan China 25 True\n1 Luis Estados Unidos 15 False\n2 Carlos Reino Unido 22 True\n3 Pedro España 28 False\n```\n\nFiltrando edad > 20 y empleado == True:\n```python\nprint(df[(df['age'] > 20) & (df['empleado'] == True)])\n```\n\n```sh\n name country age empleado\n0 Juan China 25 True\n2 Carlos Reino Unido 22 True\n```\n\n## Ejercicios: Día 25\n\n1. Lee el archivo [hacker_news.csv](../data/hacker_news.csv) y muestra las primeras cinco filas.\n2. Obtén la columna de títulos.\n3. Obtén el número de filas y columnas.\n4. Obtén las primeras diez y las últimas diez filas.\n5. Obtén la segunda y cuarta fila, columnas 2 a 4.\n6. Filtra las filas cuyo tema sea Python.\n7. Cuenta cuántas filas tienen tema Python.\n8. Filtra las filas con votos mayores a 200.\n9. Ordena el DataFrame por votos (ascendente).\n10. Ordena el DataFrame por votos (descendente).\n11. Excluye las filas con tema Python y ordena por votos.\n\n🎉 ¡Felicidades! 🎉\n\n[<< Día 24](./24_statistics_sp.md) | [Día 26 >>](./26_python_web_sp.md)"
},
{
"path": "Spanish/26_python_web_sp.md",
"content": "# 30 días de desafío de programación en Python: Día 26 - Programación web con Python\n\n- [Día 26](#-día-26)\n - [Programación web con Python](#programación-web-con-python)\n - [Flask](#flask)\n - [Estructura de carpetas](#estructura-de-carpetas)\n - [Configurar el proyecto](#configurar-el-proyecto)\n - [Crear rutas](#crear-rutas)\n - [Crear plantillas](#crear-plantillas)\n - [Script de Python](#script-de-python)\n - [Navegación](#navegación)\n - [Crear plantilla base](#crear-plantilla-base)\n - [Servir archivos estáticos](#servir-archivos-estáticos)\n - [Despliegue](#despliegue)\n - [Crear cuenta en Heroku](#crear-cuenta-en-heroku)\n - [Iniciar sesión en Heroku](#iniciar-sesión-en-heroku)\n - [Crear requirements y Procfile](#crear-requirements-y-procfile)\n - [Enviar el proyecto a Heroku](#enviar-el-proyecto-a-heroku)\n - [Ejercicios: Día 26](#ejercicios-día-26)\n\n# 📘 Día 26\n\n## Programación web con Python\n\nPython es un lenguaje de programación versátil que se puede utilizar para una variedad de propósitos. En esta sección, veremos cómo usar Python para el desarrollo web. Python tiene muchos marcos web disponibles. Django y Flask son los más populares. Hoy, aprenderemos a usar Flask para el desarrollo web.\n\n### Flask\n\nFlask es un marco de desarrollo web escrito en Python. Flask utiliza el motor de plantillas Jinja2. Flask también se puede usar con otras bibliotecas modernas de frontend como React.\n\nSi aún no has instalado el paquete virtualenv, instálalo primero. Un entorno virtual permitirá aislar las dependencias del proyecto de las dependencias de la máquina local.\n\n#### Estructura de carpetas\n\nDespués de completar todos los pasos, la estructura de archivos de tu proyecto debería ser la siguiente:\n\n```sh\n├── Procfile\n├── app.py\n├── env\n│ ├── bin\n├── requirements.txt\n├── static\n│ └── css\n│ └── main.css\n└── templates\n ├── about.html\n ├── home.html\n ├── layout.html\n ├── post.html\n └── result.html\n```\n\n### Configurar el proyecto\n\nComienza a usar Flask siguiendo estos pasos.\n\nPaso 1: Instala virtualenv con el siguiente comando.\n\n```sh\npip install virtualenv\n```\n\nPaso 2:\n\n```sh\nasabeneh@Asabeneh:~/Desktop$ mkdir python_for_web\nasabeneh@Asabeneh:~/Desktop$ cd python_for_web/\nasabeneh@Asabeneh:~/Desktop/python_for_web$ virtualenv venv\nasabeneh@Asabeneh:~/Desktop/python_for_web$ source venv/bin/activate\n(env) asabeneh@Asabeneh:~/Desktop/python_for_web$ pip freeze\n(env) asabeneh@Asabeneh:~/Desktop/python_for_web$ pip install Flask\n(env) asabeneh@Asabeneh:~/Desktop/python_for_web$ pip freeze\nClick==7.0\nFlask==1.1.1\nitsdangerous==1.1.0\nJinja2==2.10.3\nMarkupSafe==1.1.1\nWerkzeug==0.16.0\n(env) asabeneh@Asabeneh:~/Desktop/python_for_web$\n```\n\nHemos creado un directorio de proyecto llamado python_for_web. Dentro del proyecto, hemos creado un entorno virtual llamado *venv*, que puede tener cualquier nombre. Luego, activamos el entorno virtual. Usamos pip freeze para verificar los paquetes instalados en el directorio del proyecto. El resultado de pip freeze está vacío porque aún no se han instalado paquetes.\n\nAhora, creemos el archivo app.py en el directorio del proyecto y escribamos el siguiente código. El archivo app.py será el archivo principal del proyecto. El siguiente código contiene el módulo flask y el módulo os.\n\n### Crear rutas\n\nRuta de inicio.\n\n```py\n# importar flask\nfrom flask import Flask\nimport os # importar el módulo del sistema operativo\n\napp = Flask(__name__)\n\n@app.route('/') # este decorador crea la ruta de inicio\ndef home ():\n return '
'\n\n\nif __name__ == '__main__':\n # usamos variables de entorno para despliegue\n # funciona tanto para producción como para desarrollo\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\nPara ejecutar la aplicación flask, ingresa python app.py en el directorio principal de la aplicación flask.\n\nDespués de ejecutar _python app.py_, verifica el puerto 5000 de tu localhost.\n\nAgreguemos una ruta adicional creando la ruta \"acerca de\".\n\n```py\n# importar flask\nfrom flask import Flask\nimport os # importar el módulo del sistema operativo\n\napp = Flask(__name__)\n\n@app.route('/') # este decorador crea la ruta de inicio\ndef home ():\n return '
'\n\nif __name__ == '__main__':\n # usamos variables de entorno para despliegue\n # funciona tanto para producción como para desarrollo\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\nAhora, hemos agregado la ruta acerca de en el código anterior. ¿Pero qué pasa si queremos renderizar un archivo HTML en lugar de una cadena? Podemos renderizar un archivo HTML usando la función *render_template*. Creamos una carpeta llamada templates en el directorio del proyecto y dentro de ella, creamos home.html y about.html. También importamos *render_template* desde flask.\n\n### Crear plantillas\n\nCrea archivos HTML dentro de la carpeta templates.\n\nhome.html\n\n```html\n\n\n \n \n \n Página principal\n \n\n \n
\n \n\n```\n\n### Script de Python (con render_template)\n\napp.py\n\n```py\n# importar flask\nfrom flask import Flask, render_template\nimport os # importar el módulo del sistema operativo\n\napp = Flask(__name__)\n\n@app.route('/') # este decorador crea la ruta de inicio\ndef home ():\n return render_template('home.html')\n\n@app.route('/about')\ndef about():\n return render_template('about.html')\n\nif __name__ == '__main__':\n # usamos variables de entorno para despliegue\n # funciona tanto para producción como para desarrollo\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\nComo puedes ver, para acceder a diferentes páginas o navegar, necesitamos un sistema de navegación. Agreguemos un enlace para cada página, o creemos un diseño que usemos para cada página.\n\n### Navegación\n\n```html\n
\n```\n\nAhora, podemos navegar entre páginas usando los enlaces anteriores. Creamos una página adicional para manejar los datos del formulario. Puedes nombrarla como quieras, yo prefiero llamarla post.html.\n\nPodemos inyectar datos en el archivo HTML usando el motor de plantillas Jinja2.\n\n```py\n# importar flask\nfrom flask import Flask, render_template, request, redirect, url_for\nimport os # importar el módulo del sistema operativo\n\napp = Flask(__name__)\n\n@app.route('/') # este decorador crea la ruta de inicio\ndef home ():\n techs = ['HTML', 'CSS', 'Flask', 'Python']\n name = '30 días de desafío de programación en Python'\n return render_template('home.html', techs=techs, name=name, title='Página principal')\n\n@app.route('/about')\ndef about():\n name = '30 días de desafío de programación en Python'\n return render_template('about.html', name=name, title='Acerca de nosotros')\n\n@app.route('/post')\ndef post():\n name = 'Artículos sobre programación'\n path = request.path\n return render_template('post.html', name=name, path=path, title='Artículos')\n\nif __name__ == '__main__':\n # usamos variables de entorno para despliegue\n # funciona tanto para producción como para desarrollo\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\nhome.html\n\n```html\n\n\n \n \n \n {{title}}\n \n\n \n
\n \n \n\n```\n\nAhora, agreguemos una ruta que procese los datos del formulario. Usamos el método POST porque recibiremos datos del formulario.\n\n```py\n# importar flask\nfrom flask import Flask, render_template, request, redirect, url_for\nimport os # importar el módulo del sistema operativo\n\napp = Flask(__name__)\n\n@app.route('/') # este decorador crea la ruta de inicio\ndef home():\n techs = ['HTML', 'CSS', 'Flask', 'Python']\n name = '30 días de desafío de programación en Python'\n return render_template('home.html', techs=techs, name=name, title='Página principal')\n\n@app.route('/about')\ndef about():\n name = '30 días de desafío de programación en Python'\n return render_template('about.html', name=name, title='Acerca de nosotros')\n\n@app.route('/post')\ndef post():\n name = 'Artículos'\n return render_template('post.html', name=name, title='Artículos')\n\n\n@app.route('/result', methods=['POST'])\ndef result():\n first_name = request.form['first_name']\n last_name = request.form['last_name']\n old_job = request.form['old_job']\n current_job = request.form['current_job']\n country = request.form['country']\n print(first_name, last_name, old_job, current_job, country)\n result_data = {\n 'first_name':first_name,\n 'last_name':last_name,\n 'old_job': old_job,\n 'current_job': current_job,\n 'country':country\n }\n return render_template('result.html', result_data = result_data, title= 'Resultado')\n\nif __name__ == '__main__':\n # usamos variables de entorno para despliegue\n # funciona tanto para producción como para desarrollo\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\nresult.html\n\n```html\n\n\n \n \n \n {{title}}\n \n\n \n
\n \n\n```\n\nEn el mundo real, no repetiríamos el código HTML en todas las páginas. En su lugar, crearíamos una plantilla base y las demás heredarían de ella. Usemos la herencia (plantillas). Ahora, en lugar de tres archivos diferentes, necesitamos crear un archivo de diseño llamado layout.html. Luego, otros archivos heredarán de él.\n\n### Crear plantilla base (layout)\n\nlayout.html\n\n```html\n\n\n \n \n \n \n \n {% if title %}\n 30 Días de Python - {{ title}}\n {% else %}\n 30 Días de Python\n {% endif %}\n \n\n \n \n
\n \n \n {% block content %} {% endblock %}\n \n \n\n```\n\nEn el diseño anterior, hemos creado una plantilla común que puede ser utilizada por todas las páginas que heredan de ella. Dentro del diseño, podemos ver los enlaces de navegación. Usamos las etiquetas {% block content %}{% endblock %} para permitir que las subplantillas agreguen contenido.\n\nhome.html\n\n```html\n{% extends 'layout.html' %} {% block content %}\n
\n
Bienvenido de vuelta a {{name}}
\n
\n Este proyecto fue construido usando las siguientes tecnologías:\n Flask, Python\n y HTML, CSS\n
\n Este desafío es un desafío de programación de 30 días diseñado para ayudarte a aprender el lenguaje de programación Python, resolviendo un problema de Python cada día.\n
\n\n{% endblock %}\n```\n\n#### Servir archivos estáticos\n\nA continuación se muestra el archivo main.css, que colocaremos en el directorio static/css:\n\n```css\n/* === GENERAL === */\nbody {\n margin: 0;\n padding: 0;\n font-family: \"Lato\", sans-serif;\n background-color: #f0f8ea;\n}\n\n.container {\n max-width: 80%;\n margin: auto;\n padding: 30px;\n}\n\nul {\n list-style-type: none;\n padding: 0;\n}\n\n.tech {\n color: #5bbc2e;\n}\n\n/* === HEADER === */\nheader {\n background-color: #5bbc2e;\n}\n\n.menu-container {\n display: flex;\n justify-content: space-between;\n padding: 20px 30px;\n}\n\n.brand-name {\n color: white;\n font-weight: 800;\n font-size: 24px;\n}\n\n.nav-lists {\n display: flex;\n}\n\n.nav-list {\n margin-right: 15px;\n}\n\n.nav-link {\n text-decoration: none;\n color: white;\n font-weight: 300;\n}\n\n/* === FORM === */\n\nform {\n margin: 30px 0;\n border: 1px solid #ddd;\n padding: 30px;\n border-radius: 10px;\n}\n\nform > div {\n margin-bottom: 15px;\n}\n\ninput {\n width: 100%;\n padding: 10px;\n border: 1px solid #ddd;\n border-radius: 5px;\n outline: 0;\n font-size: 16px;\n box-sizing: border-box;\n margin-top: 5px;\n}\n\nbutton {\n padding: 12px 24px;\n border: 0;\n background-color: #5bbc2e;\n color: white;\n border-radius: 10px;\n font-size: 16px;\n outline: 0;\n cursor: pointer;\n}\n\nbutton:hover {\n background-color: #4b9c25;\n}\n```\n\n### Despliegue\n\n#### Crear cuenta en Heroku\n\nHeroku ofrece un servicio de alojamiento gratuito. Si deseas desplegar una aplicación, debes tener una cuenta en Heroku.\n\n#### Iniciar sesión en Heroku\n\n```sh\nasabeneh@Asabeneh:~/Desktop/python_for_web$ heroku login\nheroku: Press any key to open up the browser to login or q to exit:\nOpening browser to https://cli-auth.heroku.com/auth/cli/browser/ec0972d5-d8c6-4adf-b004-a42a22dd09a8\nLogging in... done\nLogged in as asabeneh@gmail.com\nasabeneh@Asabeneh:~/Desktop/python_for_web$\n```\n\n#### Crear requirements y Procfile\n\nAntes de desplegar la aplicación, necesitamos informar a Heroku qué dependencias instalar y cómo ejecutar la aplicación. Heroku utiliza el archivo requirements.txt para obtener información sobre las dependencias de la aplicación. Usa el comando pip freeze para listar todas las dependencias y sus versiones, y escríbelas en requirements.txt.\n\n```sh\nasabeneh@Asabeneh:~/Desktop/python_for_web$ pip freeze\nClick==7.0\nFlask==1.1.1\nitsdangerous==1.1.0\nJinja2==2.10.3\nMarkupSafe==1.1.1\nWerkzeug==0.16.0\nasabeneh@Asabeneh:~/Desktop/python_for_web$ pip freeze > requirements.txt\n```\n\nProcfile le dice a Heroku cómo ejecutar la aplicación. En este caso, usamos Gunicorn como servidor HTTP WSGI para ejecutar aplicaciones web en Python. Necesitamos agregar Gunicorn a nuestras dependencias.\n\n```sh\nasabeneh@Asabeneh:~/Desktop/python_for_web$ pip install gunicorn\nasabeneh@Asabeneh:~/Desktop/python_for_web$ pip freeze > requirements.txt\n```\n\nAhora, creemos un Procfile y agreguemos el siguiente contenido:\n\n```sh\nweb: gunicorn app:app\n```\n\n#### Enviar el proyecto a Heroku\n\n```sh\nasabeneh@Asabeneh:~/Desktop/python_for_web$ heroku create 30-days-of-python-app\nCreating ⬢ 30-days-of-python-app... done\nhttps://30-days-of-python-app.herokuapp.com/ | https://git.heroku.com/30-days-of-python-app.git\nasabeneh@Asabeneh:~/Desktop/python_for_web$ git init\nInitialized empty Git repository in /home/asabeneh/Desktop/python_for_web/.git/\nasabeneh@Asabeneh:~/Desktop/python_for_web$ heroku git:remote -a 30-days-of-python-app\nset git remote heroku to https://git.heroku.com/30-days-of-python-app.git\nasabeneh@Asabeneh:~/Desktop/python_for_web$ echo -e \"venv\\n.vscode\" > .gitignore\nasabeneh@Asabeneh:~/Desktop/python_for_web$ git add .\nasabeneh@Asabeneh:~/Desktop/python_for_web$ git commit -m \"primer aplicación web en python\"\n[master (root-commit) 9dfcc6a] primer aplicación web en python\n 9 files changed, 403 insertions(+)\n create mode 100644 .gitignore\n create mode 100644 Procfile\n create mode 100644 app.py\n create mode 100644 requirements.txt\n create mode 100644 static/css/main.css\n create mode 100644 templates/about.html\n create mode 100644 templates/home.html\n create mode 100644 templates/layout.html\n create mode 100644 templates/post.html\n create mode 100644 templates/result.html\nasabeneh@Asabeneh:~/Desktop/python_for_web$ git push heroku master\nEnumerating objects: 14, done.\nCounting objects: 100% (14/14), done.\nDelta compression using up to 2 threads\nCompressing objects: 100% (12/12), done.\nWriting objects: 100% (14/14), 6.08 KiB | 1.52 MiB/s, done.\nTotal 14 (delta 2), reused 0 (delta 0)\nremote: Compressing source files... done.\nremote: Building source:\nremote:\nremote: -----> Python app detected\nremote: -----> Installing python-3.6.10\nremote: -----> Installing pip\nremote: -----> Installing dependencies with Pipenv 2018.5.18…\nremote: Installing dependencies from Pipfile.lock (872ae5)…\nremote: -----> Installing SQLite3\nremote: -----> $ python manage.py collectstatic --noinput\nremote: Traceback (most recent call last):\nremote: File \"manage.py\", line 10, in \nremote: from app import app\nremote: ModuleNotFoundError: No module named 'app'\nremote:\nremote: ! Error while running '$ python manage.py collectstatic --noinput'.\nremote: See traceback above for details.\nremote:\nremote: You may need to update application code to resolve this error.\nremote: Or, you can disable collectstatic for this application:\nremote:\nremote: $ heroku config:set DISABLE_COLLECTSTATIC=1\nremote:\nremote: https://devcenter.heroku.com/articles/django-assets\nremote: -----> Discovering process types\nremote: Procfile declares types -> web\nremote:\nremote: -----> Compressing...\nremote: Done: 55.7M\nremote: -----> Launching...\nremote: Released v3\nremote: https://30-days-of-python-app.herokuapp.com/ deployed to Heroku\nremote:\nremote: Verifying deploy... done.\nTo https://git.heroku.com/30-days-of-python-app.git\n * [new branch] master -> master\nasabeneh@Asabeneh:~/Desktop/python_for_web$\n```\n\nComo puedes ver, hemos creado con éxito nuestra primera aplicación web, la hemos desplegado y la hemos alojado en Heroku. Puedes probar esta aplicación usando este [enlace](https://30-days-of-python-app.herokuapp.com/).\n\nSin más preámbulos, realicemos algunos ejercicios para reforzar lo aprendido.\n\n## Ejercicios: Día 26\n\n1. Crea una aplicación Flask llamada \"Calculadora de calificaciones\". El usuario ingresa la nota y el nombre de la asignatura, y la aplicación debe mostrar un mensaje según la nota:\n - Si nota ≥ 90: \"¡Excelente! Tu calificación en [Asignatura] es [Nota]\".\n - Si 80 ≤ nota < 90: \"¡Muy bien! Tu calificación en [Asignatura] es [Nota]\".\n - Si 70 ≤ nota < 80: \"Regular. Tu calificación en [Asignatura] es [Nota]\".\n - Si 60 ≤ nota < 70: \"Aprobaste. Tu calificación en [Asignatura] es [Nota]\".\n - Si nota < 60: \"¡Necesitas esforzarte más! Tu calificación en [Asignatura] es [Nota]\".\n\n2. Crea una aplicación \"Calculadora de IMC\" que calcule el índice de masa corporal (IMC = peso(kg) / altura(m)²) y muestre el estado según el IMC:\n - IMC < 18.5: \"Bajo peso\"\n - 18.5 ≤ IMC < 24.9: \"Peso saludable\"\n - 25 ≤ IMC < 29.9: \"Sobrepeso\"\n - IMC ≥ 30: \"Obesidad\"\n\n3. Crea una aplicación de blog donde los usuarios puedan añadir, editar y eliminar publicaciones.\n\n4. Crea una aplicación \"Gestor de tareas\" donde los usuarios puedan añadir, ver y eliminar tareas.\n\n🎉 ¡Felicidades! 🎉\n\n[<< Día 25](./25_pandas_sp.md) | [>> Día 27](./27_python_with_mongodb_sp.md)"
