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Repository: wbsth/cs50ai
Branch: master
Commit: b97b10ad1b39
Files: 49
Total size: 1.4 MB
Directory structure:
gitextract_o39wik8g/
├── .gitignore
├── README.md
├── week0/
│ ├── degrees/
│ │ ├── degrees.py
│ │ ├── small/
│ │ │ ├── movies.csv
│ │ │ ├── people.csv
│ │ │ └── stars.csv
│ │ └── util.py
│ └── tictactoe/
│ ├── requirements.txt
│ ├── runner.py
│ └── tictactoe.py
├── week1/
│ ├── knights/
│ │ ├── logic.py
│ │ └── puzzle.py
│ └── minesweeper/
│ ├── minesweeper.py
│ ├── requirements.txt
│ └── runner.py
├── week2/
│ ├── heredity/
│ │ └── heredity.py
│ └── pagerank/
│ └── pagerank.py
├── week3/
│ └── crossword/
│ ├── crossword.py
│ ├── data/
│ │ ├── structure0.txt
│ │ ├── structure1.txt
│ │ ├── structure2.txt
│ │ ├── words0.txt
│ │ ├── words1.txt
│ │ └── words2.txt
│ └── generate.py
├── week4/
│ ├── nim/
│ │ ├── nim.py
│ │ └── play.py
│ └── shopping/
│ ├── shopping.csv
│ └── shopping.py
├── week5/
│ └── traffic/
│ └── traffic.py
└── week6/
├── parser/
│ ├── parser.py
│ └── sentences/
│ ├── 1.txt
│ ├── 10.txt
│ ├── 2.txt
│ ├── 3.txt
│ ├── 4.txt
│ ├── 5.txt
│ ├── 6.txt
│ ├── 7.txt
│ ├── 8.txt
│ ├── 9.txt
│ └── test.txt
└── questions/
├── corpus/
│ ├── artificial_intelligence.txt
│ ├── machine_learning.txt
│ ├── natural_language_processing.txt
│ ├── neural_network.txt
│ ├── probability.txt
│ └── python.txt
└── questions.py
================================================
FILE CONTENTS
================================================
================================================
FILE: .gitignore
================================================
*.zip
*.pyc
__pycache__/
.venv/
venv/
.idea/
*/degrees/large/
================================================
FILE: README.md
================================================
# CS50 AI
Mine solutions for CS50's Introduction to Artificial Intelligence with Python course
*Warning : before visiting this repo files, please read about [CS50's Academic Honesty rules](https://cs50.harvard.edu/college/2021/fall/syllabus/#academic-honesty)*.
## Includes:
* Quizzes answers
* Projects solutions
## Course info:
* __Name:__ CS50's Introduction to Artificial Intelligence with Python
* __University:__ Harvard University
* __WWW:__ https://cs50.harvard.edu/ai/2020/
================================================
FILE: week0/degrees/degrees.py
================================================
import csv
import sys
from util import Node, StackFrontier, QueueFrontier
# Maps names to a set of corresponding person_ids
names = {}
# Maps person_ids to a dictionary of: name, birth, movies (a set of movie_ids)
people = {}
# Maps movie_ids to a dictionary of: title, year, stars (a set of person_ids)
movies = {}
def load_data(directory):
"""
Load data from CSV files into memory.
"""
# Load people
with open(f"{directory}/people.csv", encoding="utf-8") as f:
reader = csv.DictReader(f)
for row in reader:
people[row["id"]] = {
"name": row["name"],
"birth": row["birth"],
"movies": set()
}
if row["name"].lower() not in names:
names[row["name"].lower()] = {row["id"]}
else:
names[row["name"].lower()].add(row["id"])
# Load movies
with open(f"{directory}/movies.csv", encoding="utf-8") as f:
reader = csv.DictReader(f)
for row in reader:
movies[row["id"]] = {
"title": row["title"],
"year": row["year"],
"stars": set()
}
# Load stars
with open(f"{directory}/stars.csv", encoding="utf-8") as f:
reader = csv.DictReader(f)
for row in reader:
try:
people[row["person_id"]]["movies"].add(row["movie_id"])
movies[row["movie_id"]]["stars"].add(row["person_id"])
except KeyError:
pass
def main():
if len(sys.argv) > 2:
sys.exit("Usage: python degrees.py [directory]")
directory = sys.argv[1] if len(sys.argv) == 2 else "large"
# Load data from files into memory
print("Loading data...")
load_data(directory)
print("Data loaded.")
source = person_id_for_name(input("Name: "))
if source is None:
sys.exit("Person not found.")
target = person_id_for_name(input("Name: "))
if target is None:
sys.exit("Person not found.")
path = shortest_path(source, target)
if path is None:
print("Not connected.")
else:
degrees = len(path)
print(f"{degrees} degrees of separation.")
path = [(None, source)] + path
for i in range(degrees):
person1 = people[path[i][1]]["name"]
person2 = people[path[i + 1][1]]["name"]
movie = movies[path[i + 1][0]]["title"]
print(f"{i + 1}: {person1} and {person2} starred in {movie}")
def shortest_path(source, target):
"""
Returns the shortest list of (movie_id, person_id) pairs
that connect the source to the target.
If no possible path, returns None.
"""
start = Node(state=source, parent=None, action=None)
frontier = QueueFrontier()
frontier.add(start)
explored = set()
while True:
if frontier.empty():
return None
node = frontier.remove()
if node.state == target:
rt = []
while node.parent is not None:
rt.append((node.action, node.state))
node = node.parent
rt.reverse()
return rt
explored.add(node.state)
# find neighbours
neighbours = neighbors_for_person(node.state)
# add neighbours to frontier
for action, state in neighbours:
if not frontier.contains_state(state) and state not in explored:
child = Node(state=state, parent=node, action=action)
if child.state == target:
rt = []
while child.parent is not None:
rt.append((child.action, child.state))
child = child.parent
rt.reverse()
return rt
frontier.add(child)
def person_id_for_name(name):
"""
Returns the IMDB id for a person's name,
resolving ambiguities as needed.
"""
person_ids = list(names.get(name.lower(), set()))
if len(person_ids) == 0:
return None
elif len(person_ids) > 1:
print(f"Which '{name}'?")
for person_id in person_ids:
person = people[person_id]
name = person["name"]
birth = person["birth"]
print(f"ID: {person_id}, Name: {name}, Birth: {birth}")
try:
person_id = input("Intended Person ID: ")
if person_id in person_ids:
return person_id
except ValueError:
pass
return None
else:
return person_ids[0]
def neighbors_for_person(person_id):
"""
Returns (movie_id, person_id) pairs for people
who starred with a given person.
"""
movie_ids = people[person_id]["movies"]
neighbors = set()
for movie_id in movie_ids:
for person_id in movies[movie_id]["stars"]:
neighbors.add((movie_id, person_id))
return neighbors
if __name__ == "__main__":
main()
================================================
FILE: week0/degrees/small/movies.csv
================================================
id,title,year
112384,"Apollo 13",1995
104257,"A Few Good Men",1992
109830,"Forrest Gump",1994
93779,"The Princess Bride",1987
95953,"Rain Man",1988
================================================
FILE: week0/degrees/small/people.csv
================================================
id,name,birth
102,"Kevin Bacon",1958
129,"Tom Cruise",1962
144,"Cary Elwes",1962
158,"Tom Hanks",1956
1597,"Mandy Patinkin",1952
163,"Dustin Hoffman",1937
1697,"Chris Sarandon",1942
193,"Demi Moore",1962
197,"Jack Nicholson",1937
200,"Bill Paxton",1955
398,"Sally Field",1946
420,"Valeria Golino",1965
596520,"Gerald R. Molen",1935
641,"Gary Sinise",1955
705,"Robin Wright",1966
914612,"Emma Watson",1990
================================================
FILE: week0/degrees/small/stars.csv
================================================
person_id,movie_id
102,104257
102,112384
129,104257
129,95953
144,93779
158,109830
158,112384
1597,93779
163,95953
1697,93779
193,104257
197,104257
200,112384
398,109830
420,95953
596520,95953
641,109830
641,112384
705,109830
705,93779
================================================
FILE: week0/degrees/util.py
================================================
class Node():
def __init__(self, state, parent, action):
self.state = state
self.parent = parent
self.action = action
class StackFrontier():
def __init__(self):
self.frontier = []
def add(self, node):
self.frontier.append(node)
def contains_state(self, state):
return any(node.state == state for node in self.frontier)
def empty(self):
return len(self.frontier) == 0
def remove(self):
if self.empty():
raise Exception("empty frontier")
else:
node = self.frontier[-1]
self.frontier = self.frontier[:-1]
return node
class QueueFrontier(StackFrontier):
def remove(self):
if self.empty():
raise Exception("empty frontier")
else:
node = self.frontier[0]
self.frontier = self.frontier[1:]
return node
================================================
FILE: week0/tictactoe/requirements.txt
================================================
pygame
================================================
FILE: week0/tictactoe/runner.py
================================================
import pygame
import sys
import time
import tictactoe as ttt
pygame.init()
size = width, height = 600, 400
# Colors
black = (0, 0, 0)
white = (255, 255, 255)
screen = pygame.display.set_mode(size)
mediumFont = pygame.font.Font("OpenSans-Regular.ttf", 28)
largeFont = pygame.font.Font("OpenSans-Regular.ttf", 40)
moveFont = pygame.font.Font("OpenSans-Regular.ttf", 60)
user = None
board = ttt.initial_state()
ai_turn = False
while True:
for event in pygame.event.get():
if event.type == pygame.QUIT:
sys.exit()
screen.fill(black)
# Let user choose a player.
if user is None:
# Draw title
title = largeFont.render("Play Tic-Tac-Toe", True, white)
titleRect = title.get_rect()
titleRect.center = ((width / 2), 50)
screen.blit(title, titleRect)
# Draw buttons
playXButton = pygame.Rect((width / 8), (height / 2), width / 4, 50)
playX = mediumFont.render("Play as X", True, black)
playXRect = playX.get_rect()
playXRect.center = playXButton.center
pygame.draw.rect(screen, white, playXButton)
screen.blit(playX, playXRect)
playOButton = pygame.Rect(5 * (width / 8), (height / 2), width / 4, 50)
playO = mediumFont.render("Play as O", True, black)
playORect = playO.get_rect()
playORect.center = playOButton.center
pygame.draw.rect(screen, white, playOButton)
screen.blit(playO, playORect)
# Check if button is clicked
click, _, _ = pygame.mouse.get_pressed()
if click == 1:
mouse = pygame.mouse.get_pos()
if playXButton.collidepoint(mouse):
time.sleep(0.2)
user = ttt.X
elif playOButton.collidepoint(mouse):
time.sleep(0.2)
user = ttt.O
else:
# Draw game board
tile_size = 80
tile_origin = (width / 2 - (1.5 * tile_size),
height / 2 - (1.5 * tile_size))
tiles = []
for i in range(3):
row = []
for j in range(3):
rect = pygame.Rect(
tile_origin[0] + j * tile_size,
tile_origin[1] + i * tile_size,
tile_size, tile_size
)
pygame.draw.rect(screen, white, rect, 3)
if board[i][j] != ttt.EMPTY:
move = moveFont.render(board[i][j], True, white)
moveRect = move.get_rect()
moveRect.center = rect.center
screen.blit(move, moveRect)
row.append(rect)
tiles.append(row)
game_over = ttt.terminal(board)
player = ttt.player(board)
# Show title
if game_over:
winner = ttt.winner(board)
if winner is None:
title = f"Game Over: Tie."