},
{
"path": "Spanish/27_python_with_mongodb_sp.md",
"content": "# Reto de 30 días de Python: Día 27 - Python y MongoDB\n\n- [Día 27](#-día-27)\n- [Python y MongoDB](#python-y-mongodb)\n - [MongoDB](#mongodb)\n - [Comparación entre SQL y NoSQL](#comparación-entre-sql-y-nosql)\n - [Obtener la cadena de conexión (URI de MongoDB)](#obtener-la-cadena-de-conexión-uri-de-mongodb)\n - [Conectar una aplicación Flask a un clúster de MongoDB](#conectar-una-aplicación-flask-a-un-clúster-de-mongodb)\n - [Crear base de datos y colecciones](#crear-base-de-datos-y-colecciones)\n - [Insertar múltiples documentos en una colección](#insertar-múltiples-documentos-en-una-colección)\n - [Consultas en MongoDB](#consultas-en-mongodb)\n - [Buscar usando una consulta](#buscar-usando-una-consulta)\n - [Buscar con modificadores](#buscar-con-modificadores)\n - [Limitar la cantidad de documentos](#limitar-la-cantidad-de-documentos)\n - [Buscar con ordenamiento](#buscar-con-ordenamiento)\n - [Actualizar usando una consulta](#actualizar-usando-una-consulta)\n - [Eliminar documentos](#eliminar-documentos)\n - [Eliminar una colección](#eliminar-una-colección)\n - [💻 Ejercicio: Día 27](#-ejercicio-día-27)\n\n# 📘 Día 27\n\n# Python y MongoDB\n\nPython es una tecnología backend que puede conectarse a distintas bases de datos. Puede conectarse a bases de datos SQL y NoSQL. En esta sección conectaremos Python con la base de datos MongoDB, que es una base de datos NoSQL.\n\n## MongoDB\n\nMongoDB es una base de datos NoSQL. MongoDB almacena datos en documentos tipo JSON, lo que hace a MongoDB muy flexible y escalable. Veamos la terminología que difiere entre bases de datos SQL y NoSQL. La siguiente tabla mostrará la diferencia entre SQL y NoSQL.\n\n### Comparación entre SQL y NoSQL\n\n\n\nEn esta sección nos centraremos en la base de datos NoSQL MongoDB. Regístrate en [MongoDB](https://www.mongodb.com/) haciendo clic en registrarse y luego en la página siguiente confirma el registro.\n\n\n\nRellena el formulario y haz clic en continuar..\n\n\n\nElige el plan gratuito\n\n\n\nElige la región gratuita más cercana y ponle un nombre a tu clúster.\n\n\n\nAhora se ha creado un sandbox gratuito\n\n\n\nPermitir el acceso desde todos los hosts locales\n\n\n\nAgregar usuario y contraseña\n\n\n\nCrear enlace URI de MongoDB\n\n\n\nSelecciona el driver para Python 3.6 o superior\n\n\n\n### Obtener la cadena de conexión (URI de MongoDB)\n\nCopia la cadena de conexión; obtendrás algo similar a esto:\n\n```sh\nmongodb+srv://asabeneh:@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority\n```\n\nNo te preocupes por esta URL; es la forma de conectar tu aplicación con MongoDB.\nReemplaza el marcador de contraseña con la contraseña que creaste al añadir el usuario.\n\nEjemplo:\n\n```sh\nmongodb+srv://asabeneh:123123123@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority\n```\n\nEn este ejemplo reemplacé todo y la contraseña es 123123123; el nombre de la base de datos es *thirty_days_python*. Esto solo es un ejemplo; tu contraseña debe ser más segura.\n\nPython necesita drivers para acceder a MongoDB. Usaremos _pymongo_ y _dnspython_ para conectar nuestra aplicación con la base de MongoDB. Instala pymongo y dnspython en tu directorio de proyecto:\n\n```sh\npip install pymongo dnspython\n```\n\nPara usar el URI mongodb+srv:// debes instalar el módulo \"dnspython\". dnspython es un paquete de utilidades DNS para Python que soporta prácticamente todos los tipos de registros.\n\n### Conectar una aplicación Flask a un clúster de MongoDB\n\n```py\n# importar flask\nfrom flask import Flask, render_template\nimport os # importar el módulo os\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\nprint(client.list_database_names())\n\napp = Flask(__name__)\nif __name__ == '__main__':\n # en despliegue usamos variables de entorno\n # para que funcione tanto en producción como en desarrollo\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\nAl ejecutar el código anterior obtendremos las bases de datos por defecto de MongoDB.\n\n```sh\n['admin', 'local']\n```\n\n### Crear base de datos y colecciones\n\nCreemos una base de datos; si la base de datos y la colección no existen en MongoDB, se crearán. Crearemos una base de datos llamada *thirty_days_of_python* y una colección *students*.\n\nFormas de crear la base de datos:\n\n```sh\ndb = client.name_of_database # podemos crear la base de datos así, o usar la segunda forma\ndb = client['name_of_database']\n```\n\n```py\n# importar flask\nfrom flask import Flask, render_template\nimport os # importar el módulo os\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\n# crear la base de datos\ndb = client.thirty_days_of_python\n# crear la colección students e insertar un documento\ndb.students.insert_one({'name': 'Asabeneh', 'country': 'Finland', 'city': 'Helsinki', 'age': 250})\nprint(client.list_database_names())\n\napp = Flask(__name__)\nif __name__ == '__main__':\n # en despliegue usamos variables de entorno\n # para que funcione tanto en producción como en desarrollo\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\nDespués de crear la base de datos, también creamos la colección students y usamos *insert_one()* para insertar un documento.\nAhora la base de datos *thirty_days_of_python* y la colección *students* han sido creadas y el documento insertado.\nRevisa tu clúster MongoDB y verás la base de datos y la colección, con un documento dentro.\n\n```sh\n['thirty_days_of_python', 'admin', 'local']\n```\n\nSi ves lo anterior en tu clúster, significa que has creado con éxito una base de datos y una colección.\n\n\n\nSi ves la imagen anterior, el documento fue creado con un ID largo como clave primaria. Cada vez que incrustamos un documento, MongoDB le asigna un ID único.\n\n### Insertar múltiples documentos en una colección\n\n*insert_one()* inserta un elemento a la vez; si queremos insertar múltiples documentos de una vez podemos usar *insert_many()* o un bucle for.\nPodemos usar un bucle for para insertar varios documentos a la vez.\n\n```py\n# importar flask\nfrom flask import Flask, render_template\nimport os # importar el módulo os\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\n\nstudents = [\n {'name':'David','country':'UK','city':'London','age':34},\n {'name':'John','country':'Sweden','city':'Stockholm','age':28},\n {'name':'Sami','country':'Finland','city':'Helsinki','age':25},\n ]\nfor student in students:\n db.students.insert_one(student)\n\napp = Flask(__name__)\nif __name__ == '__main__':\n # en despliegue usamos variables de entorno\n # para que funcione tanto en producción como en desarrollo\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\n### Consultas en MongoDB\n\nLos métodos *find()* y *findOne()* son formas comunes de buscar datos en una colección MongoDB. Son similares al SELECT en MySQL.\nUsemos _find_one()_ para obtener un documento de la colección.\n\n- *find_one({\"_id\": ObjectId(\"id\")}): si no se proporciona id, devuelve la primera aparición.\n\n```py\n# importar flask\nfrom flask import Flask, render_template\nimport os # importar el módulo os\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # acceder a la base de datos\nstudent = db.students.find_one()\nprint(student)\n\napp = Flask(__name__)\nif __name__ == '__main__':\n # en despliegue usamos variables de entorno\n # para que funcione tanto en producción como en desarrollo\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\n```sh\n{'_id': ObjectId('5df68a21f106fe2d315bbc8b'), 'name': 'Asabeneh', 'country': 'Finland', 'city': 'Helsinki', 'age': 250}\n```\n\nLa consulta anterior devuelve la primera entrada, pero podemos usar un _id_ específico para ubicar un documento concreto. Por ejemplo, usemos el id de David para obtener el objeto David.\n'_id':ObjectId('5df68a23f106fe2d315bbc8c')\n\n```py\n# importar flask\nfrom flask import Flask, render_template\nimport os # importar el módulo os\nfrom bson.objectid import ObjectId # objeto id\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # acceder a la base de datos\nstudent = db.students.find_one({'_id':ObjectId('5df68a23f106fe2d315bbc8c')})\nprint(student)\n\napp = Flask(__name__)\nif __name__ == '__main__':\n # en despliegue usamos variables de entorno\n # para que funcione tanto en producción como en desarrollo\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\n```sh\n{'_id': ObjectId('5df68a23f106fe2d315bbc8c'), 'name': 'David', 'country': 'UK', 'city': 'London', 'age': 34}\n```\n\nHemos visto cómo usar _find_one()_. Veamos ahora _find()_.\n\n- _find()_: si no pasamos un objeto consulta devuelve todas las apariciones en la colección. El resultado es un objeto pymongo.cursor.\n\n```py\n# importar flask\nfrom flask import Flask, render_template\nimport os # importar el módulo os\n\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # acceder a la base de datos\nstudents = db.students.find()\nfor student in students:\n print(student)\n\napp = Flask(__name__)\nif __name__ == '__main__':\n # en despliegue usamos variables de entorno\n # para que funcione tanto en producción como en desarrollo\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\n```sh\n{'_id': ObjectId('5df68a21f106fe2d315bbc8b'), 'name': 'Asabeneh', 'country': 'Finland', 'city': 'Helsinki', 'age': 250}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8c'), 'name': 'David', 'country': 'UK', 'city': 'London', 'age': 34}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8d'), 'name': 'John', 'country': 'Sweden', 'city': 'Stockholm', 'age': 28}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8e'), 'name': 'Sami', 'country': 'Finland', 'city': 'Helsinki', 'age': 25}\n```\n\nPodemos especificar los campos a devolver pasando un segundo objeto a _find({}, {})_. 0 significa excluir, 1 incluir; no se puede mezclar 0 y 1 excepto para _id.\n\n```py\n# importar flask\nfrom flask import Flask, render_template\nimport os # importar el módulo os\n\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # acceder a la base de datos\nstudents = db.students.find({}, {\"_id\":0, \"name\": 1, \"country\":1}) # 0 excluir, 1 incluir\nfor student in students:\n print(student)\n\napp = Flask(__name__)\nif __name__ == '__main__':\n # en despliegue usamos variables de entorno\n # para que funcione tanto en producción como en desarrollo\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\n```sh\n{'name': 'Asabeneh', 'country': 'Finland'}\n{'name': 'David', 'country': 'UK'}\n{'name': 'John', 'country': 'Sweden'}\n{'name': 'Sami', 'country': 'Finland'}\n```\n\n### Buscar usando una consulta\n\nEn MongoDB, find acepta un objeto de consulta. Podemos pasar ese objeto para filtrar los documentos que queremos.\n\n```py\n# importar flask\nfrom flask import Flask, render_template\nimport os # importar el módulo os\n\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # acceder a la base de datos\n\nquery = {\n \"country\":\"Finland\"\n}\nstudents = db.students.find(query)\n\nfor student in students:\n print(student)\n\napp = Flask(__name__)\nif __name__ == '__main__':\n # en despliegue usamos variables de entorno\n # para que funcione tanto en producción como en desarrollo\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\n```sh\n{'_id': ObjectId('5df68a21f106fe2d315bbc8b'), 'name': 'Asabeneh', 'country': 'Finland', 'city': 'Helsinki', 'age': 250}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8e'), 'name': 'Sami', 'country': 'Finland', 'city': 'Helsinki', 'age': 25}\n```\n\n### Buscar con modificadores\n\n```py\n# importar flask\nfrom flask import Flask, render_template\nimport os # importar el módulo os\nimport pymongo\n\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # acceder a la base de datos\n\nquery = {\n \"city\":\"Helsinki\"\n}\nstudents = db.students.find(query)\nfor student in students:\n print(student)\n\napp = Flask(__name__)\nif __name__ == '__main__':\n # en despliegue usamos variables de entorno\n # para que funcione tanto en producción como en desarrollo\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\n```sh\n{'_id': ObjectId('5df68a21f106fe2d315bbc8b'), 'name': 'Asabeneh', 'country': 'Finland', 'city': 'Helsinki', 'age': 250}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8e'), 'name': 'Sami', 'country': 'Finland', 'city': 'Helsinki', 'age': 25}\n```\n\n### Buscar con modificadores (combinados)\n\n```py\n# importar flask\nfrom flask import Flask, render_template\nimport os # importar el módulo os\nimport pymongo\n\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # acceder a la base de datos\nquery = {\n \"country\":\"Finland\",\n \"city\":\"Helsinki\"\n}\nstudents = db.students.find(query)\nfor student in students:\n print(student)\n\napp = Flask(__name__)\nif __name__ == '__main__':\n # en despliegue usamos variables de entorno\n # para que funcione tanto en producción como en desarrollo\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\n```sh\n{'_id': ObjectId('5df68a21f106fe2d315bbc8b'), 'name': 'Asabeneh', 'country': 'Finland', 'city': 'Helsinki', 'age': 250}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8e'), 'name': 'Sami', 'country': 'Finland', 'city': 'Helsinki', 'age': 25}\n```\n\nEjemplos con operadores:\n\n```py\n# importar flask\nfrom flask import Flask, render_template\nimport os # importar el módulo os\nimport pymongo\n\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # acceder a la base de datos\nquery = {\"age\":{\"$gt\":30}}\nstudents = db.students.find(query)\nfor student in students:\n print(student)\n\napp = Flask(__name__)\nif __name__ == '__main__':\n # en despliegue usamos variables de entorno\n # para que funcione tanto en producción como en desarrollo\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\n```sh\n{'_id': ObjectId('5df68a21f106fe2d315bbc8b'), 'name': 'Asabeneh', 'country': 'Finland', 'city': 'Helsinki', 'age': 250}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8c'), 'name': 'David', 'country': 'UK', 'city': 'London', 'age': 34}\n```\n\n```py\n# importar flask\nfrom flask import Flask, render_template\nimport os # importar el módulo os\nimport pymongo\n\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # acceder a la base de datos\nquery = {\"age\":{\"$lt\":30}}\nstudents = db.students.find(query)\nfor student in students:\n print(student)\n```\n\n```sh\n{'_id': ObjectId('5df68a23f106fe2d315bbc8d'), 'name': 'John', 'country': 'Sweden', 'city': 'Stockholm', 'age': 28}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8e'), 'name': 'Sami', 'country': 'Finland', 'city': 'Helsinki', 'age': 25}\n```\n\n### Limitar la cantidad de documentos\n\nPodemos usar el método _limit()_ para restringir el número de documentos devueltos.\n\n```py\n# importar flask\nfrom flask import Flask, render_template\nimport os # importar el módulo os\nimport pymongo\n\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # acceder a la base de datos\ndb.students.find().limit(3)\n```\n\n### Buscar con ordenamiento\n\nPor defecto el orden es ascendente. Podemos cambiar a descendente pasando -1.