else:
title = f"Game Over: {winner} wins."
elif user == player:
title = f"Play as {user}"
else:
title = f"Computer thinking..."
title = largeFont.render(title, True, white)
titleRect = title.get_rect()
titleRect.center = ((width / 2), 30)
screen.blit(title, titleRect)
# Check for AI move
if user != player and not game_over:
if ai_turn:
time.sleep(0.5)
move = ttt.minimax(board)
board = ttt.result(board, move)
ai_turn = False
else:
ai_turn = True
# Check for a user move
click, _, _ = pygame.mouse.get_pressed()
if click == 1 and user == player and not game_over:
mouse = pygame.mouse.get_pos()
for i in range(3):
for j in range(3):
if (board[i][j] == ttt.EMPTY and tiles[i][j].collidepoint(mouse)):
board = ttt.result(board, (i, j))
if game_over:
againButton = pygame.Rect(width / 3, height - 65, width / 3, 50)
again = mediumFont.render("Play Again", True, black)
againRect = again.get_rect()
againRect.center = againButton.center
pygame.draw.rect(screen, white, againButton)
screen.blit(again, againRect)
click, _, _ = pygame.mouse.get_pressed()
if click == 1:
mouse = pygame.mouse.get_pos()
if againButton.collidepoint(mouse):
time.sleep(0.2)
user = None
board = ttt.initial_state()
ai_turn = False
pygame.display.flip()
================================================
FILE: week0/tictactoe/tictactoe.py
================================================
"""
Tic Tac Toe Player
"""
import math
from copy import deepcopy
X = "X"
O = "O"
EMPTY = None
def initial_state():
"""
Returns starting state of the board.
"""
return [[EMPTY, EMPTY, EMPTY],
[EMPTY, EMPTY, EMPTY],
[EMPTY, EMPTY, EMPTY]]
def player(board):
"""
Returns player who has the next turn on a board.
"""
Xcount = 0
Ocount = 0
for row in board:
Xcount += row.count(X)
Ocount += row.count(O)
if Xcount <= Ocount:
return X
else:
return O
def actions(board):
"""
Returns set of all possible actions (i, j) available on the board.
"""
possible_moves = set()
for row_index, row in enumerate(board):
for column_index, item in enumerate(row):
if item == None:
possible_moves.add((row_index, column_index))
return possible_moves
def result(board, action):
"""
Returns the board that results from making move (i, j) on the board.
"""
player_move = player(board)
new_board = deepcopy(board)
i, j = action
if board[i][j] != None:
raise Exception
else:
new_board[i][j] = player_move
return new_board
def winner(board):
"""
Returns the winner of the game, if there is one.
"""
for player in (X, O):
# check vertical
for row in board:
if row == [player] * 3:
return player
# check horizontal
for i in range(3):
column = [board[x][i] for x in range(3)]
if column == [player] * 3:
return player
# check diagonal
if [board[i][i] for i in range(0, 3)] == [player] * 3:
return player
elif [board[i][~i] for i in range(0, 3)] == [player] * 3:
return player
return None
def terminal(board):
"""
Returns True if game is over, False otherwise.
"""
# game is won by one of the players
if winner(board) != None:
return True
# moves still possible
for row in board:
if EMPTY in row:
return False
# no possible moves
return True
def utility(board):
"""
Returns 1 if X has won the game, -1 if O has won, 0 otherwise.
"""
win_player = winner(board)
if win_player == X:
return 1
elif win_player == O:
return -1
else:
return 0
def minimax(board):
"""
Returns the optimal action for the current player on the board.
"""
def max_value(board):
optimal_move = ()
if terminal(board):
return utility(board), optimal_move
else:
v = -5
for action in actions(board):
minval = min_value(result(board, action))[0]
if minval > v:
v = minval
optimal_move = action
return v, optimal_move
def min_value(board):
optimal_move = ()
if terminal(board):
return utility(board), optimal_move
else:
v = 5
for action in actions(board):
maxval = max_value(result(board, action))[0]
if maxval < v:
v = maxval
optimal_move = action
return v, optimal_move
curr_player = player(board)
if terminal(board):
return None
if curr_player == X:
return max_value(board)[1]
else:
return min_value(board)[1]
================================================
FILE: week1/knights/logic.py
================================================
import itertools
class Sentence():
def evaluate(self, model):
"""Evaluates the logical sentence."""
raise Exception("nothing to evaluate")
def formula(self):
"""Returns string formula representing logical sentence."""
return ""
def symbols(self):
"""Returns a set of all symbols in the logical sentence."""
return set()
@classmethod
def validate(cls, sentence):
if not isinstance(sentence, Sentence):
raise TypeError("must be a logical sentence")
@classmethod
def parenthesize(cls, s):
"""Parenthesizes an expression if not already parenthesized."""
def balanced(s):
"""Checks if a string has balanced parentheses."""
count = 0
for c in s:
if c == "(":
count += 1
elif c == ")":
if count <= 0:
return False
count -= 1
return count == 0
if not len(s) or s.isalpha() or (
s[0] == "(" and s[-1] == ")" and balanced(s[1:-1])
):
return s
else:
return f"({s})"
class Symbol(Sentence):
def __init__(self, name):
self.name = name
def __eq__(self, other):
return isinstance(other, Symbol) and self.name == other.name
def __hash__(self):
return hash(("symbol", self.name))
def __repr__(self):
return self.name
def evaluate(self, model):
try:
return bool(model[self.name])
except KeyError:
raise Exception(f"variable {self.name} not in model")
def formula(self):
return self.name
def symbols(self):
return {self.name}
class Not(Sentence):
def __init__(self, operand):
Sentence.validate(operand)
self.operand = operand
def __eq__(self, other):
return isinstance(other, Not) and self.operand == other.operand
def __hash__(self):
return hash(("not", hash(self.operand)))
def __repr__(self):
return f"Not({self.operand})"
def evaluate(self, model):
return not self.operand.evaluate(model)
def formula(self):
return "¬" + Sentence.parenthesize(self.operand.formula())
def symbols(self):
return self.operand.symbols()
class And(Sentence):
def __init__(self, *conjuncts):
for conjunct in conjuncts:
Sentence.validate(conjunct)
self.conjuncts = list(conjuncts)
def __eq__(self, other):
return isinstance(other, And) and self.conjuncts == other.conjuncts
def __hash__(self):
return hash(
("and", tuple(hash(conjunct) for conjunct in self.conjuncts))
)
def __repr__(self):
conjunctions = ", ".join(
[str(conjunct) for conjunct in self.conjuncts]
)
return f"And({conjunctions})"
def add(self, conjunct):
Sentence.validate(conjunct)
self.conjuncts.append(conjunct)
def evaluate(self, model):
return all(conjunct.evaluate(model) for conjunct in self.conjuncts)
def formula(self):
if len(self.conjuncts) == 1:
return self.conjuncts[0].formula()
return " ∧ ".join([Sentence.parenthesize(conjunct.formula())
for conjunct in self.conjuncts])
def symbols(self):
return set.union(*[conjunct.symbols() for conjunct in self.conjuncts])
class Or(Sentence):
def __init__(self, *disjuncts):
for disjunct in disjuncts:
Sentence.validate(disjunct)
self.disjuncts = list(disjuncts)
def __eq__(self, other):
return isinstance(other, Or) and self.disjuncts == other.disjuncts
def __hash__(self):
return hash(
("or", tuple(hash(disjunct) for disjunct in self.disjuncts))
)
def __repr__(self):
disjuncts = ", ".join([str(disjunct) for disjunct in self.disjuncts])
return f"Or({disjuncts})"
def evaluate(self, model):
return any(disjunct.evaluate(model) for disjunct in self.disjuncts)
def formula(self):
if len(self.disjuncts) == 1:
return self.disjuncts[0].formula()
return " ∨ ".join([Sentence.parenthesize(disjunct.formula())
for disjunct in self.disjuncts])
def symbols(self):
return set.union(*[disjunct.symbols() for disjunct in self.disjuncts])
class Implication(Sentence):
def __init__(self, antecedent, consequent):
Sentence.validate(antecedent)
Sentence.validate(consequent)
self.antecedent = antecedent
self.consequent = consequent
def __eq__(self, other):
return (isinstance(other, Implication)
and self.antecedent == other.antecedent
and self.consequent == other.consequent)
def __hash__(self):
return hash(("implies", hash(self.antecedent), hash(self.consequent)))
def __repr__(self):
return f"Implication({self.antecedent}, {self.consequent})"
def evaluate(self, model):
return ((not self.antecedent.evaluate(model))
or self.consequent.evaluate(model))
def formula(self):
antecedent = Sentence.parenthesize(self.antecedent.formula())
consequent = Sentence.parenthesize(self.consequent.formula())
return f"{antecedent} => {consequent}"
def symbols(self):
return set.union(self.antecedent.symbols(), self.consequent.symbols())
class Biconditional(Sentence):
def __init__(self, left, right):
Sentence.validate(left)
Sentence.validate(right)
self.left = left
self.right = right
def __eq__(self, other):
return (isinstance(other, Biconditional)
and self.left == other.left
and self.right == other.right)
def __hash__(self):
return hash(("biconditional", hash(self.left), hash(self.right)))
def __repr__(self):
return f"Biconditional({self.left}, {self.right})"
def evaluate(self, model):
return ((self.left.evaluate(model)
and self.right.evaluate(model))
or (not self.left.evaluate(model)
and not self.right.evaluate(model)))
def formula(self):
left = Sentence.parenthesize(str(self.left))
right = Sentence.parenthesize(str(self.right))
return f"{left} <=> {right}"
def symbols(self):
return set.union(self.left.symbols(), self.right.symbols())
def model_check(knowledge, query):
"""Checks if knowledge base entails query."""
def check_all(knowledge, query, symbols, model):
"""Checks if knowledge base entails query, given a particular model."""
# If model has an assignment for each symbol
if not symbols:
# If knowledge base is true in model, then query must also be true
if knowledge.evaluate(model):
return query.evaluate(model)
return True
else:
# Choose one of the remaining unused symbols
remaining = symbols.copy()
p = remaining.pop()
# Create a model where the symbol is true
model_true = model.copy()
model_true[p] = True
# Create a model where the symbol is false
model_false = model.copy()
model_false[p] = False
# Ensure entailment holds in both models
return (check_all(knowledge, query, remaining, model_true) and
check_all(knowledge, query, remaining, model_false))
# Get all symbols in both knowledge and query
symbols = set.union(knowledge.symbols(), query.symbols())
# Check that knowledge entails query
return check_all(knowledge, query, symbols, dict())
================================================
FILE: week1/knights/puzzle.py
================================================
from logic import *
AKnight = Symbol("A is a Knight")
AKnave = Symbol("A is a Knave")
BKnight = Symbol("B is a Knight")
BKnave = Symbol("B is a Knave")
CKnight = Symbol("C is a Knight")
CKnave = Symbol("C is a Knave")
# Puzzle 0
# A says "I am both a knight and a knave."
knowledge0 = And(
Not(And(AKnight, AKnave)), # cannot be knight and knave at the same time
Or(AKnight, AKnave), # will be Knight or Knave
Implication(AKnight, And(AKnight, AKnave)),
Implication(AKnave, Not(And(AKnight, AKnave)))
)
# Puzzle 1
# A says "We are both knaves."
# B says nothing.
knowledge1 = And(
Not(And(AKnight, AKnave)), # cannot be knight and knave at the same time
Or(AKnight, AKnave), # will be Knight or Knave
Not(And(BKnight, BKnave)), # cannot be knight and knave at the same time
Or(BKnight, BKnave), # will be Knight or Knave
# Or(And(AKnight, BKnave), And(AKnave, BKnight)), # A and B can't be the same figure
Implication(AKnight, And(AKnave, BKnave)),
Implication(AKnave, Not(And(AKnave, BKnave)))
)
# Puzzle 2
# A says "We are the same kind."
# B says "We are of different kinds."
knowledge2 = And(
Not(And(AKnight, AKnave)), # cannot be knight and knave at the same time
Or(AKnight, AKnave), # will be Knight or Knave
Not(And(BKnight, BKnave)), # cannot be knight and knave at the same time
Or(BKnight, BKnave), # will be Knight or Knave
# Or(And(AKnight, BKnave), And(AKnave, BKnight)), # A and B can't be the same figure
Implication(AKnight, And(AKnight, BKnight)),
Implication(AKnave, Not(And(AKnave, BKnave))),
Implication(BKnight, And(BKnight, AKnave)),
Implication(BKnave, Not(And(BKnave, AKnight)))
)
# Puzzle 3
# A says either "I am a knight." or "I am a knave.", but you don't know which.
# B says "A said 'I am a knave'."
# B says "C is a knave."
# C says "A is a knight."
knowledge3 = And(
Not(And(AKnight, AKnave)), # A cannot be knight and knave at the same time
Or(AKnight, AKnave), # A will be Knight or Knave
Not(And(BKnight, BKnave)), # B cannot be knight and knave at the same time
Or(BKnight, BKnave), # B will be Knight or Knave
Not(And(CKnight, CKnave)), # C cannot be knight and knave at the same time
Or(CKnight, CKnave), # C will be Knight or Knave
# A says either "I am a knight." or "I am a knave.", but you don't know which.
Or(
# "I am a knight."
And(
Implication(AKnight, AKnight),
Implication(AKnave, Not(AKnight))
),
# "I am a knave."
And(
Implication(AKnight, AKnave),
Implication(AKnave, Not(AKnave))
)
),
Not(And(
# "I am a knight."
And(
Implication(AKnight, AKnight),
Implication(AKnave, Not(AKnight))
),
# "I am a knave."
And(
Implication(AKnight, AKnave),
Implication(AKnave, Not(AKnave))
)
)),
# B says "A said 'I am a knave'."
Implication(BKnight, And(
Implication(AKnight, AKnave),
Implication(AKnave, Not(AKnave))
)),
Implication(BKnave, Not(And(
Implication(AKnight, AKnave),
Implication(AKnave, Not(AKnave))
))),
# B says "C is a knave."
Implication(BKnight, CKnave),
Implication(BKnave, Not(CKnave)),
# C says "A is a knight."
Implication(CKnight, AKnight),
Implication(CKnave, Not(AKnight))
)
def main():
symbols = [AKnight, AKnave, BKnight, BKnave, CKnight, CKnave]
puzzles = [
("Puzzle 0", knowledge0),
("Puzzle 1", knowledge1),
("Puzzle 2", knowledge2),
("Puzzle 3", knowledge3)
]
for puzzle, knowledge in puzzles:
print(puzzle)
if len(knowledge.conjuncts) == 0:
print(" Not yet implemented.")
else:
for symbol in symbols:
if model_check(knowledge, symbol):
print(f" {symbol}")
if __name__ == "__main__":
main()
================================================
FILE: week1/minesweeper/minesweeper.py
================================================
import itertools
import random
import copy
class Minesweeper():
"""
Minesweeper game representation
"""
def __init__(self, height=8, width=8, mines=8):
# Set initial width, height, and number of mines
self.height = height
self.width = width
self.mines = set()
# Initialize an empty field with no mines
self.board = []
for i in range(self.height):
row = []
for j in range(self.width):
row.append(False)
self.board.append(row)
# Add mines randomly
while len(self.mines) != mines:
i = random.randrange(height)
j = random.randrange(width)
if not self.board[i][j]:
self.mines.add((i, j))
self.board[i][j] = True
# At first, player has found no mines
self.mines_found = set()
def print(self):
"""
Prints a text-based representation
of where mines are located.
"""
for i in range(self.height):
print("--" * self.width + "-")
for j in range(self.width):
if self.board[i][j]:
print("|X", end="")
else:
print("| ", end="")
print("|")
print("--" * self.width + "-")
def is_mine(self, cell):
i, j = cell
return self.board[i][j]
def nearby_mines(self, cell):
"""
Returns the number of mines that are
within one row and column of a given cell,
not including the cell itself.
"""
# Keep count of nearby mines
count = 0
# Loop over all cells within one row and column
for i in range(cell[0] - 1, cell[0] + 2):
for j in range(cell[1] - 1, cell[1] + 2):
# Ignore the cell itself
if (i, j) == cell:
continue
# Update count if cell in bounds and is mine
if 0 <= i < self.height and 0 <= j < self.width:
if self.board[i][j]:
count += 1
return count
def won(self):
"""
Checks if all mines have been flagged.
"""
return self.mines_found == self.mines
class Sentence():
"""
Logical statement about a Minesweeper game
A sentence consists of a set of board cells,
and a count of the number of those cells which are mines.
"""
def __init__(self, cells, count):
self.cells = set(cells)
self.count = count
def __eq__(self, other):
return self.cells == other.cells and self.count == other.count
def __str__(self):
return f"{self.cells} = {self.count}"
def known_mines(self):
"""
Returns the set of all cells in self.cells known to be mines.
"""
if self.count == len(self.cells):
return self.cells
def known_safes(self):
"""
Returns the set of all cells in self.cells known to be safe.
"""
if self.count == 0:
return self.cells
def mark_mine(self, cell):
"""
Updates internal knowledge representation given the fact that
a cell is known to be a mine.
"""
if cell in self.cells:
self.cells.remove(cell)
self.count -= 1
else:
pass
def mark_safe(self, cell):
"""
Updates internal knowledge representation given the fact that
a cell is known to be safe.
"""
if cell in self.cells:
self.cells.remove(cell)
else:
pass
class MinesweeperAI():
"""
Minesweeper game player
"""
def __init__(self, height=8, width=8):
# Set initial height and width
self.height = height
self.width = width
# Keep track of which cells have been clicked on
self.moves_made = set()
# Keep track of cells known to be safe or mines
self.mines = set()
self.safes = set()
# List of sentences about the game known to be true
self.knowledge = []
def mark_mine(self, cell):
"""
Marks a cell as a mine, and updates all knowledge
to mark that cell as a mine as well.
"""
self.mines.add(cell)
for sentence in self.knowledge:
sentence.mark_mine(cell)
def mark_safe(self, cell):
"""
Marks a cell as safe, and updates all knowledge
to mark that cell as safe as well.
"""
self.safes.add(cell)
for sentence in self.knowledge:
sentence.mark_safe(cell)
def add_knowledge(self, cell, count):
"""
Called when the Minesweeper board tells us, for a given
safe cell, how many neighboring cells have mines in them.
This function should:
1) mark the cell as a move that has been made
2) mark the cell as safe
3) add a new sentence to the AI's knowledge base
based on the value of `cell` and `count`
4) mark any additional cells as safe or as mines
if it can be concluded based on the AI's knowledge base
5) add any new sentences to the AI's knowledge base
if they can be inferred from existing knowledge
"""
# mark the cell as one of the moves made in the game
self.moves_made.add(cell)
# mark the cell as a safe cell, updating any sequences that contain the cell as well
self.mark_safe(cell)
# add new sentence to AI knowledge base based on value of cell and count
cells = set()
count_cpy = copy.deepcopy(count)
close_cells = self.return_close_cells(cell) # returns neighbour cells
for cl in close_cells:
if cl in self.mines:
count_cpy -= 1
if cl not in self.mines | self.safes:
cells.add(cl) # only add cells that are of unknown state
new_sentence = Sentence(cells, count_cpy) # prepare new sentence
if len(new_sentence.cells) > 0: # add that sentence to knowledge only if it is not empty
self.knowledge.append(new_sentence)
# print(f"Adding new sentence: {new_sentence}")
# # print("Printing knowledge:")
# for sent in self.knowledge:
# # print(sent)
# check sentences for new cells that could be marked as safe or as mine
self.check_knowledge()
# print(f"Safe cells: {self.safes - self.moves_made}")
# print(f"Mine cells: {self.mines}")
# print("------------")
self.extra_inference()
def return_close_cells(self, cell):
"""
returns cell that are 1 cell away from cell passed in arg
"""
# returns cells close to arg cell by 1 cell
close_cells = set()
for rows in range(self.height):
for columns in range(self.width):
if abs(cell[0] - rows) <= 1 and abs(cell[1] - columns) <= 1 and (rows, columns) != cell:
close_cells.add((rows, columns))
return close_cells
def check_knowledge(self):
"""
check knowledge for new safes and mines, updates knowledge if possible
"""
# copies the knowledge to operate on copy
knowledge_copy = copy.deepcopy(self.knowledge)
# iterates through sentences
for sentence in knowledge_copy:
if len(sentence.cells) == 0:
try:
self.knowledge.remove(sentence)
except ValueError:
pass
# check for possible mines and safes
mines = sentence.known_mines()
safes = sentence.known_safes()
# update knowledge if mine or safe was found
if mines:
for mine in mines:
# print(f"Marking {mine} as mine")
self.mark_mine(mine)
self.check_knowledge()
if safes:
for safe in safes:
# print(f"Marking {safe} as safe")
self.mark_safe(safe)
self.check_knowledge()
def extra_inference(self):
"""
update knowledge based on inference
"""
# iterate through pairs of sentences
for sentence1 in self.knowledge:
for sentence2 in self.knowledge:
# check if sentence 1 is subset of sentence 2
if sentence1.cells.issubset(sentence2.cells):
new_cells = sentence2.cells - sentence1.cells
new_count = sentence2.count - sentence1.count
new_sentence = Sentence(new_cells, new_count)
mines = new_sentence.known_mines()
safes = new_sentence.known_safes()
if mines:
for mine in mines:
# print(f"Used inference to mark mine: {mine}")
# print(f"FinalSen: {new_sentence}")
# print(f"Sent1: {sent1copy}")
# print(f"Sent2: {sent2copy}")
self.mark_mine(mine)
if safes:
for safe in safes:
# print(f"Used inference to mark safe: {safe}")
# print(f"FinalSen: {new_sentence}")
# print(f"Sent1: {sent1copy}")
# print(f"Sent2: {sent2copy}")
self.mark_safe(safe)
def make_safe_move(self):
"""
Returns a safe cell to choose on the Minesweeper board.