\n\n```py\n# importar flask\nfrom flask import Flask, render_template\nimport os # importar el módulo os\nimport pymongo\n\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # acceder a la base de datos\nstudents = db.students.find().sort('name')\nfor student in students:\n print(student)\n\nstudents = db.students.find().sort('name',-1)\nfor student in students:\n print(student)\n\nstudents = db.students.find().sort('age')\nfor student in students:\n print(student)\n\nstudents = db.students.find().sort('age',-1)\nfor student in students:\n print(student)\n\napp = Flask(__name__)\nif __name__ == '__main__':\n # en despliegue usamos variables de entorno\n # para que funcione tanto en producción como en desarrollo\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\nAscendente\n\n```sh\n{'_id': ObjectId('5df68a21f106fe2d315bbc8b'), 'name': 'Asabeneh', 'country': 'Finland', 'city': 'Helsinki', 'age': 250}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8c'), 'name': 'David', 'country': 'UK', 'city': 'London', 'age': 34}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8d'), 'name': 'John', 'country': 'Sweden', 'city': 'Stockholm', 'age': 28}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8e'), 'name': 'Sami', 'country': 'Finland', 'city': 'Helsinki', 'age': 25}\n```\n\nDescendente\n\n```sh\n{'_id': ObjectId('5df68a23f106fe2d315bbc8e'), 'name': 'Sami', 'country': 'Finland', 'city': 'Helsinki', 'age': 25}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8d'), 'name': 'John', 'country': 'Sweden', 'city': 'Stockholm', 'age': 28}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8c'), 'name': 'David', 'country': 'UK', 'city': 'London', 'age': 34}\n{'_id': ObjectId('5df68a21f106fe2d315bbc8b'), 'name': 'Asabeneh', 'country': 'Finland', 'city': 'Helsinki', 'age': 250}\n```\n\n### Actualizar usando una consulta\n\nUsaremos *update_one()* para actualizar un documento. Acepta dos objetos: la consulta y el nuevo valor.\nLa primera persona, Asabeneh, tenía una edad poco razonable. Actualicemos la edad de Asabeneh.\n\n```py\n# importar flask\nfrom flask import Flask, render_template\nimport os # importar el módulo os\nimport pymongo\n\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # acceder a la base de datos\n\nquery = {'age':250}\nnew_value = {'$set':{'age':38}}\n\ndb.students.update_one(query, new_value)\n# verifiquemos el resultado para ver si la edad fue modificada\nfor student in db.students.find():\n print(student)\n\napp = Flask(__name__)\nif __name__ == '__main__':\n # en despliegue usamos variables de entorno\n # para que funcione tanto en producción como en desarrollo\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\n```sh\n{'_id': ObjectId('5df68a21f106fe2d315bbc8b'), 'name': 'Asabeneh', 'country': 'Finland', 'city': 'Helsinki', 'age': 38}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8c'), 'name': 'David', 'country': 'UK', 'city': 'London', 'age': 34}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8d'), 'name': 'John', 'country': 'Sweden', 'city': 'Stockholm', 'age': 28}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8e'), 'name': 'Sami', 'country': 'Finland', 'city': 'Helsinki', 'age': 25}\n```\n\nSi queremos actualizar varios documentos a la vez usamos *update_many()*.\n\n### Eliminar documentos\n\nEl método *delete_one()* elimina un documento. Acepta un objeto consulta y elimina la primera aparición.\nEliminemos a John de la colección.\n\n```py\n# importar flask\nfrom flask import Flask, render_template\nimport os # importar el módulo os\nimport pymongo\n\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # acceder a la base de datos\n\nquery = {'name':'John'}\ndb.students.delete_one(query)\n\nfor student in db.students.find():\n print(student)\n# verifiquemos el resultado\n\napp = Flask(__name__)\nif __name__ == '__main__':\n # en despliegue usamos variables de entorno\n # para que funcione tanto en producción como en desarrollo\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\n```sh\n{'_id': ObjectId('5df68a21f106fe2d315bbc8b'), 'name': 'Asabeneh', 'country': 'Finland', 'city': 'Helsinki', 'age': 38}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8c'), 'name': 'David', 'country': 'UK', 'city': 'London', 'age': 34}\n{'_id': ObjectId('5df68a23f106fe2d315bbc8e'), 'name': 'Sami', 'country': 'Finland', 'city': 'Helsinki', 'age': 25}\n```\n\nComo puedes ver, John ha sido eliminado de la colección.\n\nSi queremos eliminar varios documentos usamos *delete_many()* con un objeto consulta. Si pasamos un objeto vacío *delete_many({})* eliminará todos los documentos en la colección.\n\n### Eliminar una colección\n\nUsando el método _drop()_ podemos eliminar una colección de la base de datos.\n\n```py\n# importar flask\nfrom flask import Flask, render_template\nimport os # importar el módulo os\nimport pymongo\n\nMONGODB_URI = 'mongodb+srv://asabeneh:your_password_goes_here@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # acceder a la base de datos\ndb.students.drop()\n```\n\nAhora hemos eliminado la colección students de la base de datos.\n\n## 💻 Ejercicio: Día 27\n\n🎉 ¡Felicidades! 🎉\n\n[<< Día 26](./26_python_web_sp.md) | [Día 28 >>](./28_API_sp.md)"
},
{
"path": "Spanish/28_API_sp.md",
"content": "# Reto de 30 días de Python: Día 28 - API\n\n- [Día 28](#-día-28)\n- [Interfaz de Programación de Aplicaciones (API)](#interfaz-de-programación-de-aplicaciones-api)\n - [API](#api)\n - [Construir una API](#construir-una-api)\n - [HTTP (Protocolo de transferencia de hipertexto)](#http-protocolo-de-transferencia-de-hipertexto)\n - [Estructura de HTTP](#estructura-de-http)\n - [Línea inicial de solicitud (línea de estado)](#línea-inicial-de-solicitud-línea-de-estado)\n - [Línea inicial de respuesta (línea de estado)](#línea-inicial-de-respuesta-línea-de-estado)\n - [Campos de cabecera](#campos-de-cabecera)\n - [Cuerpo del mensaje](#cuerpo-del-mensaje)\n - [Métodos de solicitud](#métodos-de-solicitud)\n - [💻 Ejercicio: Día 28](#-ejercicio-día-28)\n\n# 📘 Día 28\n\n# Interfaz de Programación de Aplicaciones (API)\n\n## API\n\nAPI son las siglas de Application Programming Interface (Interfaz de Programación de Aplicaciones). El tipo de API que veremos en esta sección es la Web API.\nUna Web API es una interfaz definida que permite la interacción entre organizaciones y las aplicaciones que consumen sus recursos; también actúa como un contrato de nivel de servicio (SLA) que especifica al proveedor de la funcionalidad y expone rutas o URLs de servicio a los usuarios de la API.\n\nEn el contexto del desarrollo web, una API se define como un conjunto de especificaciones, por ejemplo mensajes de solicitud HTTP y la estructura de los mensajes de respuesta, normalmente en formato XML o JSON (JavaScript Object Notation).\n\nLas Web APIs han evolucionado de servicios web basados en SOAP y arquitecturas orientadas a servicios (SOA) hacia recursos web más directos en estilo REST.\n\nLos servicios de redes sociales y las Web APIs han permitido a la comunidad web compartir contenido y datos entre comunidades y plataformas.\n\nCon las APIs, el contenido creado en un lugar puede publicarse y actualizarse dinámicamente en múltiples lugares de la web.\n\nPor ejemplo, la REST API de Twitter permite a los desarrolladores acceder a los datos principales de Twitter, mientras que la Search API ofrece formas de interactuar con los datos de búsqueda y tendencias de Twitter.\n\nMuchas aplicaciones exponen endpoints de API. Algunos ejemplos de APIs son la [API de países](https://restcountries.eu/rest/v2/all) y la [API de razas de gatos](https://api.thecatapi.com/v1/breeds).\n\nEn esta sección presentaremos una API RESTful que utiliza métodos de solicitud HTTP como GET, PUT, POST y DELETE para manejar datos.\n\n## Construir una API\n\nUna API RESTful es una interfaz que usa solicitudes HTTP para GET, PUT, POST y DELETE datos. En secciones anteriores aprendimos Python, Flask y MongoDB. Aprovecharemos ese conocimiento para desarrollar una API RESTful usando Python, Flask y la base de datos MongoDB. Toda aplicación con operaciones CRUD (Crear, Leer, Actualizar, Eliminar) suele exponer una API para crear datos en la base, obtener datos, actualizarlos o borrarlos.\n\nPara construir una API es útil entender el protocolo HTTP y el ciclo de solicitud-respuesta HTTP.\n\n## HTTP (Protocolo de transferencia de hipertexto)\n\nHTTP es el protocolo de comunicación establecido entre cliente y servidor. En este caso, el cliente es el navegador y el servidor es el lugar desde donde obtienes los datos. HTTP es un protocolo de red utilizado para transferir recursos en la web, como archivos HTML, imágenes, resultados de consultas, scripts u otros tipos de archivos.\n\nEl navegador actúa como cliente HTTP porque envía solicitudes al servidor HTTP (servidor web), y el servidor responde al cliente.\n\n## Estructura de HTTP\n\nHTTP utiliza un modelo cliente-servidor. El cliente HTTP abre una conexión y envía un mensaje de solicitud al servidor HTTP; el servidor HTTP devuelve un mensaje de respuesta, es decir, el recurso solicitado. Cuando el ciclo solicitud-respuesta termina, el servidor cierra la conexión.\n\n\n\nLos formatos de los mensajes de solicitud y respuesta son similares. Ambos mensajes contienen:\n\n- Una línea inicial\n- Cero o más líneas de cabecera\n- Una línea en blanco (es decir, un CRLF por separado)\n- Un cuerpo de mensaje opcional (por ejemplo, un archivo, datos de formulario o la salida de una consulta)\n\nNavega por este sitio para ver un ejemplo de mensaje de solicitud y respuesta: https://thirtydaysofpython-v1-final.herokuapp.com/. Este sitio está desplegado en un dyno gratuito de Heroku y puede no estar disponible en algunos meses debido al alto tráfico. Apoyar este proyecto ayuda a mantener el servidor activo.\n\n\n\n## Línea inicial de solicitud (línea de estado)\n\nLa línea inicial de la solicitud difiere de la de la respuesta.\nLa línea de solicitud tiene tres partes separadas por espacios:\n\n- El nombre del método (GET, POST, HEAD)\n- La ruta del recurso solicitado\n- La versión HTTP utilizada. Por ejemplo: GET / HTTP/1.1\n\nGET es el método HTTP más común, usado para obtener o leer recursos, mientras que POST es un método común para crear recursos.\n\n### Línea inicial de respuesta (línea de estado)\n\nLa línea inicial de la respuesta, llamada línea de estado, también tiene tres partes separadas por espacios:\n\n- La versión HTTP\n- El código de estado de la respuesta, que indica el resultado de la solicitud, junto con una razón que describe dicho código. Ejemplos de líneas de estado:\n HTTP/1.0 200 OK\n o\n HTTP/1.0 404 Not Found\n **Nota:**\n\nLos códigos de estado más comunes son:\n200 OK: la solicitud fue exitosa y el recurso generado (por ejemplo un archivo o la salida de un script) se devuelve en el cuerpo del mensaje.\n500 Error del servidor\nLa lista completa de códigos de estado HTTP puede encontrarse [aquí](https://httpstatuses.com/). También puedes verla [aquí](https://httpstatusdogs.com/).\n\n### Campos de cabecera\n\nComo se observa en la captura anterior, las líneas de cabecera proporcionan información sobre la solicitud o la respuesta, o sobre el objeto enviado en el cuerpo del mensaje.\n\n```sh\nGET / HTTP/1.1\nHost: thirtydaysofpython-v1-final.herokuapp.com\nConnection: keep-alive\nPragma: no-cache\nCache-Control: no-cache\nUpgrade-Insecure-Requests: 1\nUser-Agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_14_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/79.0.3945.79 Safari/537.36\nSec-Fetch-User: ?1\nAccept: text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.9\nSec-Fetch-Site: same-origin\nSec-Fetch-Mode: navigate\nReferer: https://thirtydaysofpython-v1-final.herokuapp.com/post\nAccept-Encoding: gzip, deflate, br\nAccept-Language: en-GB,en;q=0.9,fi-FI;q=0.8,fi;q=0.7,en-CA;q=0.6,en-US;q=0.5,fr;q=0.4\n```\n\n### Cuerpo del mensaje\n\nUn mensaje HTTP puede llevar un cuerpo después de las cabeceras. En una respuesta, este es el lugar donde el recurso solicitado se devuelve al cliente (el uso más común del cuerpo). Si hay un error, puede contener texto explicativo. En una solicitud, es el lugar donde se envían los datos introducidos por el usuario o los archivos subidos al servidor.\n\nSi un mensaje HTTP contiene un cuerpo, normalmente hay cabeceras que describen ese cuerpo, en particular:\n\nContent-Type: indica el tipo MIME de los datos en el cuerpo (text/html, application/json, text/plain, text/css, image/gif).\nContent-Length: indica el número de bytes en el cuerpo del mensaje.\n\n### Métodos de solicitud\n\nGET, POST, PUT y DELETE son los métodos HTTP que usaremos para implementar la API y las operaciones CRUD.\n\n1. GET: el método GET se usa para recuperar y obtener información desde el servidor dado un URI. Las solicitudes GET deben únicamente recuperar datos y no producir otros efectos.\n2. POST: las solicitudes POST se usan para crear datos y enviar datos al servidor, por ejemplo al crear una nueva entrada con un formulario HTML o subir archivos.\n3. PUT: reemplaza la representación actual completa del recurso objetivo con la carga enviada; lo usamos para modificar o actualizar datos.\n4. DELETE: elimina datos.\n\n## 💻 Ejercicio: Día 28\n\n1. Lee recursos sobre APIs y HTTP\n\n🎉 ¡Felicidades! 🎉\n\n[<< Día 27](./27_python_with_mongodb_sp.md) | [Día 29 >>](./29_building_API_sp.md)\n"
},
{
"path": "Spanish/29_building_API_sp.md",
"content": "# Reto de 30 días de Python: Día 29 - Construyendo una API\n\n- [Día 29](#día-29)\n- [Construyendo una API](#construyendo-una-api)\n - [Estructura de la API](#estructura-de-la-api)\n - [Obtener datos con GET](#obtener-datos-con-get)\n - [Obtener un documento por ID](#obtener-un-documento-por-id)\n - [Crear datos con POST](#crear-datos-con-post)\n - [Actualizar con PUT](#actualizar-con-put)\n - [Eliminar documentos con DELETE](#eliminar-documentos-con-delete)\n- [💻 Ejercicio: Día 29](#-ejercicio-día-29)\n\n## Día 29\n\n## Construyendo una API\n\nEn esta sección presentaremos una API RESTful que utiliza métodos HTTP como GET, PUT, POST y DELETE para manejar datos.\n\nUna API RESTful es una interfaz de programación de aplicaciones (API) que usa solicitudes HTTP para GET, PUT, POST y DELETE datos. En secciones anteriores aprendimos Python, Flask y MongoDB. Aprovecharemos ese conocimiento para desarrollar una API RESTful usando Python, Flask y MongoDB. Toda aplicación con operaciones CRUD (Crear, Leer, Actualizar, Eliminar) suele exponer una API para crear datos en la base, obtener datos, actualizarlos o borrarlos.\n\nLos navegadores solo manejan solicitudes GET. Por eso necesitamos una herramienta que nos permita manejar todos los métodos (GET, POST, PUT, DELETE).\n\nEjemplos de APIs:\n\n- API de países: https://restcountries.eu/rest/v2/all\n- API de razas de gatos: https://api.thecatapi.com/v1/breeds\n\n[Postman](https://www.getpostman.com/) es una herramienta muy popular en el desarrollo de APIs. Si quieres seguir esta sección, descarga [Postman](https://www.getpostman.com/). Una alternativa a Postman es [Insomnia](https://insomnia.rest/download).\n\n\n\n### Estructura de la API\n\nUn endpoint de API es una URL que ayuda a recuperar, crear, actualizar o eliminar un recurso. La estructura suele ser:\nEjemplo de endpoint:\nhttps://api.twitter.com/1.1/lists/members.json\nEste endpoint devuelve los miembros de una lista específica. Las listas privadas muestran miembros solo si el usuario autenticado posee la lista.\nEl nombre de la empresa va seguido de la versión y del propósito de la API.\nMétodos:\nMétodos HTTP: método y URL\n\nLa API usa los siguientes métodos HTTP para operar sobre objetos:\n\n```sh\nGET para recuperar objetos\nPOST para crear objetos y operaciones relacionadas\nPUT para actualizar objetos\nDELETE para eliminar objetos\n```\n\nConstruiremos una API para recopilar información sobre estudiantes de 30DaysOfPython. Recogemos nombre, país, ciudad, año de nacimiento, habilidades y biografía.\n\nPara implementar esta API utilizaremos:\n\n- Postman\n- Python\n- Flask\n- MongoDB\n\n### Obtener datos con GET\n\nEn este paso usaremos datos ficticios y los devolveremos como JSON. Para retornarlos como JSON usaremos el módulo json y Response.\n\n```py\n# importar flask\n\nfrom flask import Flask, Response\nimport json\n\napp = Flask(__name__)\n\n@app.route('/api/v1.0/students', methods = ['GET'])\ndef students ():\n student_list = [\n {\n 'name':'Asabeneh',\n 'country':'Finland',\n 'city':'Helsinki',\n 'skills':['HTML', 'CSS','JavaScript','Python']\n },\n {\n 'name':'David',\n 'country':'UK',\n 'city':'London',\n 'skills':['Python','MongoDB']\n },\n {\n 'name':'John',\n 'country':'Sweden',\n 'city':'Stockholm',\n 'skills':['Java','C#']\n }\n ]\n return Response(json.dumps(student_list), mimetype='application/json')\n\n\nif __name__ == '__main__':\n # usado en despliegue\n # para que funcione en producción y desarrollo\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\nSi solicitas http://localhost:5000/api/v1.0/students en el navegador obtendrás:\n\n\n\nSi solicitas la misma URL en Postman obtendrás:\n\n\n\nEn lugar de datos ficticios, conectaremos la aplicación Flask a MongoDB y obtendremos datos desde la base.\n\n```py\n# importar flask\n\nfrom flask import Flask, Response\nimport json\nimport pymongo\n\n\napp = Flask(__name__)\n\n#\nMONGODB_URI='mongodb+srv://asabeneh:your_password@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\n#Nota: nunca incluyas credenciales reales en el código.