The move must be known to be safe, and not already a move
that has been made.
This function may use the knowledge in self.mines, self.safes
and self.moves_made, but should not modify any of those values.
"""
for i in self.safes - self.moves_made:
# choose first safe cell that wasn't picked before
# print(f"Making {i} move")
return i
return None
def make_random_move(self):
"""
Returns a move to make on the Minesweeper board.
Should choose randomly among cells that:
1) have not already been chosen, and
2) are not known to be mines
"""
maxmoves = self.width * self.height
while maxmoves > 0:
maxmoves -= 1
row = random.randrange(self.height)
column = random.randrange(self.width)
if (row, column) not in self.moves_made | self.mines:
return (row, column)
return None
================================================
FILE: week1/minesweeper/requirements.txt
================================================
pygame
================================================
FILE: week1/minesweeper/runner.py
================================================
import pygame
import sys
import time
from minesweeper import Minesweeper, MinesweeperAI
HEIGHT = 8
WIDTH = 8
MINES = 8
# Colors
BLACK = (0, 0, 0)
GRAY = (180, 180, 180)
WHITE = (255, 255, 255)
# Create game
pygame.init()
size = width, height = 600, 400
screen = pygame.display.set_mode(size)
# Fonts
OPEN_SANS = "assets/fonts/OpenSans-Regular.ttf"
smallFont = pygame.font.Font(OPEN_SANS, 20)
mediumFont = pygame.font.Font(OPEN_SANS, 28)
largeFont = pygame.font.Font(OPEN_SANS, 40)
# Compute board size
BOARD_PADDING = 20
board_width = ((2 / 3) * width) - (BOARD_PADDING * 2)
board_height = height - (BOARD_PADDING * 2)
cell_size = int(min(board_width / WIDTH, board_height / HEIGHT))
board_origin = (BOARD_PADDING, BOARD_PADDING)
# Add images
flag = pygame.image.load("assets/images/flag.png")
flag = pygame.transform.scale(flag, (cell_size, cell_size))
mine = pygame.image.load("assets/images/mine.png")
mine = pygame.transform.scale(mine, (cell_size, cell_size))
# Create game and AI agent
game = Minesweeper(height=HEIGHT, width=WIDTH, mines=MINES)
ai = MinesweeperAI(height=HEIGHT, width=WIDTH)
# Keep track of revealed cells, flagged cells, and if a mine was hit
revealed = set()
flags = set()
lost = False
# Show instructions initially
instructions = True
while True:
# Check if game quit
for event in pygame.event.get():
if event.type == pygame.QUIT:
sys.exit()
screen.fill(BLACK)
# Show game instructions
if instructions:
# Title
title = largeFont.render("Play Minesweeper", True, WHITE)
titleRect = title.get_rect()
titleRect.center = ((width / 2), 50)
screen.blit(title, titleRect)
# Rules
rules = [
"Click a cell to reveal it.",
"Right-click a cell to mark it as a mine.",
"Mark all mines successfully to win!"
]
for i, rule in enumerate(rules):
line = smallFont.render(rule, True, WHITE)
lineRect = line.get_rect()
lineRect.center = ((width / 2), 150 + 30 * i)
screen.blit(line, lineRect)
# Play game button
buttonRect = pygame.Rect((width / 4), (3 / 4) * height, width / 2, 50)
buttonText = mediumFont.render("Play Game", True, BLACK)
buttonTextRect = buttonText.get_rect()
buttonTextRect.center = buttonRect.center
pygame.draw.rect(screen, WHITE, buttonRect)
screen.blit(buttonText, buttonTextRect)
# Check if play button clicked
click, _, _ = pygame.mouse.get_pressed()
if click == 1:
mouse = pygame.mouse.get_pos()
if buttonRect.collidepoint(mouse):
instructions = False
time.sleep(0.3)
pygame.display.flip()
continue
# Draw board
cells = []
for i in range(HEIGHT):
row = []
for j in range(WIDTH):
# Draw rectangle for cell
rect = pygame.Rect(
board_origin[0] + j * cell_size,
board_origin[1] + i * cell_size,
cell_size, cell_size
)
pygame.draw.rect(screen, GRAY, rect)
pygame.draw.rect(screen, WHITE, rect, 3)
# Add a mine, flag, or number if needed
if game.is_mine((i, j)) and lost:
screen.blit(mine, rect)
elif (i, j) in flags:
screen.blit(flag, rect)
elif (i, j) in revealed:
neighbors = smallFont.render(
str(game.nearby_mines((i, j))),
True, BLACK
)
neighborsTextRect = neighbors.get_rect()
neighborsTextRect.center = rect.center
screen.blit(neighbors, neighborsTextRect)
row.append(rect)
cells.append(row)
# AI Move button
aiButton = pygame.Rect(
(2 / 3) * width + BOARD_PADDING, (1 / 3) * height - 50,
(width / 3) - BOARD_PADDING * 2, 50
)
buttonText = mediumFont.render("AI Move", True, BLACK)
buttonRect = buttonText.get_rect()
buttonRect.center = aiButton.center
pygame.draw.rect(screen, WHITE, aiButton)
screen.blit(buttonText, buttonRect)
# Reset button
resetButton = pygame.Rect(
(2 / 3) * width + BOARD_PADDING, (1 / 3) * height + 20,
(width / 3) - BOARD_PADDING * 2, 50
)
buttonText = mediumFont.render("Reset", True, BLACK)
buttonRect = buttonText.get_rect()
buttonRect.center = resetButton.center
pygame.draw.rect(screen, WHITE, resetButton)
screen.blit(buttonText, buttonRect)
# Display text
text = "Lost" if lost else "Won" if game.mines == flags else ""
text = mediumFont.render(text, True, WHITE)
textRect = text.get_rect()
textRect.center = ((5 / 6) * width, (2 / 3) * height)
screen.blit(text, textRect)
move = None
left, _, right = pygame.mouse.get_pressed()
# Check for a right-click to toggle flagging
if right == 1 and not lost:
mouse = pygame.mouse.get_pos()
for i in range(HEIGHT):
for j in range(WIDTH):
if cells[i][j].collidepoint(mouse) and (i, j) not in revealed:
if (i, j) in flags:
flags.remove((i, j))
else:
flags.add((i, j))
time.sleep(0.2)
elif left == 1:
mouse = pygame.mouse.get_pos()
# If AI button clicked, make an AI move
if aiButton.collidepoint(mouse) and not lost:
move = ai.make_safe_move()
if move is None:
move = ai.make_random_move()
if move is None:
flags = ai.mines.copy()
print("No moves left to make.")
else:
print("No known safe moves, AI making random move.")
else:
print("AI making safe move.")
time.sleep(0.2)
# Reset game state
elif resetButton.collidepoint(mouse):
game = Minesweeper(height=HEIGHT, width=WIDTH, mines=MINES)
ai = MinesweeperAI(height=HEIGHT, width=WIDTH)
revealed = set()
flags = set()
lost = False
continue
# User-made move
elif not lost:
for i in range(HEIGHT):
for j in range(WIDTH):
if (cells[i][j].collidepoint(mouse)
and (i, j) not in flags
and (i, j) not in revealed):
move = (i, j)
# Make move and update AI knowledge
if move:
if game.is_mine(move):
lost = True
else:
nearby = game.nearby_mines(move)
revealed.add(move)
ai.add_knowledge(move, nearby)
pygame.display.flip()
================================================
FILE: week2/heredity/heredity.py
================================================
import csv
import itertools
import sys
PROBS = {
# Unconditional probabilities for having gene
"gene": {
2: 0.01,
1: 0.03,
0: 0.96
},
"trait": {
# Probability of trait given two copies of gene
2: {
True: 0.65,
False: 0.35
},
# Probability of trait given one copy of gene
1: {
True: 0.56,
False: 0.44
},
# Probability of trait given no gene
0: {
True: 0.01,
False: 0.99
}
},
# Mutation probability
"mutation": 0.01
}
def main():
# Check for proper usage
if len(sys.argv) != 2:
sys.exit("Usage: python heredity.py data.csv")
people = load_data(sys.argv[1])
# Keep track of gene and trait probabilities for each person
probabilities = {
person: {
"gene": {
2: 0,
1: 0,
0: 0
},
"trait": {
True: 0,
False: 0
}
}
for person in people
}
# Loop over all sets of people who might have the trait
names = set(people)
for have_trait in powerset(names):
# Check if current set of people violates known information
fails_evidence = any(
(people[person]["trait"] is not None and
people[person]["trait"] != (person in have_trait))
for person in names
)
if fails_evidence:
continue
# Loop over all sets of people who might have the gene
for one_gene in powerset(names):
for two_genes in powerset(names - one_gene):
# Update probabilities with new joint probability
p = joint_probability(people, one_gene, two_genes, have_trait)
update(probabilities, one_gene, two_genes, have_trait, p)
# Ensure probabilities sum to 1
normalize(probabilities)
# Print results
for person in people:
print(f"{person}:")
for field in probabilities[person]:
print(f" {field.capitalize()}:")
for value in probabilities[person][field]:
p = probabilities[person][field][value]
print(f" {value}: {p:.4f}")
def load_data(filename):
"""
Load gene and trait data from a file into a dictionary.
File assumed to be a CSV containing fields name, mother, father, trait.
mother, father must both be blank, or both be valid names in the CSV.
trait should be 0 or 1 if trait is known, blank otherwise.
"""
data = dict()
with open(filename) as f:
reader = csv.DictReader(f)
for row in reader:
name = row["name"]
data[name] = {
"name": name,
"mother": row["mother"] or None,
"father": row["father"] or None,
"trait": (True if row["trait"] == "1" else
False if row["trait"] == "0" else None)
}
return data
def powerset(s):
"""
Return a list of all possible subsets of set s.
"""
s = list(s)
return [
set(s) for s in itertools.chain.from_iterable(
itertools.combinations(s, r) for r in range(len(s) + 1)
)
]
def joint_probability(people, one_gene, two_genes, have_trait):
"""
Compute and return a joint probability.
The probability returned should be the probability that
* everyone in set `one_gene` has one copy of the gene, and
* everyone in set `two_genes` has two copies of the gene, and
* everyone not in `one_gene` or `two_gene` does not have the gene, and
* everyone in set `have_trait` has the trait, and
* everyone not in set` have_trait` does not have the trait.
"""
probability = 1
for person in people:
gene_number = 1 if person in one_gene else 2 if person in two_genes else 0
trait = True if person in have_trait else False
gene_numb_prop = PROBS['gene'][gene_number]
trait_prop = PROBS['trait'][gene_number][trait]
if people[person]['mother'] is None:
# no parents, use probability distribution
probability *= gene_numb_prop * trait_prop
else:
# info about parents is available
mother = people[person]['mother']
father = people[person]['father']
percentages = {}
for ppl in [mother, father]:
number = 1 if ppl in one_gene else 2 if ppl in two_genes else 0
perc = 0 + PROBS['mutation'] if number == 0 else 0.5 if number == 1 else 1 - PROBS['mutation']
percentages[ppl] = perc
if gene_number == 0:
# 0, none of parents gave gene
probability *= (1 - percentages[mother]) * (1 - percentages[father])
elif gene_number == 1:
# 1, one of parents gave gene
probability *= (1 - percentages[mother]) * percentages[father] + percentages[mother] * (1 - percentages[father])
else:
# 2, both of parents gave gene
probability *= percentages[mother] * percentages[father]
probability *= trait_prop
return probability
def update(probabilities, one_gene, two_genes, have_trait, p):
"""
Add to `probabilities` a new joint probability `p`.
Each person should have their "gene" and "trait" distributions updated.
Which value for each distribution is updated depends on whether
the person is in `have_gene` and `have_trait`, respectively.
"""
for person in probabilities:
gene_number = 1 if person in one_gene else 2 if person in two_genes else 0
probabilities[person]["gene"][gene_number] += p
probabilities[person]["trait"][person in have_trait] += p
def normalize(probabilities):
"""
Update `probabilities` such that each probability distribution
is normalized (i.e., sums to 1, with relative proportions the same).
"""
normalized = probabilities.copy()
for person in probabilities:
for typ in ['gene', 'trait']:
summed = sum(probabilities[person][typ].values())
for category in probabilities[person][typ]:
val = probabilities[person][typ][category]
normalized_val = val / summed
normalized[person][typ][category] = normalized_val
return normalized
if __name__ == "__main__":
main()
================================================
FILE: week2/pagerank/pagerank.py
================================================
import os
import random
import re
import sys
DAMPING = 0.85
SAMPLES = 10000
def main():
if len(sys.argv) != 2:
sys.exit("Usage: python pagerank.py corpus")
corpus = crawl(sys.argv[1])
ranks = sample_pagerank(corpus, DAMPING, SAMPLES)
print(f"PageRank Results from Sampling (n = {SAMPLES})")
for page in sorted(ranks):
print(f" {page}: {ranks[page]:.4f}")
ranks = iterate_pagerank(corpus, DAMPING)
print(f"PageRank Results from Iteration")
for page in sorted(ranks):
print(f" {page}: {ranks[page]:.4f}")
def crawl(directory):
"""
Parse a directory of HTML pages and check for links to other pages.
Return a dictionary where each key is a page, and values are
a list of all other pages in the corpus that are linked to by the page.
"""
pages = dict()
# Extract all links from HTML files
for filename in os.listdir(directory):
if not filename.endswith(".html"):
continue
with open(os.path.join(directory, filename)) as f:
contents = f.read()
links = re.findall(r"<a\s+(?:[^>]*?)href=\"([^\"]*)\"", contents)
pages[filename] = set(links) - {filename}
# Only include links to other pages in the corpus
for filename in pages:
pages[filename] = set(
link for link in pages[filename]
if link in pages
)
return pages
def transition_model(corpus, page, damping_factor):
"""
Return a probability distribution over which page to visit next,
given a current page.
With probability `damping_factor`, choose a link at random
linked to by `page`. With probability `1 - damping_factor`, choose
a link at random chosen from all pages in the corpus.
"""
prop_dist = {}
# check if page has outgoing links
dict_len = len(corpus.keys())
pages_len = len(corpus[page])
if len(corpus[page]) < 1:
# no outgoing pages, choosing randomly from all possible pages
for key in corpus.keys():
prop_dist[key] = 1 / dict_len
else:
# there are outgoing pages, calculating distribution
random_factor = (1 - damping_factor) / dict_len
even_factor = damping_factor / pages_len
for key in corpus.keys():
if key not in corpus[page]:
prop_dist[key] = random_factor
else:
prop_dist[key] = even_factor + random_factor
return prop_dist
def sample_pagerank(corpus, damping_factor, n):
"""
Return PageRank values for each page by sampling `n` pages
according to transition model, starting with a page at random.
Return a dictionary where keys are page names, and values are
their estimated PageRank value (a value between 0 and 1). All
PageRank values should sum to 1.
"""
# prepare dictionary with number of samples == 0
samples_dict = corpus.copy()
for i in samples_dict:
samples_dict[i] = 0
sample = None
# itearting n times
for _ in range(n):
if sample:
# previous sample is available, choosing using transition model
dist = transition_model(corpus, sample, damping_factor)
dist_lst = list(dist.keys())
dist_weights = [dist[i] for i in dist]
sample = random.choices(dist_lst, dist_weights, k=1)[0]
else:
# no previous sample, choosing randomly
sample = random.choice(list(corpus.keys()))
# count each sample
samples_dict[sample] += 1
# turn sample count to percentage
for item in samples_dict:
samples_dict[item] /= n
return samples_dict
def iterate_pagerank(corpus, damping_factor):
"""
Return PageRank values for each page by iteratively updating
PageRank values until convergence.
Return a dictionary where keys are page names, and values are
their estimated PageRank value (a value between 0 and 1). All
PageRank values should sum to 1.
"""
pages_number = len(corpus)
old_dict = {}
new_dict = {}
# assigning each page a rank of 1/n, where n is total number of pages in the corpus
for page in corpus:
old_dict[page] = 1 / pages_number
# repeatedly calculating new rank values basing on all of the current rank values
while True:
for page in corpus:
temp = 0
for linking_page in corpus:
# check if page links to our page
if page in corpus[linking_page]:
temp += (old_dict[linking_page] / len(corpus[linking_page]))
# if page has no links, interpret it as having one link for every other page
if len(corpus[linking_page]) == 0:
temp += (old_dict[linking_page]) / len(corpus)
temp *= damping_factor
temp += (1 - damping_factor) / pages_number
new_dict[page] = temp
difference = max([abs(new_dict[x] - old_dict[x]) for x in old_dict])
if difference < 0.001:
break
else:
old_dict = new_dict.copy()
return old_dict
if __name__ == "__main__":
main()
================================================
FILE: week3/crossword/crossword.py
================================================
class Variable():
ACROSS = "across"
DOWN = "down"
def __init__(self, i, j, direction, length):
"""Create a new variable with starting point, direction, and length."""
self.i = i
self.j = j
self.direction = direction
self.length = length
self.cells = []
for k in range(self.length):
self.cells.append(
(self.i + (k if self.direction == Variable.DOWN else 0),
self.j + (k if self.direction == Variable.ACROSS else 0))
)
def __hash__(self):
return hash((self.i, self.j, self.direction, self.length))
def __eq__(self, other):
return (
(self.i == other.i) and
(self.j == other.j) and
(self.direction == other.direction) and
(self.length == other.length)
)
def __str__(self):
return f"({self.i}, {self.j}) {self.direction} : {self.length}"
def __repr__(self):
direction = repr(self.direction)
return f"Variable({self.i}, {self.j}, {direction}, {self.length})"
class Crossword():
def __init__(self, structure_file, words_file):
# Determine structure of crossword
with open(structure_file) as f:
contents = f.read().splitlines()
self.height = len(contents)
self.width = max(len(line) for line in contents)
self.structure = []
for i in range(self.height):
row = []
for j in range(self.width):
if j >= len(contents[i]):
row.append(False)
elif contents[i][j] == "_":
row.append(True)
else:
row.append(False)
self.structure.append(row)
# Save vocabulary list
with open(words_file) as f:
self.words = set(f.read().upper().splitlines())
# Determine variable set
self.variables = set()
for i in range(self.height):
for j in range(self.width):
# Vertical words
starts_word = (
self.structure[i][j]
and (i == 0 or not self.structure[i - 1][j])
)
if starts_word:
length = 1
for k in range(i + 1, self.height):
if self.structure[k][j]:
length += 1
else:
break
if length > 1:
self.variables.add(Variable(
i=i, j=j,
direction=Variable.DOWN,
length=length
))
# Horizontal words
starts_word = (
self.structure[i][j]
and (j == 0 or not self.structure[i][j - 1])
)
if starts_word:
length = 1
for k in range(j + 1, self.width):
if self.structure[i][k]:
length += 1
else:
break
if length > 1:
self.variables.add(Variable(
i=i, j=j,
direction=Variable.ACROSS,
length=length
))
# Compute overlaps for each word
# For any pair of variables v1, v2, their overlap is either:
# None, if the two variables do not overlap; or
# (i, j), where v1's ith character overlaps v2's jth character
self.overlaps = dict()
for v1 in self.variables:
for v2 in self.variables:
if v1 == v2:
continue
cells1 = v1.cells
cells2 = v2.cells
intersection = set(cells1).intersection(cells2)
if not intersection:
self.overlaps[v1, v2] = None
else:
intersection = intersection.pop()
self.overlaps[v1, v2] = (
cells1.index(intersection),
cells2.index(intersection)
)
def neighbors(self, var):
"""Given a variable, return set of overlapping variables."""