\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # acceder a la base de datos\n\n@app.route('/api/v1.0/students', methods = ['GET'])\ndef students ():\n\n return Response(json.dumps(student), mimetype='application/json')\n\n\nif __name__ == '__main__':\n # usado en despliegue\n # para que funcione en producción y desarrollo\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\nAl conectar Flask con MongoDB podemos obtener la colección students de la base thirty_days_of_python:\n\n```sh\n[\n {\n \"_id\": {\n \"$oid\": \"5df68a21f106fe2d315bbc8b\"\n },\n \"name\": \"Asabeneh\",\n \"country\": \"Finland\",\n \"city\": \"Helsinki\",\n \"age\": 38\n },\n {\n \"_id\": {\n \"$oid\": \"5df68a23f106fe2d315bbc8c\"\n },\n \"name\": \"David\",\n \"country\": \"UK\",\n \"city\": \"London\",\n \"age\": 34\n },\n {\n \"_id\": {\n \"$oid\": \"5df68a23f106fe2d315bbc8e\"\n },\n \"name\": \"Sami\",\n \"country\": \"Finland\",\n \"city\": \"Helsinki\",\n \"age\": 25\n }\n]\n```\n\n### Obtener un documento por ID\n\nPodemos acceder a un documento individual por su ID. Por ejemplo, accedamos a Asabeneh:\nhttp://localhost:5000/api/v1.0/students/5df68a21f106fe2d315bbc8b\n\n```py\n# importar flask\n\nfrom flask import Flask, Response\nimport json\nfrom bson.objectid import ObjectId\nimport json\nfrom bson.json_util import dumps\nimport pymongo\n\n\napp = Flask(__name__)\n\n#\nMONGODB_URI='mongodb+srv://asabeneh:your_password@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\n#Nota: nunca incluyas credenciales reales en el código.\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # acceder a la base de datos\n\n@app.route('/api/v1.0/students', methods = ['GET'])\ndef students ():\n\n return Response(json.dumps(student), mimetype='application/json')\n@app.route('/api/v1.0/students/', methods = ['GET'])\ndef single_student (id):\n student = db.students.find({'_id':ObjectId(id)})\n return Response(dumps(student), mimetype='application/json')\n\nif __name__ == '__main__':\n # usado en despliegue\n # para que funcione en producción y desarrollo\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\nRespuesta de ejemplo:\n\n```sh\n[\n {\n \"_id\": {\n \"$oid\": \"5df68a21f106fe2d315bbc8b\"\n },\n \"name\": \"Asabeneh\",\n \"country\": \"Finland\",\n \"city\": \"Helsinki\",\n \"age\": 38\n }\n]\n```\n\n### Crear datos con POST\n\nUsamos el método POST para crear datos.\n\n```py\n# importar flask\n\nfrom flask import Flask, Response, Request\nimport json\nfrom bson.objectid import ObjectId\nimport json\nfrom bson.json_util import dumps\nimport pymongo\nfrom datetime import datetime\n\n\n\napp = Flask(__name__)\n\n#\nMONGODB_URI='mongodb+srv://asabeneh:your_password@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\n#Nota: nunca incluyas credenciales reales en el código.\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # acceder a la base de datos\n\n@app.route('/api/v1.0/students', methods = ['GET'])\ndef students ():\n\n return Response(json.dumps(student), mimetype='application/json')\n@app.route('/api/v1.0/students/', methods = ['GET'])\ndef single_student (id):\n student = db.students.find({'_id':ObjectId(id)})\n return Response(dumps(student), mimetype='application/json')\n@app.route('/api/v1.0/students', methods = ['POST'])\ndef create_student ():\n name = request.form['name']\n country = request.form['country']\n city = request.form['city']\n skills = request.form['skills'].split(', ')\n bio = request.form['bio']\n birthyear = request.form['birthyear']\n created_at = datetime.now()\n student = {\n 'name': name,\n 'country': country,\n 'city': city,\n 'birthyear': birthyear,\n 'skills': skills,\n 'bio': bio,\n 'created_at': created_at\n\n }\n db.students.insert_one(student)\n return ;\ndef update_student (id):\nif __name__ == '__main__':\n # usado en despliegue\n # para que funcione en producción y desarrollo\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\n### Actualizar con PUT\n\n```py\n# importar flask\n\nfrom flask import Flask, Response\nimport json\nfrom bson.objectid import ObjectId\nimport json\nfrom bson.json_util import dumps\nimport pymongo\nfrom datetime import datetime\n\n\napp = Flask(__name__)\n\n#\nMONGODB_URI='mongodb+srv://asabeneh:your_password@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\n#Nota: nunca incluyas credenciales reales en el código.\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # acceder a la base de datos\n\n@app.route('/api/v1.0/students', methods = ['GET'])\ndef students ():\n\n return Response(json.dumps(student), mimetype='application/json')\n@app.route('/api/v1.0/students/', methods = ['GET'])\ndef single_student (id):\n student = db.students.find({'_id':ObjectId(id)})\n return Response(dumps(student), mimetype='application/json')\n@app.route('/api/v1.0/students', methods = ['POST'])\ndef create_student ():\n name = request.form['name']\n country = request.form['country']\n city = request.form['city']\n skills = request.form['skills'].split(', ')\n bio = request.form['bio']\n birthyear = request.form['birthyear']\n created_at = datetime.now()\n student = {\n 'name': name,\n 'country': country,\n 'city': city,\n 'birthyear': birthyear,\n 'skills': skills,\n 'bio': bio,\n 'created_at': created_at\n\n }\n db.students.insert_one(student)\n return\n@app.route('/api/v1.0/students/', methods = ['PUT']) # este decorador crea la ruta para actualizar\ndef update_student (id):\n query = {\"_id\":ObjectId(id)}\n name = request.form['name']\n country = request.form['country']\n city = request.form['city']\n skills = request.form['skills'].split(', ')\n bio = request.form['bio']\n birthyear = request.form['birthyear']\n created_at = datetime.now()\n student = {\n 'name': name,\n 'country': country,\n 'city': city,\n 'birthyear': birthyear,\n 'skills': skills,\n 'bio': bio,\n 'created_at': created_at\n\n }\n db.students.update_one(query, {\"$set\": student})\n # return Response(dumps({\"result\":\"a new student has been created\"}), mimetype='application/json')\n return\ndef update_student (id):\nif __name__ == '__main__':\n # usado en despliegue\n # para que funcione en producción y desarrollo\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\n### Eliminar documentos con DELETE\n\n```py\n# importar flask\n\nfrom flask import Flask, Response\nimport json\nfrom bson.objectid import ObjectId\nimport json\nfrom bson.json_util import dumps\nimport pymongo\nfrom datetime import datetime\n\n\napp = Flask(__name__)\n\n#\nMONGODB_URI='mongodb+srv://asabeneh:your_password@30daysofpython-twxkr.mongodb.net/test?retryWrites=true&w=majority'\n#Nota: nunca incluyas credenciales reales en el código.\nclient = pymongo.MongoClient(MONGODB_URI)\ndb = client['thirty_days_of_python'] # acceder a la base de datos\n\n@app.route('/api/v1.0/students', methods = ['GET'])\ndef students ():\n\n return Response(json.dumps(student), mimetype='application/json')\n@app.route('/api/v1.0/students/', methods = ['GET'])\ndef single_student (id):\n student = db.students.find({'_id':ObjectId(id)})\n return Response(dumps(student), mimetype='application/json')\n@app.route('/api/v1.0/students', methods = ['POST'])\ndef create_student ():\n name = request.form['name']\n country = request.form['country']\n city = request.form['city']\n skills = request.form['skills'].split(', ')\n bio = request.form['bio']\n birthyear = request.form['birthyear']\n created_at = datetime.now()\n student = {\n 'name': name,\n 'country': country,\n 'city': city,\n 'birthyear': birthyear,\n 'skills': skills,\n 'bio': bio,\n 'created_at': created_at\n\n }\n db.students.insert_one(student)\n return\n@app.route('/api/v1.0/students/', methods = ['PUT']) # este decorador crea la ruta para actualizar\ndef update_student (id):\n query = {\"_id\":ObjectId(id)}\n name = request.form['name']\n country = request.form['country']\n city = request.form['city']\n skills = request.form['skills'].split(', ')\n bio = request.form['bio']\n birthyear = request.form['birthyear']\n created_at = datetime.now()\n student = {\n 'name': name,\n 'country': country,\n 'city': city,\n 'birthyear': birthyear,\n 'skills': skills,\n 'bio': bio,\n 'created_at': created_at\n\n }\n db.students.update_one(query, {\"$set\": student})\n # return Response(dumps({\"result\":\"a new student has been created\"}), mimetype='application/json')\n return ;\n@app.route('/api/v1.0/students/', methods = ['DELETE'])\ndef delete_student (id):\n db.students.delete_one({\"_id\":ObjectId(id)})\n return\nif __name__ == '__main__':\n # usado en despliegue\n # para que funcione en producción y desarrollo\n port = int(os.environ.get(\"PORT\", 5000))\n app.run(debug=True, host='0.0.0.0', port=port)\n```\n\n## 💻 Ejercicio: Día 29\n\n1. Implementa los ejemplos anteriores y desarrolla [esta API](https://thirtydayofpython-api.herokuapp.com/)\n\n🎉 ¡Felicidades! 🎉\n\n[<< Día 28](./28_API_sp.md) | [Día 30 >>](./30_conclusions_sp.md)"
},
{
"path": "Spanish/30_conclusions_sp.md",
"content": "# Reto de 30 días de Python: Día 30 - Conclusiones\n\n- [Día 30](#día-30)\n - [Resumen](#resumen)\n - [Testimonios](#testimonios)\n\n# Día 30\n\n## Resumen\n\nAl preparar este material aprendí mucho y ustedes me motivaron a hacer más. Felicidades por llegar hasta aquí. Si has completado todos los ejercicios y proyectos, ahora tienes la capacidad de avanzar en análisis de datos, ciencia de datos, aprendizaje automático o desarrollo web. [Apoya al autor para más material educativo](https://www.paypal.com/paypalme/asabeneh).\n\n## Testimonios\n\nAhora es el momento de compartir tus pensamientos sobre el autor y el reto de 30 días de Python. Puedes dejar tu testimonio en este [enlace](https://www.asabeneh.com/testimonials).\n\nEnviar comentarios/retroalimentación:\nhttp://thirtydayofpython-api.herokuapp.com/feedback\n\n🎉 ¡Felicidades! 🎉\n\n[<< Día 29](./29_building_API_sp.md)"
},
{
"path": "Spanish/README_sp.md",
"content": "# 🐍 30 Días de Python\n\n| # Día | Tema |\n| ------ | :--------------------------------------------------------------------------------------: |\n| 01 | [Introducción](./readme_sp.md) |\n| 02 | [Variables y funciones integradas](./02_variables_builtin_functions_sp.md) |\n| 03 | [Operadores](./03_operators_sp.md) |\n| 04 | [Cadenas](./04_strings_sp.md) |\n| 05 | [Listas](./05_lists_sp.md) |\n| 06 | [Tuplas](./06_tuples_sp.md) |\n| 07 | [Conjuntos](./07_sets_sp.md) |\n| 08 | [Diccionarios](./08_dictionaries_sp.md) |\n| 09 | [Condicionales](./09_conditionals_sp.md) |\n| 10 | [Bucles](./10_loops_sp.md) |\n| 11 | [Funciones](./11_functions_sp.md) |\n| 12 | [Módulos](./12_modules_sp.md) |\n| 13 | [Comprensión de listas](./13_list_comprehension_sp.md) |\n| 14 | [Funciones de orden superior](./14_higher_order_functions_sp.md) |\n| 15 | [Errores de tipo](./15_python_type_errors_sp.md) |\n| 16 | [Fechas y horas en Python](./16_python_datetime_sp.md) |\n| 17 | [Manejo de excepciones](./17_exception_handling_sp.md) |\n| 18 | [Expresiones regulares](./18_regular_expressions_sp.md) |\n| 19 | [Manejo de archivos](./19_file_handling_sp.md) |\n| 20 | [Gestor de paquetes](./20_python_package_manager_sp.md) |\n| 21 | [Clases y objetos](./21_classes_and_objects_sp.md) |\n| 22 | [Web scraping](./22_web_scraping_sp.md) |\n| 23 | [Entornos virtuales](./23_virtual_environment_sp.md) |\n| 24 | [Estadística](./24_statistics_sp.md) |\n| 25 | [Pandas](./25_pandas_sp.md) |\n| 26 | [Python en la web](./26_python_web_sp.md) |\n| 27 | [Python y MongoDB](./27_python_with_mongodb_sp.md) |\n| 28 | [API](./28_API_sp.md) |\n| 29 | [Construir API](./29_building_API_sp.md) |\n| 30 | [Conclusiones](./30_conclusions_sp.md) |\n\n🧡🧡🧡 Feliz codificación 🧡🧡🧡\n\n
\nAyuda al autor a crear más material educativo \n\n
\n\n[Ir al Día 2 >>](./02_variables_builtin_functions_sp.md)\n\n\n\n- [🐍 30 Días de Python](#-30-días-de-python)\n- [📘 Día 1](#-día-1)\n - [¡Bienvenido!](#¡bienvenido!)\n - [Introducción](#introducción)\n - [¿Por qué elegir Python?](#¿por-qué-elegir-python?)\n - [Configuración del entorno](#configuración-del-entorno)\n - [Instalar Python](#instalar-python)\n - [Python Shell](#python-shell)\n - [Instalar Visual Studio Code](#instalar-visual-studio-code)\n - [Cómo usar Visual Studio Code](#cómo-usar-visual-studio-code)\n - [Fundamentos de Python](#fundamentos-de-python)\n - [Sintaxis de Python](#sintaxis-de-python)\n - [Indentación en Python](#indentación-en-python)\n - [Comentarios](#comentarios)\n- [Ejemplo: comentario de una sola línea](#ejemplo-comentario-de-una-sola-línea)\n- [Ejemplo: comentario multilínea (docstring)](#ejemplo-comentario-multilínea-docstring)\n - [Tipos de datos](#tipos-de-datos)\n - [Números](#números)\n - [Cadenas](#cadenas)\n - [Booleanos](#booleanos)\n - [Listas](#listas)\n - [Diccionarios](#diccionarios)\n - [Tuplas](#tuplas)\n - [Conjuntos](#conjuntos)\n - [Comprobar tipos de datos](#comprobar-tipos-de-datos)\n - [Archivos Python](#archivos-python)\n - [💻 Ejercicios - Día 1](#-ejercicios---día-1)\n - [Ejercicios: Nivel 1](#ejercicios-nivel-1)\n - [Ejercicios: Nivel 2](#ejercicios-nivel-2)\n - [Ejercicios: Nivel 3](#ejercicios-nivel-3)\n\n# 📘 Día 1\n\n## ¡Bienvenido!\n\n**Felicidades** por decidir participar en el desafío de programación _30 Días de Python_. En este reto aprenderás todo lo necesario para convertirte en programador Python y la mayoría de los conceptos de programación. Al finalizar el reto recibirás un certificado del desafío _30DaysOfPython_.\n\nSi quieres participar activamente, únete al grupo de Telegram [30DaysOfPython challenge](https://t.me/ThirtyDaysOfPython).\n\n## Introducción\n\nPython es un lenguaje de programación de alto nivel, de propósito general. Es un lenguaje de código abierto, interpretado y orientado a objetos. Python fue creado por el programador holandés Guido van Rossum. El nombre del lenguaje proviene del show cómico británico _Monty Python's Flying Circus_. La primera versión se lanzó el 20 de febrero de 1991. Este desafío de 30 días te ayudará a aprender progresivamente la versión más reciente de Python, Python 3. Cada día cubre un tema diferente con explicaciones claras, ejemplos del mundo real, y muchos ejercicios y proyectos prácticos.\n\nEl reto es adecuado para principiantes y profesionales que quieran aprender Python. Completar el reto puede tomar de 30 a 100 días; los miembros activos del grupo de Telegram tienen más probabilidades de terminarlo.\n\nEste reto fue escrito inicialmente en inglés sencillo, y luego traducido al chino. El reto es motivador, accesible y desafiante. Requiere dedicación para completarlo. Si aprendes mejor con vídeos, visita el canal Washera en YouTube: \nWashera YouTube channel. Puedes empezar por el video [Python for absolute beginners](https://youtu.be/OCCWZheOesI). Suscríbete, deja tus preguntas en los comentarios y sé proactivo; el autor te podrá notar.\n\nEl autor aprecia tus comentarios, que compartas el contenido y la retroalimentación sobre el reto 30DaysOfPython. Puedes dejar feedback aquí: [link](https://www.asabeneh.com/testimonials)\n\n## ¿Por qué elegir Python?\n\nPython es un lenguaje con sintaxis cercana al lenguaje humano, sencillo y fácil de aprender y usar.\nPython es usado en muchas industrias y empresas (incluido Google). Se usa para desarrollar aplicaciones web, de escritorio, administración de sistemas y librerías de aprendizaje automático. Python está ampliamente adoptado en la comunidad de ciencia de datos y machine learning. Si esto no te convence, ¡es hora de empezar!\n\n## Configuración del entorno\n\n### Instalar Python\n\nPara ejecutar scripts escritos en Python necesitas instalar Python. Visita la página de descargas de Python: [https://www.python.org/](https://www.python.org/).\n\nSi usas Windows haz clic en el botón marcado en la imagen.\n\n[](https://www.python.org/)\n\nSi usas macOS haz clic en el botón marcado en la imagen.\n\n[](https://www.python.org/)\n\nPara comprobar si Python está instalado, abre la terminal y ejecuta:\n\n```shell\npython --version\n```\n\n\n\nEn mi terminal aparece Python 3.7.5. Tu versión puede variar, pero debe ser 3.6 o superior. Si ves la versión, Python está instalado. Continúa al siguiente apartado.\n\n### Python Shell\n\nPython es un lenguaje interpretado, no necesita compilación. Se ejecuta línea por línea. Python incluye el Python Shell (intérprete interactivo), también llamado REPL (Read Eval Print Loop). Se usa para ejecutar comandos Python individuales y ver resultados al instante.\n\nEl Python Shell espera código Python. Al escribir código lo interpreta y muestra el resultado.\nAbre la terminal o el símbolo del sistema (cmd) y escribe:\n\n```shell\npython\n```\n\n\n\nEl intérprete interactivo de Python estará abierto y mostrará el prompt >>> para que escribas comandos Python. Escribe tu primer script y pulsa Enter.\nVeamos un ejemplo en el Shell interactivo.\n\n\n\nGenial: escribiste tu primer script en el Shell interactivo. ¿Cómo salir del Shell?\nPara salir escribe **exit()** y pulsa Enter.\n\n\n\nAhora sabes cómo abrir y cerrar el intérprete interactivo.\n\nSi escribes código inválido, Python mostrará un error. Probemos un error intencional:\n\n\n\nEl error indica Syntax Error: Invalid Syntax. Usar x para multiplicar no es válido en Python; el operador correcto es el asterisco (*). El error señala exactamente lo que hay que corregir.\n\nEl proceso de encontrar y corregir errores se llama depuración (debugging). Reemplazamos x por * y volvemos a ejecutar:\n\n\n\nEl error se corrige y el código produce el resultado esperado. Verás errores así a diario; aprender a depurar es esencial. Para depurar bien debes reconocer los tipos de errores: SyntaxError, IndexError, NameError, ModuleNotFoundError, KeyError, ImportError, AttributeError, TypeError, ValueError, ZeroDivisionError, etc. Los explicaremos más adelante.