return set(
v for v in self.variables
if v != var and self.overlaps[v, var]
)
================================================
FILE: week3/crossword/data/structure0.txt
================================================
#___#
#_##_
#_##_
#_##_
#____
================================================
FILE: week3/crossword/data/structure1.txt
================================================
##############
#######_####_#
#____________#
#_#####_####_#
#_##_____###_#
#_#####_####_#
#_###______#_#
#######_####_#
##############
================================================
FILE: week3/crossword/data/structure2.txt
================================================
######_
____##_
_##____
_##_##_
_##_##_
#___##_
================================================
FILE: week3/crossword/data/words0.txt
================================================
one
two
three
four
five
six
seven
eight
nine
ten
================================================
FILE: week3/crossword/data/words1.txt
================================================
adversarial
alpha
arc
artificial
bayes
beta
bit
breadth
byte
classification
classify
condition
constraint
create
depth
distribution
end
false
graph
heuristic
infer
inference
initial
intelligence
knowledge
language
learning
line
logic
loss
markov
minimax
network
neural
node
optimization
probability
proposition
prune
reason
recurrent
regression
resolution
resolve
satisfaction
search
sine
start
true
truth
uncertainty
================================================
FILE: week3/crossword/data/words2.txt
================================================
a
abandon
ability
able
abortion
about
above
abroad
absence
absolute
absolutely
absorb
abuse
academic
accept
access
accident
accompany
accomplish
according
account
accurate
accuse
achieve
achievement
acid
acknowledge
acquire
across
act
action
active
activist
activity
actor
actress
actual
actually
ad
adapt
add
addition
additional
address
adequate
adjust
adjustment
administration
administrator
admire
admission
admit
adolescent
adopt
adult
advance
advanced
advantage
adventure
advertising
advice
advise
adviser
advocate
affair
affect
afford
afraid
African
African-American
after
afternoon
again
against
age
agency
agenda
agent
aggressive
ago
agree
agreement
agricultural
ah
ahead
aid
aide
AIDS
aim
air
aircraft
airline
airport
album
alcohol
alive
all
alliance
allow
ally
almost
alone
along
already
also
alter
alternative
although
always
AM
amazing
American
among
amount
analysis
analyst
analyze
ancient
and
anger
angle
angry
animal
anniversary
announce
annual
another
answer
anticipate
anxiety
any
anybody
anymore
anyone
anything
anyway
anywhere
apart
apartment
apparent
apparently
appeal
appear
appearance
apple
application
apply
appoint
appointment
appreciate
approach
appropriate
approval
approve
approximately
Arab
architect
area
argue
argument
arise
arm
armed
army
around
arrange
arrangement
arrest
arrival
arrive
art
article
artist
artistic
as
Asian
aside
ask
asleep
aspect
assault
assert
assess
assessment
asset
assign
assignment
assist
assistance
assistant
associate
association
assume
assumption
assure
at
athlete
athletic
atmosphere
attach
attack
attempt
attend
attention
attitude
attorney
attract
attractive
attribute
audience
author
authority
auto
available
average
avoid
award
aware
awareness
away
awful
baby
back
background
bad
badly
bag
bake
balance
ball
ban
band
bank
bar
barely
barrel
barrier
base
baseball
basic
basically
basis
basket
basketball
bathroom
battery
battle
be
beach
bean
bear
beat
beautiful
beauty
because
become
bed
bedroom
beer
before
begin
beginning
behavior
behind
being
belief
believe
bell
belong
below
belt
bench
bend
beneath
benefit
beside
besides
best
bet
better
between
beyond
Bible
big
bike
bill
billion
bind
biological
bird
birth
birthday
bit
bite
black
blade
blame
blanket
blind
block
blood
blow
blue
board
boat
body
bomb
bombing
bond
bone
book
boom
boot
border
born
borrow
boss
both
bother
bottle
bottom
boundary
bowl
box
boy
boyfriend
brain
branch
brand
bread
break
breakfast
breast
breath
breathe
brick
bridge
brief
briefly
bright
brilliant
bring
British
broad
broken
brother
brown
brush
buck
budget
build
building
bullet
bunch
burden
burn
bury
bus
business
busy
but
butter
button
buy
buyer
by
cabin
cabinet
cable
cake
calculate
call
camera
camp
campaign
campus
can
Canadian
cancer
candidate
cap
capability
capable
capacity
capital
captain
capture
car
carbon
card
care
career
careful
carefully
carrier
carry
case
cash
cast
cat
catch
category
Catholic
cause
ceiling
celebrate
celebration
celebrity
cell
center
central
century
CEO
ceremony
certain
certainly
chain
chair
chairman
challenge
chamber
champion
championship
chance
change
changing
channel
chapter
character
characteristic
characterize
charge
charity
chart
chase
cheap
check
cheek
cheese
chef
chemical
chest
chicken
chief
child
childhood
Chinese
chip
chocolate
choice
cholesterol
choose
Christian
Christmas
church
cigarette
circle
circumstance
cite
citizen
city
civil
civilian
claim
class
classic
classroom
clean
clear
clearly
client
climate
climb
clinic
clinical
clock
close
closely
closer
clothes
clothing
cloud
club
clue
cluster
coach
coal
coalition
coast
coat
code
coffee
cognitive
cold
collapse
colleague
collect
collection
collective
college
colonial
color
column
combination
combine
come
comedy
comfort
comfortable
command
commander
comment
commercial
commission
commit
commitment
committee
common
communicate
communication
community
company
compare
comparison
compete
competition
competitive
competitor
complain
complaint
complete
completely
complex
complicated
component
compose
composition
comprehensive
computer
concentrate
concentration
concept
concern
concerned
concert
conclude
conclusion
concrete
condition
conduct
conference
confidence
confident
confirm
conflict
confront
confusion
Congress
congressional
connect
connection
consciousness
consensus
consequence
conservative
consider
considerable
consideration
consist
consistent
constant
constantly
constitute
constitutional
construct
construction
consultant
consume
consumer
consumption
contact
contain
container
contemporary
content
contest
context
continue
continued
contract
contrast
contribute
contribution
control
controversial
controversy
convention
conventional
conversation
convert
conviction
convince
cook
cookie
cooking
cool
cooperation
cop
cope
copy
core
corn
corner
corporate
corporation
correct
correspondent
cost
cotton
couch
could
council
counselor
count
counter
country
county
couple
courage
course
court
cousin
cover
coverage
cow
crack
craft
crash
crazy
cream
create
creation
creative
creature
credit
crew
crime
criminal
crisis
criteria
critic
critical
criticism
criticize
crop
cross
crowd
crucial
cry
cultural
culture
cup
curious
current
currently
curriculum
custom
customer
cut
cycle
dad
daily
damage
dance
danger
dangerous
dare
dark
darkness
data
date
daughter
day
dead
deal
dealer
dear
death
debate
debt
decade
decide
decision
deck
declare
decline
decrease
deep
deeply
deer
defeat
defend
defendant
defense
defensive
deficit
define
definitely
definition
degree
delay
deliver
delivery
demand
democracy
Democrat
democratic
demonstrate
demonstration
deny
department
depend
dependent
depending
depict
depression
depth
deputy
derive
describe
description
desert
deserve
design
designer
desire
desk
desperate
despite
destroy
destruction
detail
detailed
detect
determine
develop
developing
development
device
devote
dialogue
die
diet
differ
difference
different
differently
difficult
difficulty
dig
digital
dimension
dining
dinner
direct
direction
directly
director
dirt
dirty
disability
disagree
disappear
disaster
discipline
discourse
discover
discovery
discrimination
discuss
discussion
disease
dish
dismiss
disorder
display
dispute
distance
distant
distinct
distinction
distinguish
distribute
distribution
district
diverse
diversity
divide
division
divorce
DNA
do
doctor
document
dog
domestic
dominant
dominate
door
double
doubt
down
downtown
dozen
draft
drag
drama
dramatic
dramatically
draw
drawing
dream
dress
drink
drive
driver
drop
drug
dry
due
during
dust
duty
each
eager
ear
early
earn
earnings
earth
ease
easily
east
eastern
easy
eat
economic
economics
economist
economy
edge
edition
editor
educate
education
educational
educator
effect
effective
effectively
efficiency
efficient
effort
egg
eight
either
elderly
elect
election
electric
electricity
electronic
element
elementary
eliminate
elite
else
elsewhere
e-mail
embrace
emerge
emergency
emission
emotion
emotional
emphasis
emphasize
employ
employee
employer
employment
empty
enable
encounter
encourage
end
enemy
energy
enforcement
engage
engine
engineer
engineering
English
enhance
enjoy
enormous
enough
ensure
enter
enterprise
entertainment
entire
entirely
entrance
entry
environment
environmental
episode
equal
equally
equipment
era
error
escape
especially
essay
essential
essentially
establish
establishment
estate
estimate
etc
ethics
ethnic
European
evaluate
evaluation
even
evening
event
eventually
ever
every
everybody
everyday
everyone
everything
everywhere
evidence
evolution
evolve
exact
exactly
examination
examine
example
exceed
excellent
except
exception
exchange
exciting
executive
exercise
exhibit
exhibition
exist
existence
existing
expand
expansion
expect
expectation
expense
expensive
experience
experiment
expert
explain
explanation
explode
explore
explosion
expose
exposure
express
expression
extend
extension
extensive
extent
external
extra
extraordinary
extreme
extremely
eye
fabric
face
facility
fact
factor
factory
faculty
fade
fail
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fair
fairly
faith
fall
false
familiar
family
famous
fan
fantasy
far
farm
farmer
fashion
fast
fat
fate
father
fault
favor
favorite
fear
feature
federal
fee
feed
feel
feeling
fellow
female
fence
few
fewer
fiber
fiction
field
fifteen
fifth
fifty
fight
fighter
fighting
figure
file
fill
film
final
finally
finance
financial
find
finding
fine
finger
finish
fire
firm
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fish
fishing
fit
fitness
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fix
flag
flame
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flavor
flee
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flow
flower
fly
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folk
follow
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force
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forever
forget
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founder
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free
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French
frequency
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friend
friendly
friendship
from
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fruit
frustration
fuel
full
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function
fund
fundamental
funding
funeral
funny
furniture
furthermore
future
gain
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gallery
game
gang
gap
garage
garden
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gas
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gather
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gaze
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gender
gene
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generally
generate
generation
genetic
gentleman
gently
German
gesture
get
ghost
giant
gift
gifted
girl
girlfriend
give
given
glad
glance
glass
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glove
go
goal
God
gold
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golf
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governor
grab
grade
gradually
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grand
grandfather
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grant
grass
grave
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greatest
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grow
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guard
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hero
herself
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horse
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hotel
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hunter
hunting
hurt
husband
hypothesis
I
ice
idea
ideal
identification
identify
identity
ie
if
ignore
ill
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illness
illustrate
image
imagination
imagine
immediate
immediately
immigrant
immigration
impact
implement
implication
imply
importance
important
impose
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impress
impression
impressive
improve
improvement
in
incentive
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include
including
income
incorporate
increase
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increasingly
incredible
indeed
independence
independent
index
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industry
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information
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inquiry
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insist
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instance
instead
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institutional
instruction
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intend
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intensity
intention
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interested
interesting
internal
international
Internet
interpret
interpretation
intervention
interview
into
introduce
introduction
invasion
invest
investigate
investigation
investigator
investment
investor
invite
involve
involved
involvement
Iraqi
Irish
iron
Islamic
island
Israeli
issue
it
Italian
item
its
itself
jacket
jail
Japanese
jet
Jew
Jewish
job
join
joint
joke
journal
journalist
journey
joy
judge
judgment
juice
jump
junior
jury
just
justice
justify
keep
key
kick
kid
kill
killer
killing
kind
king
kiss
kitchen
knee
knife
knock
know
knowledge
lab
label
labor
laboratory
lack
lady
lake
land
landscape
language
lap
large
largely
last
late
later
Latin
latter
laugh
launch
law
lawn
lawsuit
lawyer
lay
layer
lead
leader
leadership
leading
leaf
league
lean
learn
learning
least
leather
leave
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Mrs
Ms
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PM
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porch
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pose
position
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pot
potato
potential
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pour
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power
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pray
prayer
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predict
prefer
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presidential
press
pressure
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pretty
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previous
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pride
priest
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primary
prime
principal
principle
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process
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prominent
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prove
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zone
================================================
FILE: week3/crossword/generate.py
================================================
import sys
import copy
from crossword import *
class CrosswordCreator():
def __init__(self, crossword):
"""
Create new CSP crossword generate.
"""
self.crossword = crossword
self.domains = {
var: self.crossword.words.copy()
for var in self.crossword.variables
}
def letter_grid(self, assignment):
"""
Return 2D array representing a given assignment.
"""
letters = [
[None for _ in range(self.crossword.width)]
for _ in range(self.crossword.height)
]
for variable, word in assignment.items():
direction = variable.direction
for k in range(len(word)):
i = variable.i + (k if direction == Variable.DOWN else 0)
j = variable.j + (k if direction == Variable.ACROSS else 0)
letters[i][j] = word[k]
return letters
def print(self, assignment):
"""
Print crossword assignment to the terminal.
"""
letters = self.letter_grid(assignment)
for i in range(self.crossword.height):
for j in range(self.crossword.width):
if self.crossword.structure[i][j]:
print(letters[i][j] or " ", end="")
else:
print("█", end="")
print()
def save(self, assignment, filename):
"""
Save crossword assignment to an image file.
"""
from PIL import Image, ImageDraw, ImageFont
cell_size = 100
cell_border = 2
interior_size = cell_size - 2 * cell_border
letters = self.letter_grid(assignment)
# Create a blank canvas
img = Image.new(
"RGBA",
(self.crossword.width * cell_size,
self.crossword.height * cell_size),
"black"
)
font = ImageFont.truetype("assets/fonts/OpenSans-Regular.ttf", 80)
draw = ImageDraw.Draw(img)
for i in range(self.crossword.height):
for j in range(self.crossword.width):
rect = [
(j * cell_size + cell_border,
i * cell_size + cell_border),
((j + 1) * cell_size - cell_border,
(i + 1) * cell_size - cell_border)
]
if self.crossword.structure[i][j]:
draw.rectangle(rect, fill="white")
if letters[i][j]:
w, h = draw.textsize(letters[i][j], font=font)
draw.text(
(rect[0][0] + ((interior_size - w) / 2),
rect[0][1] + ((interior_size - h) / 2) - 10),
letters[i][j], fill="black", font=font
)
img.save(filename)
def solve(self):
"""
Enforce node and arc consistency, and then solve the CSP.
"""
self.enforce_node_consistency()
self.ac3()
return self.backtrack(dict())
def enforce_node_consistency(self):
"""
Update `self.domains` such that each variable is node-consistent.
(Remove any values that are inconsistent with a variable's unary
constraints; in this case, the length of the word.)
"""
# do the deep copy of domains
domain_copy = copy.deepcopy(self.domains)
# iterate through domains copy
for variable in domain_copy:
# getting the variable length
length = variable.length
# iterate through words in domain
for word in domain_copy[variable]:
if len(word) != length:
# if length of the word doesn't fit variable, delete it from
# the original domain (not copy)
self.domains[variable].remove(word)
def revise(self, x, y):
"""
Make variable `x` arc consistent with variable `y`.
To do so, remove values from `self.domains[x]` for which there is no
possible corresponding value for `y` in `self.domains[y]`.
Return True if a revision was made to the domain of `x`; return
False if no revision was made.
"""
# getting x and y ovelapping cells, unpack cords to variables
xoverlap, yoverlap = self.crossword.overlaps[x, y]
# make variable describing if revision was made
revision_made = False
# making domains copy
domains_copy = copy.deepcopy(self.domains)
# if overlap occurs
if xoverlap:
# iterate through words in x's domain
for xword in domains_copy[x]:
matched_value = False
# iterate through words in y's domain
for yword in self.domains[y]:
# if x's word and y's word have same letter in overlapping position
if xword[xoverlap] == yword[yoverlap]:
matched_value = True
break # no need to check rest of y's words for that x
if matched_value:
continue # if x and y was matched, proceed with another x
else:
self.domains[x].remove(xword) # no matching y's word to x, removing word from domain
revision_made = True
# return bolean if revision was made
return revision_made
def ac3(self, arcs=None):
"""
Update `self.domains` such that each variable is arc consistent.
If `arcs` is None, begin with initial list of all arcs in the problem.
Otherwise, use `arcs` as the initial list of arcs to make consistent.
Return True if arc consistency is enforced and no domains are empty;
return False if one or more domains end up empty.
"""
if not arcs:
# no arcs provided, start with an initial queue of all of the arcs in the problem
queue = []
# populating queue
for variable1 in self.domains:
for variable2 in self.crossword.neighbors(variable1):
if self.crossword.overlaps[variable1, variable2] is not None:
queue.append((variable1, variable2))
while len(queue) > 0:
x, y = queue.pop(0)
if self.revise(x, y):
if len(self.domains[x]) == 0:
return False
for neighbour in self.crossword.neighbors(x):
if neighbour != y:
queue.append((neighbour, x))
return True
def assignment_complete(self, assignment):
"""
Return True if `assignment` is complete (i.e., assigns a value to each
crossword variable); return False otherwise.
"""
for variable in self.domains:
if variable not in assignment:
return False
return True
def consistent(self, assignment):
"""
Return True if `assignment` is consistent (i.e., words fit in crossword
puzzle without conflicting characters); return False otherwise.
"""
# all values are distinct, every value is the correct length,
# and there are no conflicts between neighboring variables.
# check if all values are distinct
words = [*assignment.values()]
if len(words) != len(set(words)):
return False
# check if every value is the correct length
for variable in assignment:
if variable.length != len(assignment[variable]):
return False
# check if there are any conflicts between neighbouring variables
for variable in assignment:
for neighbour in self.crossword.neighbors(variable):
if neighbour in assignment:
x, y = self.crossword.overlaps[variable, neighbour]
if assignment[variable][x] != assignment[neighbour][y]:
return False
# all cases checked, no conflicts, can return True
return True
def order_domain_values(self, var, assignment):
"""
Return a list of values in the domain of `var`, in order by
the number of values they rule out for neighboring variables.
The first value in the list, for example, should be the one
that rules out the fewest values among the neighbors of `var`.
"""
# make temporary dict for holding values
word_dict = {}
# getting neighbours of var
neighbours = self.crossword.neighbors(var)
# iterating through var's words
for word in self.domains[var]:
eliminated = 0
for neighbour in neighbours:
# don't count if neighbor has already assigned value
if neighbour in assignment:
continue
else:
# calculate overlap between two variables
xoverlap, yoverlap = self.crossword.overlaps[var, neighbour]
for neighbour_word in self.domains[neighbour]:
# iterate through neighbour's words, check for eliminate ones
if word[xoverlap] != neighbour_word[yoverlap]:
eliminated += 1
# add eliminated neighbour's words to temporary dict
word_dict[word] = eliminated
# sort variables dictionary by number of eliminated neighbour values
sorted_dict = {k: v for k, v in sorted(word_dict.items(), key=lambda item: item[1])}
return [*sorted_dict]
def select_unassigned_variable(self, assignment):
"""
Return an unassigned variable not already part of `assignment`.
Choose the variable with the minimum number of remaining values
in its domain. If there is a tie, choose the variable with the highest
degree. If there is a tie, any of the tied variables are acceptable
return values.
"""
choice_dict = {}
# iterating through variables in domains
for variable in self.domains:
# iterating through variables in assignment
if variable not in assignment:
# if variable is not yet in assigment, add it to temp dict
choice_dict[variable] = self.domains[variable]
# make list of variables sorted by number of remaining values
sorted_list = [v for v, k in sorted(choice_dict.items(), key=lambda item:len(item[1]))]
# return variable with the minimum number of remaining values
return sorted_list[0]
def backtrack(self, assignment):
"""
Using Backtracking Search, take as input a partial assignment for the
crossword and return a complete assignment if possible to do so.
`assignment` is a mapping from variables (keys) to words (values).
If no assignment is possible, return None.
"""
# if assignment is already ready
if len(assignment) == len(self.domains):
return assignment
# selecting one of unassigned variables
variable = self.select_unassigned_variable(assignment)
# iterating through words in that variable
for value in self.domains[variable]:
# making assignment copy, with updated variable value
assignment_copy = assignment.copy()
assignment_copy[variable] = value
# checking for consistency, getting result of that new assignment backtrack
if self.consistent(assignment_copy):
result = self.backtrack(assignment_copy)
if result is not None:
return result
return None
def main():
# Check usage
if len(sys.argv) not in [3, 4]:
sys.exit("Usage: python generate.py structure words [output]")
# Parse command-line arguments
structure = sys.argv[1]
words = sys.argv[2]
output = sys.argv[3] if len(sys.argv) == 4 else None
# Generate crossword
crossword = Crossword(structure, words)
creator = CrosswordCreator(crossword)
assignment = creator.solve()
# Print result
if assignment is None:
print("No solution.")
else:
creator.print(assignment)
if output:
creator.save(assignment, output)
if __name__ == "__main__":
main()
================================================
FILE: week4/nim/nim.py
================================================
import math
import random
import time
class Nim():
def __init__(self, initial=[1, 3, 5, 7]):
"""
Initialize game board.
Each game board has
- `piles`: a list of how many elements remain in each pile
- `player`: 0 or 1 to indicate which player's turn
- `winner`: None, 0, or 1 to indicate who the winner is
"""
self.piles = initial.copy()
self.player = 0
self.winner = None
@classmethod
def available_actions(cls, piles):
"""
Nim.available_actions(piles) takes a `piles` list as input
and returns all of the available actions `(i, j)` in that state.
Action `(i, j)` represents the action of removing `j` items
from pile `i` (where piles are 0-indexed).
"""
actions = set()
for i, pile in enumerate(piles):
for j in range(1, pile + 1):
actions.add((i, j))
return actions
@classmethod
def other_player(cls, player):
"""
Nim.other_player(player) returns the player that is not
`player`. Assumes `player` is either 0 or 1.
"""
return 0 if player == 1 else 1
def switch_player(self):
"""
Switch the current player to the other player.
"""
self.player = Nim.other_player(self.player)
def move(self, action):
"""
Make the move `action` for the current player.
`action` must be a tuple `(i, j)`.
"""
pile, count = action
# Check for errors
if self.winner is not None:
raise Exception("Game already won")
elif pile < 0 or pile >= len(self.piles):
raise Exception("Invalid pile")
elif count < 1 or count > self.piles[pile]:
raise Exception("Invalid number of objects")
# Update pile
self.piles[pile] -= count
self.switch_player()
# Check for a winner
if all(pile == 0 for pile in self.piles):
self.winner = self.player
class NimAI():
def __init__(self, alpha=0.5, epsilon=0.1):
"""
Initialize AI with an empty Q-learning dictionary,
an alpha (learning) rate, and an epsilon rate.
The Q-learning dictionary maps `(state, action)`
pairs to a Q-value (a number).
- `state` is a tuple of remaining piles, e.g. (1, 1, 4, 4)
- `action` is a tuple `(i, j)` for an action
"""
self.q = dict()
self.alpha = alpha
self.epsilon = epsilon
def update(self, old_state, action, new_state, reward):
"""
Update Q-learning model, given an old state, an action taken
in that state, a new resulting state, and the reward received
from taking that action.