\n\nPractiquemos más en el Python Shell. Abre la terminal y escribe python.\n\n\n\nCon el Shell abierto hagamos operaciones matemáticas básicas: suma, resta, multiplicación, división, módulo y potencia.\n\nAntes de programar, hagamos algunos cálculos:\n\n- 2 + 3 = 5\n- 3 - 2 = 1\n- 3 * 2 = 6\n- 3 / 2 = 1.5\n- 3 ** 2 = 9\n\nEn Python también tenemos:\n\n- 3 % 2 = 1 => resto de la división\n- 3 // 2 = 1 => división entera (sin resto)\n\nConviértelo a código Python en el Shell. Primero escribe un comentario.\n\nUn comentario es texto ignorado por Python. Sirve para documentar y mejorar la legibilidad. En Python los comentarios empiezan con #.\nAsí se escribe un comentario en Python:\n\n```python\n# Los comentarios comienzan con una almohadilla\n# Este es un comentario en Python porque empieza con (#)\n```\n\n\n\nAntes de continuar, practica más: cierra el Shell con _exit()_ y vuelve a abrirlo; escribe texto en el Shell:\n\n\n\n### Instalar Visual Studio Code\n\nEl Python Shell está bien para probar fragmentos, pero para proyectos más grandes se usan editores de código. En este reto usaremos Visual Studio Code. VS Code es un editor de texto de código abierto muy popular. Recomiendo instalar Visual Studio Code, aunque puedes usar otro editor si lo prefieres.\n\n[](https://code.visualstudio.com/)\n\nSi ya tienes Visual Studio Code, veamos cómo usarlo.\nSi prefieres vídeos, mira el tutorial de instalación y configuración de VS Code para Python: https://www.youtube.com/watch?v=bn7Cx4z-vSo\n\n#### Cómo usar Visual Studio Code\n\nAbre Visual Studio Code haciendo doble clic en su icono. Aparecerá la interfaz. Interactúa con los iconos marcados en la imagen.\n\n\n\nCrea en el escritorio una carpeta llamada 30DaysOfPython. Ábrela con Visual Studio Code.\n\n\n\n\n\nDentro del proyecto verás accesos para crear archivos y carpetas. Yo creé el primer archivo helloworld.py; tú puedes hacer lo mismo.\n\n\n\nCuando termines de programar puedes cerrar el proyecto desde el editor:\n\n\n\n¡Enhorabuena! El entorno está listo. ¡Manos a la obra!\n\n## Fundamentos de Python\n\n### Sintaxis de Python\n\nLos scripts Python se pueden escribir en el Shell interactivo o en un editor. Los archivos Python usan la extensión .py.\n\n### Indentación en Python\n\nLa indentación son espacios en blanco en el código. En muchos lenguajes se usa para mejorar legibilidad; en Python se usa para definir bloques de código. En otros lenguajes se usan llaves. Un error común en Python es el error de indentación.\n\n\n\n### Comentarios\n\nLos comentarios son importantes para la legibilidad. Python no ejecuta el texto dentro de comentarios.\nCualquier texto que comience con # en Python es un comentario.\n\n# Ejemplo: comentario de una sola línea\n\n```shell\n# Este es el primer comentario\n# Este es el segundo comentario\n# Python se está apoderando del mundo\n```\n\n# Ejemplo: comentario multilínea (docstring)\n\nSe pueden usar comillas triples para comentarios multilínea si no se asignan a una variable.\n\n```shell\n\"\"\"Este es un comentario multilínea\nLos comentarios multilínea ocupan varias líneas.\nPython se está apoderando del mundo\n\"\"\"\n```\n\n### Tipos de datos\n\nPython tiene varios tipos de datos. Empecemos por los más comunes. Veremos otros tipos más en detalle en secciones posteriores. A continuación un resumen para familiarizarte.\n\n#### Números\n\n- Enteros: ... -3, -2, -1, 0, 1, 2, 3 ...\n- Flotantes: ... -3.5, -2.25, -1.0, 0.0, 1.1, 2.2, 3.5 ...\n- Complejos: 1 + j, 2 + 4j\n\n#### Cadenas\n\nTexto entre comillas simples o dobles; para multilínea se usan comillas triples.\n\n**Ejemplos:**\n\n```py\n'Asabeneh'\n'Finland'\n'Python'\n'I love teaching'\n'I hope you are enjoying the first day of 30DaysOfPython Challenge'\n```\n\n#### Booleanos\n\nTrue o False. Deben estar en mayúscula.\n\n**Ejemplo:**\n\n```python\nTrue # ¿La luz está encendida? Si sí, el valor es True\nFalse # ¿La luz está encendida? Si no, el valor es False\n```\n\n#### Listas\n\nLista ordenada que puede contener distintos tipos, similar a un array en JavaScript.\n\n**Ejemplos:**\n\n```py\n[0, 1, 2, 3, 4, 5] # todos números\n['Banana', 'Orange', 'Mango', 'Avocado'] # todos cadenas\n['Finland','Estonia', 'Sweden','Norway'] # todos cadenas (países)\n['Banana', 10, False, 9.81] # mezcla de tipos\n```\n\n#### Diccionarios\n\nColección no ordenada de pares clave:valor.\n\n**Ejemplo:**\n\n```py\n{\n'first_name':'Asabeneh',\n'last_name':'Yetayeh',\n'country':'Finland',\n'age':250,\n'is_married':True,\n'skills':['JS', 'React', 'Node', 'Python']\n}\n```\n\n#### Tuplas\n\nColección ordenada e inmutable.\n\n**Ejemplo:**\n\n```py\n('Asabeneh', 'Pawel', 'Brook', 'Abraham', 'Lidiya') # nombres\n```\n\n```py\n('Earth', 'Jupiter', 'Neptune', 'Mars', 'Venus', 'Saturn', 'Uranus', 'Mercury') # planetas\n```\n\n#### Conjuntos\n\nColección no ordenada que almacena elementos únicos (sin duplicados).\n\n**Ejemplos:**\n\n```py\n{2, 4, 3, 5}\n{3.14, 9.81, 2.7} # el orden en un set no importa\n```\n\nDetallaremos cada tipo de dato en secciones posteriores.\n\n### Comprobar tipos de datos\n\nUsa la función built-in **type** para comprobar el tipo de una variable. En la imagen puedes ver ejemplos:\n\n\n\n### Archivos Python\n\nAbre tu carpeta de proyecto 30DaysOfPython (créala si no existe). Dentro crea helloworld.py. Repite lo que hicimos en el Shell pero usando print() para ver resultados en consola desde un archivo.\n\nEn el intérprete se imprime sin print, pero en VS Code debes usar la función _print()_. Ejemplo de uso: _print('argumento1', 'argumento2')_.\n\n**Ejemplo:** archivo helloworld.py\n\n```py\n# Día 1 - Desafío 30DaysOfPython\n\nprint(2 + 3) # Suma (+)\nprint(3 - 1) # Resta (-)\nprint(2 * 3) # Multiplicación (*)\nprint(3 / 2) # División (/)\nprint(3 ** 2) # Potencia (**)\nprint(3 % 2) # Módulo (%)\nprint(3 // 2) # División entera (//)\n\n# Comprobar tipos de datos\nprint(type(10)) # entero\nprint(type(3.14)) # flotante\nprint(type(1 + 3j)) # complejo\nprint(type('Asabeneh')) # cadena\nprint(type([1, 2, 3])) # lista\nprint(type({'name':'Asabeneh'})) # diccionario\nprint(type({9.8, 3.14, 2.7})) # conjunto\nprint(type((9.8, 3.14, 2.7))) # tupla\n```\n\nPara ejecutar el archivo: en VS Code usa el botón verde o en la terminal escribe _python helloworld.py_.\n\n\n\nGenial. Completaste el Día 1. Practica con los ejercicios siguientes.\n\n## 💻 Ejercicios - Día 1\n\n### Ejercicios: Nivel 1\n\n1. Comprueba la versión de Python que usas.\n2. Abre el Python Shell e intenta con los operandos 3 y 4:\n - Suma (+)\n - Resta (-)\n - Multiplicación (*)\n - Módulo (%)\n - División (/)\n - Potencia (**)\n - División entera (//)\n3. En el Python Shell escribe las siguientes cadenas:\n - Tu nombre\n - Tu apellido\n - Tu país\n - Estoy disfrutando 30 días de Python\n4. Comprueba el tipo de los siguientes datos:\n - 10\n - 9.8\n - 3.14\n - 4 - 4j\n - ['Asabeneh', 'Python', 'Finland']\n - Tu nombre\n - Tu apellido\n - Tu país\n\n### Ejercicios: Nivel 2\n\n1. Crea en la carpeta 30DaysOfPython una carpeta llamada day_1. Dentro crea helloworld.py y repite las preguntas 1, 2, 3 y 4. Recuerda usar _print()_ en archivos. Navega a la carpeta donde guardaste el archivo y ejecútalo.\n\n### Ejercicios: Nivel 3\n\n1. Escribe ejemplos para distintos tipos de datos en Python: números (enteros, flotantes, complejos), cadenas, booleanos, listas, tuplas, conjuntos y diccionarios.\n2. Calcula la distancia euclídea entre (2, 3) y (10, 8): [Euclidean distance](https://en.wikipedia.org/wiki/Euclidean_distance#:~:text=In%20mathematics%2C%20the%20Euclidean%20distance,being%20called%20the%20Pythagorean%20distance).\n\n🎉 ¡Felicidades! 🎉\n\n[Ir al Día 2 >>](./02_variables_builtin_functions_sp.md)\n"
},
{
"path": "Spanish/readme.md",
"content": "# 🐍 30 Days Of Python\n\n|# Day | Topics |\n|------|:---------------------------------------------------------:|\n| 01 | [Introducción](./readme.md)|\n| 02 | [Variables, funciones integradas](./02_Day_Variables_builtin_functions/02_variables_builtin_functions.md)|\n| 03 | [Operadores](./03_Day_Operators/03_operators.md)|\n| 04 | [Strings](./04_Day_Strings/04_strings.md)|\n| 05 | [Lists](./05_Day_Lists/05_lists.md)|\n| 06 | [Tuplas](./06_Day_Tuples/06_tuples.md)|\n| 07 | [Sets](./07_Day_Sets/07_sets.md)|\n| 08 | [Diccionarios](./08_Day_Dictionaries/08_dictionaries.md)|\n| 09 | [Condicionales](./09_Day_Conditionals/09_conditionals.md)|\n| 10 | [Bucles](./10_Day_Loops/10_loops.md)|\n| 11 | [Funciones](./11_Day_Functions/11_functions.md)|\n| 12 | [Módulos](./12_Day_Modules/12_modules.md)|\n| 13 | [Lista de comprensión](./13_Day_List_comprehension/13_list_comprehension.md)|\n| 14 | [Funciones de orden superior](./14_Day_Higher_order_functions/14_higher_order_functions.md)|\n| 15 | [Errores de tipo Python](./15_Day_Python_type_errors/15_python_type_errors.md)|\n| 16 | [Fecha y hora de Python](./16_Day_Python_date_time/16_python_datetime.md) |\n| 17 | [Manejo de excepciones](./17_Day_Exception_handling/17_exception_handling.md)|\n| 18 | [Expresiones regulares](./18_Day_Regular_expressions/18_regular_expressions.md)|\n| 19 | [Manejo de archivos](./19_Day_File_handling/19_file_handling.md)|\n| 20 | [Administrador de paquetes de Python](./20_Day_Python_package_manager/20_python_package_manager.md)|\n| 21 | [Clases y Objetos](./21_Day_Classes_and_objects/21_classes_and_objects.md)|\n| 22 | [Raspado web](./22_Day_Web_scraping/22_web_scraping.md)|\n| 23 | [Ambiente virtual](./23_Day_Virtual_environment/23_virtual_environment.md)|\n| 24 | [Estadísticas](./24_Day_Statistics/24_statistics.md)|\n| 25 | [Pandas](./25_Day_Pandas/25_pandas.md)|\n| 26 | [Python web](./26_Day_Python_web/26_python_web.md)|\n| 27 | [Python con MongoDB](./27_Day_Python_with_mongodb/27_python_with_mongodb.md)|\n| 28 | [API](./28_Day_API/28_API.md)|\n| 29 | [Building API](./29_Day_Building_API/29_building_API.md)|\n| 30 | [Conclusiones](./30_Day_Conclusions/30_conclusions.md)|\n\n🧡🧡🧡 FELIZ CODIGO 🧡🧡🧡\n\n
\nSupport the author to create more educational materials \n\n
\n\n[Dia 2 >>](./02_Day_Variables_builtin_functions/02_variables_builtin_functions.md)\n\n\n\n- [🐍 30 Days Of Python](#-30-days-of-python)\n- [📘 Day 1](#-day-1)\n - [Welcome](#welcome)\n - [Introduction](#introduction)\n - [Why Python ?](#why-python-)\n - [Environment Setup](#environment-setup)\n - [Installing Python](#installing-python)\n - [Python Shell](#python-shell)\n - [Installing Visual Studio Code](#installing-visual-studio-code)\n - [How to use visual studio code](#how-to-use-visual-studio-code)\n - [Basic Python](#basic-python)\n - [Python Syntax](#python-syntax)\n - [Python Indentation](#python-indentation)\n - [Comments](#comments)\n - [Data types](#data-types)\n - [Number](#number)\n - [String](#string)\n - [Booleans](#booleans)\n - [List](#list)\n - [Dictionary](#dictionary)\n - [Tuple](#tuple)\n - [Set](#set)\n - [Checking Data types](#checking-data-types)\n - [Python File](#python-file)\n - [💻 Exercises - Day 1](#-exercises---day-1)\n - [Exercise: Level 1](#exercise-level-1)\n - [Exercise: Level 2](#exercise-level-2)\n - [Exercise: Level 3](#exercise-level-3)\n\n# 📘 Day 1\n\n## Welcome\n\n**Congratulations** for deciding to participate in a _30 days of Python_ programming challenge . In this challenge you will learn everything you need to be a python programmer and the whole concept of programming. In the end of the challenge you will get a _30DaysOfPython_ programming challenge certificate.\n\nIf you would like to actively engage in the challenge, you may join the [30DaysOfPython challenge](https://t.me/ThirtyDaysOfPython) telegram group. \n\n## Introduction\n\nPython is a high-level programming language for general-purpose programming. It is an open source, interpreted, objected-oriented programming language. Python was created by a Dutch programmer, Guido van Rossum. The name of Python programming language was derived from a British sketch comedy series, _Monty Python's Flying Circus_. The first version was released on February 20, 1991. This 30 days of Python challenge will help you learn the latest version of Python, Python 3 step by step. The topics are broken down into 30 days, where each day contains several topics with easy-to-understand explanations, real-world examples, many hands on exercises and projects.\n\nThis challenge is designed for beginners and professionals who want to learn python programming language. It may take 30 to 100 days to complete the challenge, people who actively participate on the telegram group have a high probability of completing the challenge.\n\nThis challenge is easy to read, written in conversational English, engaging, motivating and at the same time, it is very demanding. You need to allocate much time to finish this challenge. If you are a visual learner, you may get the video lesson on Washera YouTube channel. You may start from [Python for Absolute Beginners video](https://youtu.be/OCCWZheOesI). Subscribe the channel, comment and ask questions on YouTube vidoes and be proactive, the author will eventually notice you.\n\nThe author likes to hear your opinion about the challenge, share the author by expressing your thoughts about the 30DaysOfPython challenge. You can leave your testimonial on this [link](https://testimonial-vdzd.onrender.com/)\n\n## Why Python ?\n\nIt is a programming language which is very close to human language and because of that it is easy to learn and use.\nPython is used by various industries and companies (including Google). It has been used to develop web applications, desktop applications, system adminstration, and machine learning libraries. Python is highly embraced language in the data science and machine learning community. I hope this is enough to convince you to start learning Python. Python is eating the world and you are killing it before it eats you.\n\n## Environment Setup\n\n### Installing Python\n\nTo run a python script you need to install python. Let's [download](https://www.python.org/) python.\nIf your are a windows user. Click the button encircled in red.\n\n[](https://www.python.org/)\n\nIf you are a macOS user. Click the button encircled in red.\n\n[](https://www.python.org/)\n\nTo check if python is installed write the following command on your device terminal.\n\n```shell\npython --version\n```\n\n\n\nAs you can see from the terminal, I am using _Python 3.7.5_ version at the moment. Your version of Python might be different from mine by but it should be 3.6 or above. If you mange to see the python version, well done. Python has been installed on your machine. Continue to the next section.\n\n### Python Shell\n\nPython is an interpreted scripting language, so it does not need to be compiled. It means it executes the code line by line. Python comes with a _Python Shell (Python Interactive Shell)_. It is used to execute a single python command and get the result.\n\nPython Shell waits for the Python code from the user. When you enter the code, it interprets the code and shows the result in the next line.\nOpen your terminal or command prompt(cmd) and write:\n\n```shell\npython\n```\n\n\n\nThe Python interactive shell is opened and it is waiting for you to write Python code(Python script). You will write your Python script next to this symbol >>> and then click Enter.\nLet us write our very first script on the Python scripting shell.\n\n\n\nWell done, you wrote your first Python script on Python interactive shell. How do we close the Python interactive shell ?\nTo close the shell, next to this symbol >> write **exit()** command and press Enter.\n\n\n\nNow, you know how to open the Python interactive shell and how to exit from it.\n\nPython will give you results if you write scripts that Python understands, if not it returns errors. Let's make a deliberate mistake and see what Python will return.\n\n\n\nAs you can see from the returned error, Python is so clever that it knows the mistake we made and which was _Syntax Error: invalid syntax_. Using x as multiplication in Python is a syntax error because (x) is not a valid syntax in Python. Instead of (**x**) we use asterisk (*) for multiplication. The returned error clearly shows what to fix.\n\nThe process of identifying and removing errors from a program is called _debugging_. Let us debug it by putting * in place of **x**.\n\n\n\nOur bug was fixed, the code ran and we got a result we were expecting. As a programmer you will see such kind of errors on daily basis. It is good to know how to debug. To be good at debugging you should understand what kind of errors you are facing. Some of the Python errors you may encounter are _SyntaxError_, _IndexError_, _NameError_, _ModuleNotFoundError_, _KeyError_, _ImportError_, _AttributeError_, _TypeError_, _ValueError_, _ZeroDivisionError_ etc. We will see more about different Python **_error types_** in later sections.\n\nLet us practice more how to use Python interactive shell. Go to your terminal or command prompt and write the word **python**.\n\n\n\nThe Python interactive shell is opened. Let us do some basic mathematical operations (addition, subtraction, multiplication, division, modulus, exponential).\n\nLet us do some maths first before we write any Python code:\n\n- 2 + 3 is 5\n- 3 - 2 is 1\n- 3 \\* 2 is 6\n- 3 / 2 is 1.5\n- 3 ** 2 is the same as 3 * 3\n\nIn python we have the following additional operations:\n\n- 3 % 2 = 1 => which means finding the remainder\n- 3 // 2 = 1 => which means removing the remainder\n\nLet us change the above mathematical expressions to Python code. The Python shell has been opened and let us write a comment at the very beginning of the shell.\n\nA _comment_ is a part of the code which is not executed by python. So we can leave some text in our code to make our code more readable. Python does not run the comment part. A comment in python starts with hash(#) symbol.\nThis is how you write a comment in python\n\n```shell\n # comment starts with hash\n # this is a python comment, because it starts with a (#) symbol\n```\n\n\n\nBefore we move on to the next section, let us practice more on the Python interactive shell. Close the opened shell by writing _exit()_ on the shell and open it again and let us practice how to write text on the Python shell.\n\n\n\n### Installing Visual Studio Code\n\nThe Python interactive shell is good to try and test small script codes but it will not be for a big project. In real work environment, developers use different code editors to write codes. In this 30 days of Python programming challenge we will use visual studio code. Visual studio code is a very popular open source text editor. I am a fan of vscode and I would recommend to [download](https://code.visualstudio.com/) visual studio code, but if you are in favor of other editors, feel free to follow with what you have.\n\n[](https://code.visualstudio.com/)\n\nIf you installed visual studio code, let us see how to use it.\nIf you prefer a video, you can follow this Visual Studio Code for Python [Video tutorial](https://www.youtube.com/watch?v=bn7Cx4z-vSo)\n\n#### How to use visual studio code\n\nOpen the visual studio code by double clicking the visual studio icon. When you open it you will get this kind of interface. Try to interact with the labeled icons.\n\n\n\nCreate a folder named 30DaysOfPython on your desktop. Then open it using visual studio code.\n\n\n\n\n\nAfter opening it you will see shortcuts for creating files and folders inside of 30DaysOfPython project's directory. As you can see below, I have created the very first file, helloworld.py. You can do the same.\n\n\n\nAfter a long day of coding, you want to close your code editor, right? This is how you will close the opened project.\n\n\n\nCongratulations, you have finished setting up the development environment. Let us start coding.\n\n## Basic Python\n\n### Python Syntax\n\nA Python script can be written in Python interactive shell or in the code editor. A Python file has an extension .py.\n\n### Python Indentation\n\nAn indentation is a white space in a text. Indentation in many languages is used to increase code readability, however Python uses indentation to create block of codes. In other programming languages curly brackets are used to create blocks of codes instead of indentation. One of the common bugs when writing python code is wrong indentation.\n\n\n\n### Comments\n\nComments are very important to make the code more readable and to leave remarks in our code. Python does not run comment parts of our code.\nAny text starting with hash(#) in Python is a comment.\n\n**Example: Single Line Comment**\n\n```shell\n # This is the first comment\n # This is the second comment\n # Python is eating the world\n```\n\n**Example: Multiline Comment**\n\nTriple quote can be used for multiline comment if it is not assigned to a variable\n\n```shell\n\"\"\"This is multiline comment\nmultiline comment takes multiple lines.\npython is eating the world\n\"\"\"\n```\n\n### Data types\n\nIn Python there are several types of data types. Let us get started with the most common ones. Different data types will be covered in detail in other sections. For the time being, let us just go through the different data types and get familiar with them. You do not have to have a clear understanding now.\n\n#### Number\n\n- Integer: Integer(negative, zero and positive) numbers\n Example:\n ... -3, -2, -1, 0, 1, 2, 3 ...\n- Float: Decimal number\n Example\n ... -3.5, -2.25, -1.0, 0.0, 1.1, 2.2, 3.5 ...\n- Complex\n Example\n 1 + j, 2 + 4j\n\n#### String\n\nA collection of one or more characters under a single or double quote. If a string is more than one sentence then we use a triple quote.\n\n**Example:**\n\n```py\n'Asabeneh'\n'Finland'\n'Python'\n'I love teaching'\n'I hope you are enjoying the first day of 30DaysOfPython Challenge'\n```\n\n#### Booleans\n\nA boolean data type is either a True or False value. T and F should be always uppercase.\n\n**Example:**\n\n```python\n True # Is the light on? If it is on, then the value is True\n False # Is the light on? If it is off, then the value is False\n```\n\n#### List\n\nPython list is an ordered collection which allows to store different data type items. A list is similar to an array in JavaScript.\n\n**Example:**\n\n```py\n[0, 1, 2, 3, 4, 5] # all are the same data types - a list of numbers\n['Banana', 'Orange', 'Mango', 'Avocado'] # all the same data types - a list of strings (fruits)\n['Finland','Estonia', 'Sweden','Norway'] # all the same data types - a list of strings (countries)\n['Banana', 10, False, 9.81] # different data types in the list - string, integer, boolean and float\n```\n\n#### Dictionary\n\nA Python dictionary object is an unordered collection of data in a key value pair format.\n\n**Example:**\n\n```py\n{\n'first_name':'Asabeneh',\n'last_name':'Yetayeh',\n'country':'Finland', \n'age':250, \n'is_married':True,\n'skills':['JS', 'React', 'Node', 'Python']\n}\n```\n\n#### Tuple\n\nA tuple is an ordered collection of different data types like list but tuples can not be modified once they are created. They are immutable.\n\n**Example:**\n\n```py\n('Asabeneh', 'Pawel', 'Brook', 'Abraham', 'Lidiya') # Names\n```\n\n```py\n('Earth', 'Jupiter', 'Neptune', 'Mars', 'Venus', 'Saturn', 'Uranus', 'Mercury') # planets\n```\n\n#### Set\n\nA set is a collection of data types similar to list and tuple. Unlike list and tuple, set is not an ordered collection of items. Like in Mathematics, set in Python stores only unique items.\n\nIn later sections, we will go in detail about each and every Python data type.\n\n**Example:**\n\n```py\n{2, 4, 3, 5}\n{3.14, 9.81, 2.7} # order is not important in set\n```\n\n### Checking Data types\n\nTo check the data type of certain data/variable we use the **type** function. In the following terminal you will see different python data types:\n\n\n\n### Python File\n\nFirst open your project folder, 30DaysOfPython. If you don't have this folder, create a folder name called 30DaysOfPython. Inside this folder, create a file called helloworld.py. Now, let's do what we did on python interactive shell using visual studio code.\n\nThe Python interactive shell was printing without using **print** but on visual studio code to see our result we should use a built in function _print(). The _print()_ built-in function takes one or more arguments as follows _print('arument1', 'argument2', 'argument3')_. See the examples below.\n\n**Example:**\n\nThe file name is helloworld.py\n\n```py\n# Day 1 - 30DaysOfPython Challenge\n\nprint(2 + 3) # addition(+)\nprint(3 - 1) # subtraction(-)\nprint(2 * 3) # multiplication(*)\nprint(3 / 2) # division(/)\nprint(3 ** 2) # exponential(**)\nprint(3 % 2) # modulus(%)\nprint(3 // 2) # Floor division operator(//)\n\n# Checking data types\nprint(type(10)) # Int\nprint(type(3.14)) # Float\nprint(type(1 + 3j)) # Complex number\nprint(type('Asabeneh')) # String\nprint(type([1, 2, 3])) # List\nprint(type({'name':'Asabeneh'})) # Dictionary\nprint(type({9.8, 3.14, 2.7})) # Set\nprint(type((9.8, 3.14, 2.7))) # Tuple\n```\n\nTo run the python file check the image below. You can run the python file either by running the green button on Visual Studio Code or by typing _python helloworld.py_ in the terminal .\n\n\n\n🌕 You are amazing. You have just completed day 1 challenge and you are on your way to greatness. Now do some exercises for your brain and muscles.\n\n## 💻 Exercises - Day 1\n\n### Exercise: Level 1\n\n1. Check the python version you are using\n2. Open the python interactive shell and do the following operations. The operands are 3 and 4.\n - addition(+)\n - subtraction(-)\n - multiplication(\\*)\n - modulus(%)\n - division(/)\n - exponential(\\*\\*)\n - floor division operator(//)\n3. Write strings on the python interactive shell. The strings are the following:\n - Your name\n - Your family name\n - Your country\n - I am enjoying 30 days of python\n4. Check the data types of the following data:\n - 10\n - 9.8\n - 3.14\n - 4 - 4j\n - ['Asabeneh', 'Python', 'Finland']\n - Your name\n - Your family name\n - Your country\n\n### Exercise: Level 2\n\n1. Create a folder named day_1 inside 30DaysOfPython folder. Inside day_1 folder, create a python file helloworld.py and repeat questions 1, 2, 3 and 4. Remember to use _print()_ when you are working on a python file. Navigate to the directory where you have saved your file, and run it.\n\n### Exercise: Level 3\n\n1. Write an example for different Python data types such as Number(Integer, Float, Complex), String, Boolean, List, Tuple, Set and Dictionary.\n2. Find an [Euclidian distance](https://en.wikipedia.org/wiki/Euclidean_distance#:~:text=In%20mathematics%2C%20the%20Euclidean%20distance,being%20called%20the%20Pythagorean%20distance.) between (2, 3) and (10, 8)\n\n🎉 CONGRATULATIONS ! 🎉\n\n[Day 2 >>](./02_Day_Variables_builtin_functions/02_variables_builtin_functions.md)\n"
},
{
"path": "Ukrainian/readme.md",
"content": "# 🐍 30 днів з Python \n\n| № дня | Теми |\n|-------|:-------------------------------------------------------------------------------------------------------:|\n| 01 | [Вступ](./readme.md) |\n| 02 | [Variables, Built-in Functions](./02_Day_Variables_builtin_functions/02_variables_builtin_functions.md) |\n| 03 | [Operators](../03_Day_Operators/03_operators.md) |\n| 04 | [Strings](../04_Day_Strings/04_strings.md) |\n| 05 | [Lists](../05_Day_Lists/05_lists.md) |\n| 06 | [Tuples](../06_Day_Tuples/06_tuples.md) |\n| 07 | [Sets](../07_Day_Sets/07_sets.md) |\n| 08 | [Dictionaries](../08_Day_Dictionaries/08_dictionaries.md) |\n| 09 | [Conditionals](../09_Day_Conditionals/09_conditionals.md) |\n| 10 | [Loops](../10_Day_Loops/10_loops.md) |\n| 11 | [Functions](../11_Day_Functions/11_functions.md) |\n| 12 | [Modules](../12_Day_Modules/12_modules.md) |\n| 13 | [List Comprehension](../13_Day_List_comprehension/13_list_comprehension.md) |\n| 14 | [Higher Order Functions](../14_Day_Higher_order_functions/14_higher_order_functions.md) | \n| 15 | [Python Type Errors](../15_Day_Python_type_errors/15_python_type_errors.md) | \n| 16 | [Python Date time](../16_Day_Python_date_time/16_python_datetime.md) | \n| 17 | [Exception Handling](../17_Day_Exception_handling/17_exception_handling.md) | \n| 18 | [Regular Expressions](../18_Day_Regular_expressions/18_regular_expressions.md) | \n| 19 | [File Handling](../19_Day_File_handling/19_file_handling.md) |\n| 20 | [Python Package Manager](../20_Day_Python_package_manager/20_python_package_manager.md) |\n| 21 | [Classes and Objects](../21_Day_Classes_and_objects/21_classes_and_objects.md) |\n| 22 | [Web Scraping](../22_Day_Web_scraping/22_web_scraping.md) |\n| 23 | [Virtual Environment](../23_Day_Virtual_environment/23_virtual_environment.md) |\n| 24 | [Statistics](../24_Day_Statistics/24_statistics.md) |\n| 25 | [Pandas](../25_Day_Pandas/25_pandas.md) |\n| 26 | [Python web](../26_Day_Python_web/26_python_web.md) |\n| 27 | [Python with MongoDB](../27_Day_Python_with_mongodb/27_python_with_mongodb.md) |\n| 28 | [API](../28_Day_API/28_API.md) |\n| 29 | [Building API](../29_Day_Building_API/29_building_API.md) |\n| 30 | [Conclusions](../30_Day_Conclusions/30_conclusions.md) |\n\n🧡🧡🧡 ЩАСЛИВОГО ПРОГРАМУВАННЯ 🧡🧡🧡\n\n
\nПідтримайте автора, щобм він створював більше навчальних матеріалів \n\n
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\n \n \n ![\"Twitter](\"https://img.shields.io/twitter/follow/asabeneh?style=social\")
\n \n\nAuthor:\nAsabeneh Yetayeh
\n\n \n\n[<< Day 1](../readme.md) | [Day 3 >>](../03_Day_Operators/03_operators.md)\n\n\n\n- [📘 Day 2](#-day-2)\n - [내장 함수](#내장-함수)\n - [변수](#변수)\n - [한 줄로 여러개의 변수 선언](#한-줄로-여러개의-변수-선언)\n - [자료형](#자료형)\n - [자료형 확인 및 형변환](#자료형-확인-및-형변환)\n - [숫자](#숫자)\n - [💻 Exercises - Day 2](#-exercises---day-2)\n - [Exercises: Level 1](#exercises-level-1)\n - [Exercises: Level 2](#exercises-level-2)\n\n# 📘 Day 2\n\n## 내장 함수\n\n파이썬에는 수많은 내장 함수가 있습니다. 내장 함수는 전역에서 사용 가능하고 그건 importing 이나 configuring없이 내장 함수를 사용 가능하다는 뜻입니다. 다음은 가장 자주 사용되는 파이썬 내장함수들 중 몇가지입니다: _print()_, _len()_, _type()_, _int()_, _float()_, _str()_, _input()_, _list()_, _dict()_, _min()_, _max()_, _sum()_, _sorted()_, _open()_, _file()_, _help()_, and _dir()_. 밑의 표에서 [파이썬 공식문서](https://docs.python.org/3.9/library/functions.html) 에 쓰여진 파이썬 내장 함수의 전체 목록을 볼 수 있습니다.\n\n\n\n파이썬 쉘을 열고 가장 자주 사용되는 내장 함수를 사용해봅시다.\n\n\n\n다른 내장 함수를 사용해 더 연습해봅시다.\n\n\n\n위의 터미널에서 볼 수 있듯이, 파이썬에는 reserved word가 있습니다. reserved word는 변수나 함수를 선언할때 사용되지 않습니다. 변수에 관해서는 다음 장에서 다룰것입니다.\n\n이제 당신은 내장 함수에 익숙해졌을 것이라 믿습니다. 한번 더 내장 함수의 연습을 하고 다음 장으로 넘어갑시다.\n\n\n## 변수\n\n변수는 컴퓨터 메모리에 정보를 저장합니다. Mnemonic 변수는 많은 프로그래밍 언어에서 사용하도록 권장됩니다. Mnemonic 변수는 쉽게 기억하고 연관지을 수 있는 변수 이름입니다. 한 변수는 정보가 저장되어있는 메모리 주소를 참조합니다.\n변수 이름을 지정할 때는 시작 부분의 숫자, 특수 문자, 하이픈을 사용할 수 없습니다. 변수는 짧은 이름(예: x, y, z)을 가질 수 있지만 더 변수에 대한 설명을 담은 이름(이름, 성, 나이, 국가)을 사용하는 것을 추천합니다.\n\n파이썬 변수 이름 규칙\n\n- 변수 이름은 문자 또는 밑줄 문자로 시작해야 합니다\n- 변수 이름은 숫자로 시작할 수 없습니다 \n- 변수 이름에는 알파벳과 숫자와 밑줄(A-z, 0-9 및 \\_)만 사용할 수 있습니다 \n- 변수 이름은 대소문자를 구분합니다(firstname, Firstname, FirstName, FIRSTNAME은 서로 다른 변수)\n\n사용가능한 변수 이름들을 살펴봅시다\n\n```shell\nfirstname\nlastname\nage\ncountry\ncity\nfirst_name\nlast_name\ncapital_city\n_if # reserved word를 변수 이름으로 사용하고 싶은 경우\nyear_2021\nyear2021\ncurrent_year_2021\nbirth_year\nnum1\nnum2\n```\n\n사용할 수 없는 변수 이름들\n\n```shell\nfirst-name\nfirst@name\nfirst$name\nnum-1\n1num\n```\n\n우리는 많은 파이썬 개발자들이 채택한 표준 파이썬 변수 명명 방식을 사용할 것입니다. 파이썬 개발자들은 스네이크 케이스(snake_case) 변수 명명 규칙을 사용합니다. 우리는 두 개 이상의 단어를 포함하는 변수에 대해 각 단어 뒤에 밑줄 문자를 사용합니다(예: first_name, last_name, engine_rotation_speed). 아래 예제는 변수의 표준 명명 예제이며, 변수 이름이 둘 이상의 단어일 경우 밑줄이 필요합니다.\n\n변수에 특정 데이터 유형을 할당할 때 이를 변수 선언이라고 합니다. 예를 들어 아래 예제에서 내 이름은 first_name 변수에 할당됩니다. 등호 기호는 할당 연산자입니다. 할당은 변수에 데이터를 저장하는 것을 의미합니다. 파이썬에서 등호 기호는 수학에서의 등호가 아닙니다.\n\n_Example:_\n\n```py\n# Variables in Python\nfirst_name = 'Asabeneh'\nlast_name = 'Yetayeh'\ncountry = 'Finland'\ncity = 'Helsinki'\nage = 250\nis_married = True\nskills = ['HTML', 'CSS', 'JS', 'React', 'Python']\nperson_info = {\n 'firstname':'Asabeneh',\n 'lastname':'Yetayeh',\n 'country':'Finland',\n 'city':'Helsinki'\n }\n```\n\n내장 함수인 _print()_ 와 _len()_ 을 사용해봅시다. Print 함수는 인자의 수에 제한이 없습니다. 인자는 함수 괄호 안에 넣어 전달할 수 있는 값입니다. 아래 예제를 봅시다.\n\n**Example:**\n\n```py\nprint('Hello, World!') # Hello, World! 라는 글이 하나의 인자입니다\nprint('Hello',',', 'World','!') # 여러개의 인자를 받을 수 있습니다, 네개의 인자가 넘겨졌습니다 \nprint(len('Hello, World!')) # 하나의 인자만을 받습니다\n```\n\n위에서 정의된 변수들을 찍어보고 길이를 찾아봅시다:\n\n**Example:**\n\n```py\n# 변수에 저장된 값 찍기\n\nprint('First name:', first_name)\nprint('First name length:', len(first_name))\nprint('Last name: ', last_name)\nprint('Last name length: ', len(last_name))\nprint('Country: ', country)\nprint('City: ', city)\nprint('Age: ', age)\nprint('Married: ', is_married)\nprint('Skills: ', skills)\nprint('Person information: ', person_info)\n```\n\n### 한 줄로 여러개의 변수 선언\n\n하나의 줄에서 여러개의 변수를 선언할 수도 있습니다:\n\n**Example:**\n\n```py\nfirst_name, last_name, country, age, is_married = 'Asabeneh', 'Yetayeh', 'Helsink', 250, True\n\nprint(first_name, last_name, country, age, is_married)\nprint('First name:', first_name)\nprint('Last name: ', last_name)\nprint('Country: ', country)\nprint('Age: ', age)\nprint('Married: ', is_married)\n```\n\n내장 함수 _input()_ 을 사용해 사용자의 입력 받기. 사용자로부터 받은 정보를 first_name과 age 변수에 할당해봅시다.\n**Example:**\n\n```py\nfirst_name = input('What is your name: ')\nage = input('How old are you? ')\n\nprint(first_name)\nprint(age)\n```\n\n## 자료형\n\n파이썬에는 몇 가지 자료형이 있습니다. 자료형을 식별하기 위해 내장 함수 _type()_ 을 사용합니다. 서로 다른 자료형을 잘 이해하는 데 집중해 주시기를 부탁드립니다. 프로그래밍에서 모든것은 자료형과 관련이 있습니다. 처음에 자료형을 소개했지만 모든 주제가 자료형과 관련이 있기 때문에 다시 나옵니다. 자료형에 대해서는 각 섹션에서 자세히 설명하겠습니다.\n\n## 자료형 확인 및 형변환\n\n- 자료형 확인: 특정 정보/변수의 자료형을 확인하기위해 우리는 _type()_ 을 사용합니다\n **Example:**\n\n```py\n# 다양한 파이썬 자료형\n# 다양한 자료형의 변수들을 선언해 봅시다.\n\nfirst_name = 'Asabeneh' # str\nlast_name = 'Yetayeh' # str\ncountry = 'Finland' # str\ncity= 'Helsinki' # str\nage = 250 # int, 제 실제 나이가 아닙니다, 걱정마세요\n\n# Printing out types\nprint(type('Asabeneh')) # str\nprint(type(first_name)) # str\nprint(type(10)) # int\nprint(type(3.14)) # float\nprint(type(1 + 1j)) # complex\nprint(type(True)) # bool\nprint(type([1, 2, 3, 4])) # list\nprint(type({'name':'Asabeneh','age':250, 'is_married':250})) # dict\nprint(type((1,2))) # tuple\nprint(type(zip([1,2],[3,4]))) # set\n```\n\n- 형변환: 하나의 자료형을 다른 자료형으로 변환합니다. _int()_, _float()_, _str()_, _list_, _set_ 를 사용합니다.\n 산술 연산을 수행할 때 문자열 숫자들을 먼저 int 나 float로 변환해야 합니다. 그렇지 않으면 오류가 반환됩니다. 만약 숫자를 문자열과 결합한다면, 그 숫자는 먼저 문자열로 변환되어야 합니다. 결합에 대해서는 String 섹션에서 설명하겠습니다.\n\n **Example:**\n\n```py\n# int to float\nnum_int = 10\nprint('num_int',num_int) # 10\nnum_float = float(num_int)\nprint('num_float:', num_float) # 10.0\n\n# float to int\ngravity = 9.81\nprint(int(gravity)) # 9\n\n# int to str\nnum_int = 10\nprint(num_int) # 10\nnum_str = str(num_int)\nprint(num_str) # '10'\n\n# str to int or float\nnum_str = '10.6'\nprint('num_int', int(num_str)) # 10\nprint('num_float', float(num_str)) # 10.6\n\n# str to list\nfirst_name = 'Asabeneh'\nprint(first_name) # 'Asabeneh'\nfirst_name_to_list = list(first_name)\nprint(first_name_to_list) # ['A', 's', 'a', 'b', 'e', 'n', 'e', 'h']\n```\n\n## 숫자\n\n파이썬의 숫자 자료형:\n\n1. Integers: 정수(음수, 0 , 양수) \n 예:\n ... -3, -2, -1, 0, 1, 2, 3 ...\n\n2. 부동 소수점 숫자(10진수)\n 예:\n ... -3.5, -2.25, -1.0, 0.0, 1.1, 2.2, 3.5 ...\n\n3. 복소수\n 예:\n 1 + j, 2 + 4j, 1 - 1j\n\n🌕 당신은 정말 멋집니다. 여러분은 이제 막 2일차 도전을 마쳤고 위대함으로 가는 길에 두 걸음 앞서 있습니다. 이제 여러분의 뇌와 근육을 위한 운동을 하세요.\n\n## 💻 Exercises - Day 2\n\n### Exercises: Level 1\n\n1. 30DaysOfPython 내에 day_2라는 폴더를 생성하세요. 그 폴더 내에 variables.py 라는 파일을 생성하세요.\n2. 'Day 2: 30 Days of python programming'이라는 파이썬 주석을 작성합니다.\n3. first name 변수를 선언하고 변수에 값을 할당합니다.\n4. last name 변수를 선언하고 변수에 값을 할당합니다.\n5. full name 변수를 선언하고 변수에 값을 할당합니다.\n6. country 변수를 선언하고 값을 할당합니다.\n7. city 변수를 선언하고 값을 할당합니다.\n8. age 변수를 선언하고 값을 할당합니다.\n9. year 변수를 선언하고 값을 할당합니다.\n10. is_married 변수를 선언하고 값을 할당합니다.\n11. is_true 변수를 선언하고 값을 할당합니다.\n12. is_light_on 변수를 선언하고 값을 할당합니다.\n13. 한 줄에 여러개의 변수를 선언합니다.\n\n### Exercises: Level 2\n\n1. Check the data type of all your variables using type() built-in function\n1. Using the _len()_ built-in function, find the length of your first name\n1. Compare the length of your first name and your last name\n1. Declare 5 as num_one and 4 as num_two\n 1. Add num_one and num_two and assign the value to a variable total\n 2. Subtract num_two from num_one and assign the value to a variable diff\n 3. Multiply num_two and num_one and assign the value to a variable product\n 4. Divide num_one by num_two and assign the value to a variable division\n 5. Use modulus division to find num_two divided by num_one and assign the value to a variable remainder\n 6. Calculate num_one to the power of num_two and assign the value to a variable exp\n 7. Find floor division of num_one by num_two and assign the value to a variable floor_division\n1. The radius of a circle is 30 meters.\n 1. Calculate the area of a circle and assign the value to a variable name of _area_of_circle_\n 2. Calculate the circumference of a circle and assign the value to a variable name of _circum_of_circle_\n 3. Take radius as user input and calculate the area.\n1. Use the built-in input function to get first name, last name, country and age from a user and store the value to their corresponding variable names\n1. Run help('keywords') in Python shell or in your file to check for the Python reserved words or keywords\n\n1. type() 내장 함수를 사용하여 모든 변수의 자료형을 확인합니다.\n1. _len()_ 내장 함수를 사용하여 당신의 first name 의 길이를 찾습니다.\n1. 당신의 first name 과 last name 의 길이를 비교합니다.\n1. 5를 num_1로, 4를 num_2로 선언합니다.\n 1. num_one과 num_two를 더하고 그 값을 변수 total 에 할당합니다.\n 2. num_1에서 num_2를 빼고 그 값을 변수 diff 에 할당합니다.\n 3. num_two와 num_one을 곱하여 그 값을 변수 product 에 할당합니다.\n 4. num_one을 num_two로 나누고 그 값을 변수 division 에 할당합니다.\n 5. 나머지 연산을 사용하여 num_two를 num_one으로 나눈 값을 찾고 변수 remainder 에 할당합니다.\n 6. num_one을 num_two의 거듭제곱으로 계산하고 그 값을 변수 exp 에 할당합니다.\n 7. num_one을 num_two로 나누고 소숫값은 버린 정수 값을 구하고 변수 floor_division 에 값을 할당합니다.\n1. 원의 반지름은 30미터입니다.\n 1. 원의 면적을 계산하여 _area_of_circle_ 이라는 이름의 변수에 값을 할당합니다.\n 2. 원의 둘레를 계산하여 _circum_of_circum_ 이라는 이름의 변수에 값을 할당합니다.\n 3. 반경을 사용자 입력으로 받아서 면적을 계산합니다.\n1. 내장 함수 input을 사용하여 사용자로부터 이름, 성, 국가 및 나이를 얻고 해당 변수 이름에 값을 저장합니다.\n1. Python 셸 또는 파일에서 help('keywords')을 실행하여 파이썬의 reserved words 또는 키워드를 확인합니다.\n\n🎉 축하합니다 ! 🎉\n\n[<< Day 1](../readme.md) | [Day 3 >>](../03_Day_Operators/03_operators.md)\n"
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"path": "Korean/04_strings_ko.md",
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\n\n \n\n\n[Day 2 >>](../02_Day_Variables_builtin_functions/02_variables_builtin_functions.md)\n\n\n\n- [🐍 30 Days Of Python](#-30-days-of-python)\n- [📘 Day 1](#-day-1)\n - [환영합니다](#환영합니다)\n - [소개](#소개)\n - [왜 Python이느냐?](#왜-python이느냐?)\n - [환경 설정](#환경-설정)\n - [Python 설치](#python-설치)\n - [Python 셸](#python-셸)\n - [Visual Studio Code 설치](#visual-studio-code-설치)\n - [visual studio code를 사용하기](#visual-studio-code를-사용하기)\n - [Python 기본](#python-기본)\n - [Python 구문](#python-구문)\n - [Python 들여쓰기](#python-들여쓰기)\n - [주석](#주석)\n - [데이터 타입](#데이터-타입)\n - [Number](#number)\n - [String](#string)\n - [Booleans](#booleans)\n - [List](#list)\n - [Dictionary](#dictionary)\n - [Tuple](#tuple)\n - [Set](#set)\n - [데이터 타입 체크](#데이터-타입-체크)\n - [Python 파일](#python-파일)\n - [💻 Exercises - Day 1](#-exercises---day-1)\n - [Exercise: Level 1](#exercise-level-1)\n - [Exercise: Level 2](#exercise-level-2)\n - [Exercise: Level 3](#exercise-level-3)\n\n# 📘 Day 1\n\n## 환영합니다\n\n_30 days of Python_에 참여하기로 결정하신 것을 **축하드립니다**. 이 챌린지에서는 Python 프로그래머가 되기 위해 필요한 모든 것과 프로그래밍의 전체 개념을 배우게 됩니다. 챌린지가 끝나면 _30DaysOfPython_프로그래밍 챌린지 인증서를 받게 됩니다.\n\n챌린지에 적극적으로 참여하고 싶다면 [30DaysOfPython challenge](https://t.me/ThirtyDaysOfPython) 텔레그램 그룹에 가입할 수 있습니다.\n\n## 소개\n\nPython은 범용 프로그래밍을 위한 고급 프로그래밍 언어입니다. 오픈 소스, 인터프리터, 객체 지향 프로그래밍 언어입니다. Python은 네덜란드 프로그래머 Guido van Rossum이 만들었습니다. Python 프로그래밍 언어의 이름은 영국 스케치 코미디 시리즈 *Month Python's Flying Circus* 에서 파생되었습니다. 첫 번째 버전은 1991년 2월 20일에 출시되었습니다. 이 30일간의 Python 챌린지는 최신 버전의 Python인 Python 3를 차근차근 배울 수 있도록 도와줄 것입니다. 주제는 30일로 나뉘며, 매일 이해하기 쉬운 설명, 실제 사례, 많은 실습 및 프로젝트가 포함된 여러 주제가 포함됩니다.\n\n이 챌린지는 Python 프로그래밍 언어를 배우고자 하는 초보자와 전문가를 위해 고안되었습니다. 챌린지를 완료하는 데 30~100일이 소요될 수 있으며 텔레그램 그룹에 적극적으로 참여하는 사람들이 챌린지를 완료할 확률이 높습니다.\n시각적 학습자이거나 동영상을 선호하는 경우 이 [완전 초보를 위한 Python 동영상](https://www.youtube.com/watch?v=11OYpBrhdyM)으로 시작할 수 있습니다.\n\n## 왜 Python이느냐?\n\n인간의 언어에 매우 가깝고 배우기 쉽고 사용하기 쉬운 프로그래밍 언어입니다.\nPython은 다양한 산업 및 회사(Google 포함)에서 사용됩니다. 웹 응용 프로그램, 데스크톱 응용 프로그램, 시스템 관리 및 기계 학습 라이브러리를 개발하는 데 사용되었습니다. Python은 데이터 과학 및 기계 학습 커뮤니티에서 널리 사용되는 언어입니다. 이것이 Python 학습을 시작하도록 설득하기에 충분하기를 바랍니다. Python은 세상을 지배하고 있으니 지배 당하기 전에 Python을 지배하십시오.\n## 환경 설정\n\n### Python 설치\n\nPython 스크립트를 실행하려면 Python을 설치해야 합니다. Python을 [다운로드](https://www.python.org/)합시다.\nWindows 사용자인 경우. 빨간색 동그라미 친 버튼을 클릭합니다.\n\n\n\nmacOS 사용자인 경우. 빨간색 동그라미 친 버튼을 클릭합니다.\n\n[](https://www.python.org/)\n\nPython이 설치되어 있는지 확인하려면 장치 터미널에 다음 명령을 작성하십시오.\n\n```shell\npython --version\n```\n\n\n\n터미널에서 보시다시피 저는 현재 _Python 3.7.5_ 버전을 사용하고 있습니다. 귀하의 Python 버전은 내 버전과 다를 수 있지만 3.6 이상이어야 합니다. Python 버전을 볼 수 있다면 잘한 것입니다. 이제 컴퓨터에 Python이 설치되었습니다. 다음 섹션으로 계속 진행하십시오.\n\n### Python 셸\n\nPython은 해석된 스크립팅 언어이므로 컴파일할 필요가 없습니다. 코드를 한 줄씩 실행한다는 의미입니다. Python은 _Python Shell(Python Interactive Shell)_과 함께 제공됩니다. 단일 Python 명령을 실행하고 결과를 얻는 데 사용됩니다.\n\nPython Shell은 사용자의 Python 코드를 기다립니다. 코드를 입력하면 코드를 해석하여 다음 줄에 결과를 표시합니다.\n터미널이나 명령 프롬프트(cmd)를 열고 쓰기:\n\n```shell\npython\n```\n\n\n\nPython 대화형 셸이 열리고 Python 코드(Python 스크립트)를 작성하기를 기다립니다. 기호 >>> 옆에 Python 스크립트를 작성하고 Enter를 누릅니다.\nPython 스크립팅 셸에서 첫 번째 스크립트를 작성해 보겠습니다.\n\n\n\n훌륭합니다. Python 대화형 셸에서 첫 번째 Python 스크립트를 작성했습니다. Python 대화형 셸을 어떻게 닫습니까?\n셸을 닫으려면 기호 옆에 >> **exit()** 명령을 작성하고 Enter 키를 누릅니다.\n\n\n\n이제 Python 대화형 셸을 여는 방법과 종료하는 방법을 알았습니다.\n\nPython은 Python이 이해하는 스크립트를 작성하면 결과를 제공하고 그렇지 않으면 오류를 반환합니다. 고의적인 실수를 하고 Python이 무엇을 반환하는지 봅시다.\n\n\n\n반환된 오류에서 볼 수 있듯이 Python은 우리가 저지른 실수와 _Syntax Error: invalid syntax_를 알고 있을 정도로 영리합니다. Python에서 x를 곱셈으로 사용하는 것은 (x)가 Python에서 유효한 구문이 아니기 때문에 구문 오류입니다. (**x**) 대신 곱셈에 별표(*)를 사용합니다. 반환된 오류는 수정해야 할 사항을 명확하게 보여줍니다.\n\n프로그램에서 오류를 식별하고 제거하는 프로세스를 *디버깅*이라고 합니다. **x** 대신 *를 넣어 디버깅해 봅시다.\n\n\n\n버그가 수정되었고 코드가 실행되었으며 예상했던 결과를 얻었습니다. 프로그래머로서 매일 이러한 종류의 오류를 보게 될 것입니다. 디버깅 방법을 아는 것이 좋습니다. 디버깅을 잘하려면 어떤 종류의 오류가 발생했는지 이해해야 합니다. 발생할 수 있는 Python 오류 중 일부는 *SyntaxError*, *IndexError*, *NameError*, *ModuleNotFoundError*, *KeyError*, *ImportError*, *AttributeError*, *TypeError*, *ValueError*, *ZeroDivisionError* 등입니다. 이후 섹션에서 다른 Python **_오류 유형_**에 대해 자세히 알아볼 것입니다.\n\nPython 대화형 셸을 사용하는 방법을 더 연습해 보겠습니다. 터미널이나 명령 프롬프트로 이동하여 **python**이라는 단어를 씁니다.\n\n\n\nPython 대화형 셸이 열립니다. 몇 가지 기본적인 수학 연산(더하기, 빼기, 곱하기, 나누기, 나머지, 지수)을 수행해 보겠습니다.\n\nPython 코드를 작성하기 전에 먼저 몇 가지 수학을 수행해 보겠습니다:\n\n- 2 + 3 = 5\n- 3 - 2 = 1\n- 3 \\* 2 = 6\n- 3 / 2 = 1.5\n- 3 ^ 2 = 3 x 3 = 9\n\nPython에는 다음과 같은 추가 작업이 있습니다:\n\n- 3 % 2 = 1 => 나머지를 구함\n- 3 // 2 = 1 => 나머지를 제거\n\n위의 수학식을 Python 코드로 바꿔봅시다. Python 셸이 열렸으며 셸 맨 처음에 주석을 작성하겠습니다.\n\n_comment_는 Python에 의해 실행되지 않는 코드의 일부입니다. 따라서 코드를 더 읽기 쉽게 만들기 위해 코드에 일부 텍스트를 남길 수 있습니다. Python은 주석 부분을 실행하지 않습니다. Python에서 주석은 해시(#) 기호로 시작합니다.\n이것이 Python에서 주석을 작성하는 방법입니다\n\n```shell\n # 주석은 해시로 시작합니다.\n # (#) 심볼로 시작하기 때문에 이것은 파이썬 주석입니다.\n```\n\n\n\n다음 섹션으로 이동하기 전에 Python 대화형 셸에서 더 많은 연습을 해 보겠습니다. 셸에서 _exit()_를 작성하여 열린 셸을 닫았다가 다시 열어 Python 셸에서 텍스트를 쓰는 방법을 연습해 봅시다.\n\n\n\n### Visual Studio Code 설치\n\nPython 대화형 셸은 작은 스크립트 코드를 시도하고 테스트하는 데 적합하지만 큰 프로젝트에는 적합하지 않습니다. 실제 작업 환경에서 개발자는 다양한 코드 편집기를 사용하여 코드를 작성합니다. 이 30일간의 Python 프로그래밍 챌린지에서는 Visual Studio 코드를 사용합니다. Visual Studio Code는 매우 인기 있는 오픈 소스 텍스트 편집기입니다. 나는 vscode의 팬이고 Visual Studio 코드를 [다운로드](https://code.visualstudio.com/)하는 것을 추천하고 싶지만, 다른 편집자를 선호한다면 가지고 있는 것을 자유롭게 따르십시오.\n\n[](https://code.visualstudio.com/)\n\nVisual Studio Code를 설치하셨다면 어떻게 사용하는지 알아보겠습니다.\n비디오를 선호하는 경우 Python용 Visual Studio Code[비디오 자습서](https://www.youtube.com/watch?v=bn7Cx4z-vSo)를 따를 수 있습니다.\n\n#### visual studio code를 사용하기\n\nVisual Studio 아이콘을 두 번 클릭하여 Visual Studio 코드를 엽니다. 열면 이런 종류의 인터페이스가 나타납니다. 레이블이 지정된 아이콘을 따라해보세요.\n\n\n\n바탕 화면에 30DaysOfPython이라는 폴더를 만듭니다. 그런 다음 Visual Studio 코드를 사용하여 엽시다.\n\n\n\n\n\n파일을 열면 30DaysOfPython 프로젝트의 디렉토리 내부에 파일과 폴더를 생성하기 위한 바로 가기가 표시됩니다. 아래에서 볼 수 있듯이 첫 번째 파일인 helloworld.py를 만들었습니다. 당신도 똑같이 할 수 있습니다.\n\n\n\n하루동안 오래 코딩을 한 후에 코드 편집기를 닫고 싶습니까? 이렇게 열린 프로젝트를 닫으면 됩니다.\n\n\n\n축하합니다. 개발 환경 설정을 완료했습니다. 코딩을 시작해 봅시다.\n\n## Python 기본\n\n### Python 구문\n\nPython 스크립트는 Python 대화형 셸 또는 코드 편집기에서 작성할 수 있습니다. Python 파일의 확장자는 .py입니다.\n\n### Python 들여 쓰기\n\n들여쓰기는 텍스트의 공백입니다. 많은 언어에서 들여쓰기는 코드 가독성을 높이는 데 사용되지만 Python은 들여쓰기를 사용하여 코드 블록을 만듭니다. 다른 프로그래밍 언어에서는 중괄호를 사용하여 들여쓰기 대신 코드 블록을 만듭니다. Python 코드를 작성할 때 흔히 발생하는 버그 중 하나는 잘못된 들여쓰기입니다.\n\n\n\n### 주석\n\n주석은 코드를 더 읽기 쉽게 만들고 코드에 설명을 남기기 위해 매우 중요합니다. Python은 코드의 주석 부분을 실행하지 않습니다.\nPython에서 해시(#)로 시작하는 모든 텍스트는 주석입니다.\n\n**예시:한 문장 주석**\n\n```shell\n # This is the first comment\n # This is the second comment\n # Python is eating the world\n```\n\n**예시: 여러 문장 주석**\n\nTriple quote can be used for multiline comment if it is not assigned to a variable\n\n```shell\n\"\"\"This is multiline comment\nmultiline comment takes multiple lines.\npython is eating the world\n\"\"\"\n```\n\n### 데이터 타입\n\nPython에는 여러 유형의 데이터 유형이 있습니다. 가장 일반적인 것부터 시작하겠습니다. 다른 데이터 유형은 다른 섹션에서 자세히 다룰 것입니다. 당분간 다양한 데이터 유형을 살펴보고 익숙해지도록 합시다. 지금은 명확하게 이해하지 않아도 됩니다.\n\n#### Number\n\n- Integer: 정수(음수, 영 그리고 양수)\n 예시:\n ... -3, -2, -1, 0, 1, 2, 3 ...\n- Float: 십진수\n 예시\n ... -3.5, -2.25, -1.0, 0.0, 1.1, 2.2, 3.5 ...\n- Complex\n 예시\n 1 + j, 2 + 4j\n\n#### String\n\n작은따옴표 또는 큰따옴표 아래에 있는 하나 이상의 문자 모음입니다. 문자열이 두 문장 이상인 경우 삼중 따옴표를 사용합니다.\n\n**예시:**\n\n```py\n'Asabeneh'\n'Finland'\n'Python'\n'I love teaching'\n'I hope you are enjoying the first day of 30DaysOfPython Challenge'\n```\n\n#### Boolean\n\n부울 데이터 유형은 True 또는 False 값입니다. T와 F는 항상 대문자여야 합니다.\n\n**예시:**\n\n```python\n True # 불이 켜져있나요? 그러면 참입니다.\n False # 불이 꺼져있나요? 그러면 거짓입니다.\n```\n\n#### List\n\nPython 리스트는 다른 데이터 유형 항목을 저장할 수 있는 정렬된 컬렉션입니다. 리스트는 JavaScript의 배열과 비슷합니다.\n\n**Example:**\n\n```py\n[0, 1, 2, 3, 4, 5] # 모두 동일한 데이터 유형 - 숫자 리스트\n['Banana', 'Orange', 'Mango', 'Avocado'] # 모두 동일한 데이터 유형 - 문자열 리스트(과일)\n['Finland','Estonia', 'Sweden','Norway'] # 모두 동일한 데이터 유형 - 문자열 리스트(국가)\n['Banana', 10, False, 9.81] # 리스트의 다양한 데이터 유형 - 문자열, 정수, 부울 및 부동 소수점\n```\n\n#### Dictionary\n\nPython 사전 개체는 키 값 쌍 형식의 정렬되지 않은 데이터 모음입니다.\n\n**Example:**\n\n```py\n{\n'first_name':'Asabeneh',\n'last_name':'Yetayeh',\n'country':'Finland',\n'age':250,\n'is_married':True,\n'skills':['JS', 'React', 'Node', 'Python']\n}\n```\n\n#### Tuple\n\n튜플은 목록과 같은 다양한 데이터 유형의 정렬된 모음이지만 튜플이 생성되면 수정할 수 없습니다. 그것들은 변할 수 없습니다.\n\n**Example:**\n\n```py\n('Asabeneh', 'Pawel', 'Brook', 'Abraham', 'Lidiya') # Names\n```\n\n```py\n('Earth', 'Jupiter', 'Neptune', 'Mars', 'Venus', 'Saturn', 'Uranus', 'Mercury') # planets\n```\n\n#### Set\n\n집합은 목록 및 튜플과 유사한 데이터 유형의 모음입니다. 목록 및 튜플과 달리 집합은 순서가 지정된 항목 모음이 아닙니다. 수학에서와 마찬가지로 Python에서 set은 고유한 항목만 저장합니다.\n\n이후 섹션에서는 각각의 모든 Python 데이터 유형에 대해 자세히 설명합니다.\n\n**Example:**\n\n```py\n{2, 4, 3, 5}\n{3.14, 9.81, 2.7} # order is not important in set\n```\n\n### 데이터 타입 체크\n\n특정 데이터/변수의 데이터 유형을 확인하기 위해 **type** 기능을 사용합니다. 다음 터미널에서 다양한 Python 데이터 유형을 볼 수 있습니다:\n\n\n\n### Python 파일\n\n먼저 프로젝트 폴더인 30DaysOfPython을 엽니다. 이 폴더가 없으면 30DaysOfPython이라는 폴더 이름을 만듭니다. 이 폴더 안에 helloworld.py라는 파일을 만듭니다. 이제 Visual Studio 코드를 사용하여 Python 대화형 셸에서 수행한 작업을 수행해 보겠습니다.\n\nPython 대화형 셸은 **print**를 사용하지 않고 인쇄했지만 Visual Studio 코드에서 결과를 보려면 내장 함수 *print()를 사용해야 합니다. *print()* 내장 함수는 *print('arument1', 'argument2', 'argument3')*와 같이 하나 이상의 인수를 사용합니다. 아래 예를 참조하십시오.\n\n**Example:**\n\n파일 이름은 helloworld.py.\n\n```py\n# Day 1 - 30DaysOfPython Challenge\n\nprint(2 + 3) # addition(+)\nprint(3 - 1) # subtraction(-)\nprint(2 * 3) # multiplication(*)\nprint(3 / 2) # division(/)\nprint(3 ** 2) # exponential(**)\nprint(3 % 2) # modulus(%)\nprint(3 // 2) # Floor division operator(//)\n\n# Checking data types\nprint(type(10)) # Int\nprint(type(3.14)) # Float\nprint(type(1 + 3j)) # Complex number\nprint(type('Asabeneh')) # String\nprint(type([1, 2, 3])) # List\nprint(type({'name':'Asabeneh'})) # Dictionary\nprint(type({9.8, 3.14, 2.7})) # Set\nprint(type((9.8, 3.14, 2.7))) # Tuple\n```\n\nPython 파일을 실행하려면 아래 이미지를 확인하세요. Visual Studio Code에서 녹색 버튼을 실행하거나 터미널에 *python helloworld.py*를 입력하여 Python 파일을 실행할 수 있습니다.\n\n\n\n🌕 좋습니다. 당신은 방금 1일차 도전을 완료했고 당신은 위대한 여정에 있습니다. 이제 뇌와 근육을 위한 몇 가지 훈련을 해봅시다.\n\n## 💻 Exercises - Day 1\n\n### Exercise: Level 1\n\n1. 사용 중인 Python 버전 확인\n2. Python 대화형 셸을 열고 다음 작업을 수행합니다. 피연산자는 3과 4입니다.\n - 더하기(+)\n - 빼기(-)\n - 곱하기(\\*)\n - 나머지(%)\n - 나누기(/)\n - 지수(\\*\\*)\n - 정수 나누기(//)\n3. Python 대화형 셸에 문자열을 씁니다. 문자열은 다음과 같습니다:\n - 이름\n - 가족 이름\n - 국가 이름\n - I am enjoying 30 days of python\n4. 다음 데이터의 데이터 유형을 확인하십시오.:\n - 10\n - 9.8\n - 3.14\n - 4 - 4j\n - ['Asabeneh', 'Python', 'Finland']\n - 이름\n - 가족 이름\n - 국가 이름\n\n### Exercise: Level 2\n\n1. 30DaysOfPython 폴더 안에 day_1이라는 폴더를 만듭니다. day_1 폴더 안에 python 파일 helloworld.py를 만들고 질문 1, 2, 3, 4를 반복하세요. Python 파일에서 작업할 때 _print()_를 사용하는 것을 잊지 마세요. 파일을 저장한 디렉토리로 이동하여 실행합니다.\n\n### Exercise: Level 3\n\n1. Number(Integer, Float, Complex), String, Boolean, List, Tuple, Set 및 Dictionary와 같은 다양한 Python 데이터 유형에 대한 예제를 작성합니다.\n2. 참고 [Euclidean distance](https://en.wikipedia.org/wiki/Euclidean_distance#:~:text=In%20mathematics%2C%20the%20Euclidean%20distance,being%20called%20the%20Pythagorean%20distance.) (2, 3) 과 (10, 8) 사이\n\n🎉 축하합니다 ! 🎉\n\n[Day 2 >>](../02_Day_Variables_builtin_functions/02_variables_builtin_functions.md)\n"
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\n\n \n\n[Dia 2 >>](./02_Day_Variables_builtin_functions/02_variables_builtin_functions.md)\n\n\n\n- [🐍 30 Days Of Python](#-30-days-of-python)\n- [📘 Day 1](#-day-1)\n - [Welcome](#welcome)\n - [Introduction](#introduction)\n - [Why Python ?](#why-python-)\n - [Environment Setup](#environment-setup)\n - [Installing Python](#installing-python)\n - [Python Shell](#python-shell)\n - [Installing Visual Studio Code](#installing-visual-studio-code)\n - [How to use visual studio code](#how-to-use-visual-studio-code)\n - [Basic Python](#basic-python)\n - [Python Syntax](#python-syntax)\n - [Python Indentation](#python-indentation)\n - [Comments](#comments)\n - [Data types](#data-types)\n - [Number](#number)\n - [String](#string)\n - [Booleans](#booleans)\n - [List](#list)\n - [Dictionary](#dictionary)\n - [Tuple](#tuple)\n - [Set](#set)\n - [Checking Data types](#checking-data-types)\n - [Python File](#python-file)\n - [💻 Exercises - Day 1](#-exercises---day-1)\n - [Exercise: Level 1](#exercise-level-1)\n - [Exercise: Level 2](#exercise-level-2)\n - [Exercise: Level 3](#exercise-level-3)\n\n# 📘 Day 1\n\n## Welcome\n\n**Congratulations** for deciding to participate in a _30 days of Python_ programming challenge . In this challenge you will learn everything you need to be a python programmer and the whole concept of programming. In the end of the challenge you will get a _30DaysOfPython_ programming challenge certificate.\n\nIf you would like to actively engage in the challenge, you may join the [30DaysOfPython challenge](https://t.me/ThirtyDaysOfPython) telegram group. \n\n## Introduction\n\nPython is a high-level programming language for general-purpose programming. It is an open source, interpreted, objected-oriented programming language. Python was created by a Dutch programmer, Guido van Rossum. The name of Python programming language was derived from a British sketch comedy series, _Monty Python's Flying Circus_. The first version was released on February 20, 1991. This 30 days of Python challenge will help you learn the latest version of Python, Python 3 step by step. The topics are broken down into 30 days, where each day contains several topics with easy-to-understand explanations, real-world examples, many hands on exercises and projects.\n\nThis challenge is designed for beginners and professionals who want to learn python programming language. It may take 30 to 100 days to complete the challenge, people who actively participate on the telegram group have a high probability of completing the challenge.\n\nThis challenge is easy to read, written in conversational English, engaging, motivating and at the same time, it is very demanding. You need to allocate much time to finish this challenge. If you are a visual learner, you may get the video lesson on Washera YouTube channel. You may start from [Python for Absolute Beginners video](https://youtu.be/OCCWZheOesI). Subscribe the channel, comment and ask questions on YouTube vidoes and be proactive, the author will eventually notice you.\n\nThe author likes to hear your opinion about the challenge, share the author by expressing your thoughts about the 30DaysOfPython challenge. You can leave your testimonial on this [link](https://testimonial-vdzd.onrender.com/)\n\n## Why Python ?\n\nIt is a programming language which is very close to human language and because of that it is easy to learn and use.\nPython is used by various industries and companies (including Google). It has been used to develop web applications, desktop applications, system adminstration, and machine learning libraries. Python is highly embraced language in the data science and machine learning community. I hope this is enough to convince you to start learning Python. Python is eating the world and you are killing it before it eats you.\n\n## Environment Setup\n\n### Installing Python\n\nTo run a python script you need to install python. Let's [download](https://www.python.org/) python.\nIf your are a windows user. Click the button encircled in red.\n\n[](https://www.python.org/)\n\nIf you are a macOS user. Click the button encircled in red.\n\n[](https://www.python.org/)\n\nTo check if python is installed write the following command on your device terminal.\n\n```shell\npython --version\n```\n\n\n\nAs you can see from the terminal, I am using _Python 3.7.5_ version at the moment. Your version of Python might be different from mine by but it should be 3.6 or above. If you mange to see the python version, well done. Python has been installed on your machine. Continue to the next section.\n\n### Python Shell\n\nPython is an interpreted scripting language, so it does not need to be compiled. It means it executes the code line by line. Python comes with a _Python Shell (Python Interactive Shell)_. It is used to execute a single python command and get the result.\n\nPython Shell waits for the Python code from the user. When you enter the code, it interprets the code and shows the result in the next line.\nOpen your terminal or command prompt(cmd) and write:\n\n```shell\npython\n```\n\n\n\nThe Python interactive shell is opened and it is waiting for you to write Python code(Python script). You will write your Python script next to this symbol >>> and then click Enter.\nLet us write our very first script on the Python scripting shell.\n\n\n\nWell done, you wrote your first Python script on Python interactive shell. How do we close the Python interactive shell ?\nTo close the shell, next to this symbol >> write **exit()** command and press Enter.\n\n\n\nNow, you know how to open the Python interactive shell and how to exit from it.\n\nPython will give you results if you write scripts that Python understands, if not it returns errors. Let's make a deliberate mistake and see what Python will return.\n\n\n\nAs you can see from the returned error, Python is so clever that it knows the mistake we made and which was _Syntax Error: invalid syntax_. Using x as multiplication in Python is a syntax error because (x) is not a valid syntax in Python. Instead of (**x**) we use asterisk (*) for multiplication. The returned error clearly shows what to fix.\n\nThe process of identifying and removing errors from a program is called _debugging_. Let us debug it by putting * in place of **x**.\n\n\n\nOur bug was fixed, the code ran and we got a result we were expecting. As a programmer you will see such kind of errors on daily basis. It is good to know how to debug. To be good at debugging you should understand what kind of errors you are facing. Some of the Python errors you may encounter are _SyntaxError_, _IndexError_, _NameError_, _ModuleNotFoundError_, _KeyError_, _ImportError_, _AttributeError_, _TypeError_, _ValueError_, _ZeroDivisionError_ etc. We will see more about different Python **_error types_** in later sections.\n\nLet us practice more how to use Python interactive shell. Go to your terminal or command prompt and write the word **python**.\n\n\n\nThe Python interactive shell is opened. Let us do some basic mathematical operations (addition, subtraction, multiplication, division, modulus, exponential).\n\nLet us do some maths first before we write any Python code:\n\n- 2 + 3 is 5\n- 3 - 2 is 1\n- 3 \\* 2 is 6\n- 3 / 2 is 1.5\n- 3 ** 2 is the same as 3 * 3\n\nIn python we have the following additional operations:\n\n- 3 % 2 = 1 => which means finding the remainder\n- 3 // 2 = 1 => which means removing the remainder\n\nLet us change the above mathematical expressions to Python code. The Python shell has been opened and let us write a comment at the very beginning of the shell.\n\nA _comment_ is a part of the code which is not executed by python. So we can leave some text in our code to make our code more readable. Python does not run the comment part. A comment in python starts with hash(#) symbol.\nThis is how you write a comment in python\n\n```shell\n # comment starts with hash\n # this is a python comment, because it starts with a (#) symbol\n```\n\n\n\nBefore we move on to the next section, let us practice more on the Python interactive shell. Close the opened shell by writing _exit()_ on the shell and open it again and let us practice how to write text on the Python shell.\n\n\n\n### Installing Visual Studio Code\n\nThe Python interactive shell is good to try and test small script codes but it will not be for a big project. In real work environment, developers use different code editors to write codes. In this 30 days of Python programming challenge we will use visual studio code. Visual studio code is a very popular open source text editor. I am a fan of vscode and I would recommend to [download](https://code.visualstudio.com/) visual studio code, but if you are in favor of other editors, feel free to follow with what you have.\n\n[](https://code.visualstudio.com/)\n\nIf you installed visual studio code, let us see how to use it.\nIf you prefer a video, you can follow this Visual Studio Code for Python [Video tutorial](https://www.youtube.com/watch?v=bn7Cx4z-vSo)\n\n#### How to use visual studio code\n\nOpen the visual studio code by double clicking the visual studio icon. When you open it you will get this kind of interface. Try to interact with the labeled icons.\n\n\n\nCreate a folder named 30DaysOfPython on your desktop. Then open it using visual studio code.\n\n\n\n\n\nAfter opening it you will see shortcuts for creating files and folders inside of 30DaysOfPython project's directory. As you can see below, I have created the very first file, helloworld.py. You can do the same.\n\n\n\nAfter a long day of coding, you want to close your code editor, right? This is how you will close the opened project.\n\n\n\nCongratulations, you have finished setting up the development environment. Let us start coding.\n\n## Basic Python\n\n### Python Syntax\n\nA Python script can be written in Python interactive shell or in the code editor. A Python file has an extension .py.\n\n### Python Indentation\n\nAn indentation is a white space in a text. Indentation in many languages is used to increase code readability, however Python uses indentation to create block of codes. In other programming languages curly brackets are used to create blocks of codes instead of indentation. One of the common bugs when writing python code is wrong indentation.\n\n\n\n### Comments\n\nComments are very important to make the code more readable and to leave remarks in our code. Python does not run comment parts of our code.\nAny text starting with hash(#) in Python is a comment.\n\n**Example: Single Line Comment**\n\n```shell\n # This is the first comment\n # This is the second comment\n # Python is eating the world\n```\n\n**Example: Multiline Comment**\n\nTriple quote can be used for multiline comment if it is not assigned to a variable\n\n```shell\n\"\"\"This is multiline comment\nmultiline comment takes multiple lines.\npython is eating the world\n\"\"\"\n```\n\n### Data types\n\nIn Python there are several types of data types. Let us get started with the most common ones. Different data types will be covered in detail in other sections. For the time being, let us just go through the different data types and get familiar with them. You do not have to have a clear understanding now.\n\n#### Number\n\n- Integer: Integer(negative, zero and positive) numbers\n Example:\n ... -3, -2, -1, 0, 1, 2, 3 ...\n- Float: Decimal number\n Example\n ... -3.5, -2.25, -1.0, 0.0, 1.1, 2.2, 3.5 ...\n- Complex\n Example\n 1 + j, 2 + 4j\n\n#### String\n\nA collection of one or more characters under a single or double quote. If a string is more than one sentence then we use a triple quote.\n\n**Example:**\n\n```py\n'Asabeneh'\n'Finland'\n'Python'\n'I love teaching'\n'I hope you are enjoying the first day of 30DaysOfPython Challenge'\n```\n\n#### Booleans\n\nA boolean data type is either a True or False value. T and F should be always uppercase.\n\n**Example:**\n\n```python\n True # Is the light on? If it is on, then the value is True\n False # Is the light on? If it is off, then the value is False\n```\n\n#### List\n\nPython list is an ordered collection which allows to store different data type items. A list is similar to an array in JavaScript.\n\n**Example:**\n\n```py\n[0, 1, 2, 3, 4, 5] # all are the same data types - a list of numbers\n['Banana', 'Orange', 'Mango', 'Avocado'] # all the same data types - a list of strings (fruits)\n['Finland','Estonia', 'Sweden','Norway'] # all the same data types - a list of strings (countries)\n['Banana', 10, False, 9.81] # different data types in the list - string, integer, boolean and float\n```\n\n#### Dictionary\n\nA Python dictionary object is an unordered collection of data in a key value pair format.\n\n**Example:**\n\n```py\n{\n'first_name':'Asabeneh',\n'last_name':'Yetayeh',\n'country':'Finland', \n'age':250, \n'is_married':True,\n'skills':['JS', 'React', 'Node', 'Python']\n}\n```\n\n#### Tuple\n\nA tuple is an ordered collection of different data types like list but tuples can not be modified once they are created. They are immutable.\n\n**Example:**\n\n```py\n('Asabeneh', 'Pawel', 'Brook', 'Abraham', 'Lidiya') # Names\n```\n\n```py\n('Earth', 'Jupiter', 'Neptune', 'Mars', 'Venus', 'Saturn', 'Uranus', 'Mercury') # planets\n```\n\n#### Set\n\nA set is a collection of data types similar to list and tuple. Unlike list and tuple, set is not an ordered collection of items. Like in Mathematics, set in Python stores only unique items.\n\nIn later sections, we will go in detail about each and every Python data type.\n\n**Example:**\n\n```py\n{2, 4, 3, 5}\n{3.14, 9.81, 2.7} # order is not important in set\n```\n\n### Checking Data types\n\nTo check the data type of certain data/variable we use the **type** function. In the following terminal you will see different python data types:\n\n\n\n### Python File\n\nFirst open your project folder, 30DaysOfPython. If you don't have this folder, create a folder name called 30DaysOfPython. Inside this folder, create a file called helloworld.py. Now, let's do what we did on python interactive shell using visual studio code.\n\nThe Python interactive shell was printing without using **print** but on visual studio code to see our result we should use a built in function _print(). The _print()_ built-in function takes one or more arguments as follows _print('arument1', 'argument2', 'argument3')_. See the examples below.\n\n**Example:**\n\nThe file name is helloworld.py\n\n```py\n# Day 1 - 30DaysOfPython Challenge\n\nprint(2 + 3) # addition(+)\nprint(3 - 1) # subtraction(-)\nprint(2 * 3) # multiplication(*)\nprint(3 / 2) # division(/)\nprint(3 ** 2) # exponential(**)\nprint(3 % 2) # modulus(%)\nprint(3 // 2) # Floor division operator(//)\n\n# Checking data types\nprint(type(10)) # Int\nprint(type(3.14)) # Float\nprint(type(1 + 3j)) # Complex number\nprint(type('Asabeneh')) # String\nprint(type([1, 2, 3])) # List\nprint(type({'name':'Asabeneh'})) # Dictionary\nprint(type({9.8, 3.14, 2.7})) # Set\nprint(type((9.8, 3.14, 2.7))) # Tuple\n```\n\nTo run the python file check the image below. You can run the python file either by running the green button on Visual Studio Code or by typing _python helloworld.py_ in the terminal .\n\n\n\n🌕 You are amazing. You have just completed day 1 challenge and you are on your way to greatness. Now do some exercises for your brain and muscles.\n\n## 💻 Exercises - Day 1\n\n### Exercise: Level 1\n\n1. Check the python version you are using\n2. Open the python interactive shell and do the following operations. The operands are 3 and 4.\n - addition(+)\n - subtraction(-)\n - multiplication(\\*)\n - modulus(%)\n - division(/)\n - exponential(\\*\\*)\n - floor division operator(//)\n3. Write strings on the python interactive shell. The strings are the following:\n - Your name\n - Your family name\n - Your country\n - I am enjoying 30 days of python\n4. Check the data types of the following data:\n - 10\n - 9.8\n - 3.14\n - 4 - 4j\n - ['Asabeneh', 'Python', 'Finland']\n - Your name\n - Your family name\n - Your country\n\n### Exercise: Level 2\n\n1. Create a folder named day_1 inside 30DaysOfPython folder. Inside day_1 folder, create a python file helloworld.py and repeat questions 1, 2, 3 and 4. Remember to use _print()_ when you are working on a python file. Navigate to the directory where you have saved your file, and run it.\n\n### Exercise: Level 3\n\n1. Write an example for different Python data types such as Number(Integer, Float, Complex), String, Boolean, List, Tuple, Set and Dictionary.\n2. Find an [Euclidian distance](https://en.wikipedia.org/wiki/Euclidean_distance#:~:text=In%20mathematics%2C%20the%20Euclidean%20distance,being%20called%20the%20Pythagorean%20distance.) between (2, 3) and (10, 8)\n\n🎉 CONGRATULATIONS ! 🎉\n\n[Day 2 >>](./02_Day_Variables_builtin_functions/02_variables_builtin_functions.md)\n"
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"content": "# 🐍 30 днів з Python \n\n| № дня | Теми |\n|-------|:-------------------------------------------------------------------------------------------------------:|\n| 01 | [Вступ](./readme.md) |\n| 02 | [Variables, Built-in Functions](./02_Day_Variables_builtin_functions/02_variables_builtin_functions.md) |\n| 03 | [Operators](../03_Day_Operators/03_operators.md) |\n| 04 | [Strings](../04_Day_Strings/04_strings.md) |\n| 05 | [Lists](../05_Day_Lists/05_lists.md) |\n| 06 | [Tuples](../06_Day_Tuples/06_tuples.md) |\n| 07 | [Sets](../07_Day_Sets/07_sets.md) |\n| 08 | [Dictionaries](../08_Day_Dictionaries/08_dictionaries.md) |\n| 09 | [Conditionals](../09_Day_Conditionals/09_conditionals.md) |\n| 10 | [Loops](../10_Day_Loops/10_loops.md) |\n| 11 | [Functions](../11_Day_Functions/11_functions.md) |\n| 12 | [Modules](../12_Day_Modules/12_modules.md) |\n| 13 | [List Comprehension](../13_Day_List_comprehension/13_list_comprehension.md) |\n| 14 | [Higher Order Functions](../14_Day_Higher_order_functions/14_higher_order_functions.md) | \n| 15 | [Python Type Errors](../15_Day_Python_type_errors/15_python_type_errors.md) | \n| 16 | [Python Date time](../16_Day_Python_date_time/16_python_datetime.md) | \n| 17 | [Exception Handling](../17_Day_Exception_handling/17_exception_handling.md) | \n| 18 | [Regular Expressions](../18_Day_Regular_expressions/18_regular_expressions.md) | \n| 19 | [File Handling](../19_Day_File_handling/19_file_handling.md) |\n| 20 | [Python Package Manager](../20_Day_Python_package_manager/20_python_package_manager.md) |\n| 21 | [Classes and Objects](../21_Day_Classes_and_objects/21_classes_and_objects.md) |\n| 22 | [Web Scraping](../22_Day_Web_scraping/22_web_scraping.md) |\n| 23 | [Virtual Environment](../23_Day_Virtual_environment/23_virtual_environment.md) |\n| 24 | [Statistics](../24_Day_Statistics/24_statistics.md) |\n| 25 | [Pandas](../25_Day_Pandas/25_pandas.md) |\n| 26 | [Python web](../26_Day_Python_web/26_python_web.md) |\n| 27 | [Python with MongoDB](../27_Day_Python_with_mongodb/27_python_with_mongodb.md) |\n| 28 | [API](../28_Day_API/28_API.md) |\n| 29 | [Building API](../29_Day_Building_API/29_building_API.md) |\n| 30 | [Conclusions](../30_Day_Conclusions/30_conclusions.md) |\n\n🧡🧡🧡 ЩАСЛИВОГО ПРОГРАМУВАННЯ 🧡🧡🧡\n\n