"""
old = self.get_q_value(old_state, action)
best_future = self.best_future_reward(new_state)
self.update_q_value(old_state, action, old, reward, best_future)
def get_q_value(self, state, action):
"""
Return the Q-value for the state `state` and the action `action`.
If no Q-value exists yet in `self.q`, return 0.
"""
try:
return self.q[tuple(state), action]
except KeyError:
return 0
def update_q_value(self, state, action, old_q, reward, future_rewards):
"""
Update the Q-value for the state `state` and the action `action`
given the previous Q-value `old_q`, a current reward `reward`,
and an estiamte of future rewards `future_rewards`.
Use the formula:
Q(s, a) <- old value estimate
+ alpha * (new value estimate - old value estimate)
where `old value estimate` is the previous Q-value,
`alpha` is the learning rate, and `new value estimate`
is the sum of the current reward and estimated future rewards.
"""
new_q = old_q + self.alpha * ((reward + future_rewards) - old_q)
self.q[tuple(state), action] = new_q
def best_future_reward(self, state):
"""
Given a state `state`, consider all possible `(state, action)`
pairs available in that state and return the maximum of all
of their Q-values.
Use 0 as the Q-value if a `(state, action)` pair has no
Q-value in `self.q`. If there are no available actions in
`state`, return 0.
"""
max_reward = 0
for sta, q in self.q.items():
if sta[0] == state and q > max_reward:
max_reward = q
return max_reward
def choose_action(self, state, epsilon=True):
"""
Given a state `state`, return an action `(i, j)` to take.
If `epsilon` is `False`, then return the best action
available in the state (the one with the highest Q-value,
using 0 for pairs that have no Q-values).
If `epsilon` is `True`, then with probability
`self.epsilon` choose a random available action,
otherwise choose the best action available.
If multiple actions have the same Q-value, any of those
options is an acceptable return value.
"""
max_reward = 0
best_action = None
available_moves = Nim.available_actions(state)
for move in available_moves:
try:
q = self.q[tuple(state), move]
except KeyError:
q = 0
if q > max_reward:
max_reward = q
best_action = move
if max_reward == 0:
return random.choice(tuple(available_moves))
if not epsilon:
return best_action
else:
if random.random() < self.epsilon:
return random.choice(tuple(available_moves))
else:
return best_action
def train(n):
"""
Train an AI by playing `n` games against itself.
"""
player = NimAI()
# Play n games
for i in range(n):
print(f"Playing training game {i + 1}")
game = Nim()
# Keep track of last move made by either player
last = {
0: {"state": None, "action": None},
1: {"state": None, "action": None}
}
# Game loop
while True:
# Keep track of current state and action
state = game.piles.copy()
action = player.choose_action(game.piles)
# Keep track of last state and action
last[game.player]["state"] = state
last[game.player]["action"] = action
# Make move
game.move(action)
new_state = game.piles.copy()
# When game is over, update Q values with rewards
if game.winner is not None:
player.update(state, action, new_state, -1)
player.update(
last[game.player]["state"],
last[game.player]["action"],
new_state,
1
)
break
# If game is continuing, no rewards yet
elif last[game.player]["state"] is not None:
player.update(
last[game.player]["state"],
last[game.player]["action"],
new_state,
0
)
print("Done training")
# Return the trained AI
return player
def play(ai, human_player=None):
"""
Play human game against the AI.
`human_player` can be set to 0 or 1 to specify whether
human player moves first or second.
"""
# If no player order set, choose human's order randomly
if human_player is None:
human_player = random.randint(0, 1)
# Create new game
game = Nim()
# Game loop
while True:
# Print contents of piles
print()
print("Piles:")
for i, pile in enumerate(game.piles):
print(f"Pile {i}: {pile}")
print()
# Compute available actions
available_actions = Nim.available_actions(game.piles)
time.sleep(1)
# Let human make a move
if game.player == human_player:
print("Your Turn")
while True:
pile = int(input("Choose Pile: "))
count = int(input("Choose Count: "))
if (pile, count) in available_actions:
break
print("Invalid move, try again.")
# Have AI make a move
else:
print("AI's Turn")
pile, count = ai.choose_action(game.piles, epsilon=False)
print(f"AI chose to take {count} from pile {pile}.")
# Make move
game.move((pile, count))
# Check for winner
if game.winner is not None:
print()
print("GAME OVER")
winner = "Human" if game.winner == human_player else "AI"
print(f"Winner is {winner}")
return
================================================
FILE: week4/nim/play.py
================================================
from nim import train, play
ai = train(10000)
play(ai)
================================================
FILE: week4/shopping/shopping.csv
================================================
Administrative,Administrative_Duration,Informational,Informational_Duration,ProductRelated,ProductRelated_Duration,BounceRates,ExitRates,PageValues,SpecialDay,Month,OperatingSystems,Browser,Region,TrafficType,VisitorType,Weekend,Revenue
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0,0,0,0,6,98,0,0.066666667,0,0,Feb,2,5,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,68,0,0.1,0,0,Feb,3,2,3,3,Returning_Visitor,FALSE,FALSE
2,53,0,0,23,1668.285119,0.008333333,0.016312636,0,0,Feb,1,1,9,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Feb,1,1,4,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,13,334.9666667,0,0.007692308,0,0,Feb,1,1,1,4,Returning_Visitor,TRUE,FALSE
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0,0,0,0,20,2981.166667,0,0.01,0,0,Feb,2,4,4,4,Returning_Visitor,FALSE,FALSE
0,0,0,0,8,136.1666667,0,0.008333333,0,1,Feb,2,2,5,1,Returning_Visitor,TRUE,FALSE
0,0,0,0,2,0,0.2,0.2,0,0,Feb,3,3,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,105,0,0.033333333,0,0,Feb,3,2,1,5,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,15,0,0.1,0,0.8,Feb,2,4,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Feb,2,2,4,1,Returning_Visitor,TRUE,FALSE
0,0,0,0,5,156,0,0.04,0,0,Feb,1,1,9,3,Returning_Visitor,FALSE,FALSE
4,64.6,0,0,32,1135.444444,0.002857143,0.00952381,0,0,Feb,2,2,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,76,0.05,0.1,0,0,Feb,1,1,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,63,0,0.05,0,0.2,Feb,2,6,1,3,Returning_Visitor,FALSE,FALSE
1,6,1,0,45,1582.75,0.043478261,0.050821256,54.17976426,0.4,Feb,3,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,35,0,0.1,0,0,Feb,1,1,6,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,78,0,0.066666667,0,0,Feb,1,2,6,6,Returning_Visitor,TRUE,FALSE
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0,0,0,0,10,183.6666667,0.04,0.08,0,0,Feb,1,1,3,1,Returning_Visitor,FALSE,FALSE
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0,0,0,0,52,2086.242857,0.015384615,0.020352564,0,0,Feb,2,2,7,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,8,388,0.025,0.05625,0,0,Feb,3,2,1,4,Returning_Visitor,TRUE,FALSE
2,18,0,0,5,298,0,0.028571429,0,0.8,Feb,2,2,8,4,Returning_Visitor,FALSE,FALSE
0,0,0,0,7,63,0.028571429,0.071428571,0,0.6,Feb,2,2,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,9,482,0,0.022222222,0,0,Feb,2,5,1,6,Returning_Visitor,FALSE,FALSE
1,9,0,0,46,4084.393939,0,0.001794872,0,0,Feb,2,2,8,4,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,22,0,0.066666667,0,0.6,Feb,1,1,3,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,15,310.1666667,0,0.006666667,0,0,Feb,1,1,4,4,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,34,0,0.05,0,0.4,Feb,3,2,2,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,88,0,0.05,0,0,Feb,4,1,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,22,622.25,0.003030303,0.006060606,0,0.2,Feb,2,5,1,4,Returning_Visitor,FALSE,FALSE
0,0,0,0,14,222.4,0.017142857,0.057142857,0,0,Feb,1,1,1,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,80,0.066666667,0.133333333,0,0.2,Feb,3,2,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,11,800.8333333,0,0.003636364,0,0,Feb,3,2,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0.6,Feb,2,2,3,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Feb,1,1,3,4,Returning_Visitor,TRUE,FALSE
0,0,0,0,12,265.1666667,0.011111111,0.026111111,0,0.2,Feb,3,2,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,29,0,0.1,0,1,Feb,2,4,4,2,Returning_Visitor,TRUE,FALSE
0,0,0,0,4,160,0,0.075,0,0,Feb,4,2,2,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,135.6666667,0.05,0.025,0,0.4,Feb,3,3,1,4,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0.2,Feb,2,4,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0.6,Feb,3,2,3,3,Returning_Visitor,FALSE,FALSE
4,56,2,120,36,998.7416667,0,0.014736467,19.44707913,0.2,Feb,2,2,4,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,104,0,0.05,0,0.4,Feb,2,6,6,3,Returning_Visitor,FALSE,FALSE
2,16,0,0,16,381.6865079,0.011764706,0.046568627,0,0.6,Feb,2,4,2,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,6,169,0,0.016666667,0,0.4,Feb,1,1,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,8,400.8,0.05,0.120833333,0,0,Feb,1,1,1,3,Returning_Visitor,FALSE,FALSE
12,279.4166667,0,0,42,1553.583333,0.009,0.019666667,38.30849268,0,Feb,1,1,3,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,14,706.5,0,0.007142857,0,0,Feb,2,2,5,4,Returning_Visitor,TRUE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Feb,2,2,4,3,Returning_Visitor,FALSE,FALSE
3,87.83333333,0,0,27,798.3333333,0,0.012643678,22.9160357,0.8,Feb,2,2,3,1,Returning_Visitor,FALSE,TRUE
4,44,0,0,90,6951.972222,0.002150538,0.015013034,0,0,Feb,4,1,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0.6,Feb,2,2,5,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,18,902,0,0.007407407,0,0,Feb,2,7,2,4,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0.2,Feb,3,2,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Feb,2,6,1,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,20,197.3777778,0.025,0.0525,0,0,Feb,2,6,6,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,43,0,0.1,0,0.4,Feb,2,2,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,8,426.6666667,0,0.0125,0,0,Feb,2,4,3,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,135,0,0.066666667,0,0,Feb,2,4,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,16,588.3333333,0,0.025,0,0,Feb,2,4,1,1,Returning_Visitor,FALSE,FALSE
10,1005.666667,0,0,36,2111.341667,0.004347826,0.014492754,11.43941195,0,Feb,2,6,1,2,Returning_Visitor,FALSE,TRUE
0,0,0,0,2,76,0,0.05,0,0.6,Feb,3,2,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,1,Feb,1,1,1,3,Returning_Visitor,TRUE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0.4,Feb,1,1,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,7,208,0,0.028571429,0,0,Feb,4,1,1,5,Returning_Visitor,TRUE,FALSE
0,0,0,0,4,270,0,0.016666667,0,0.8,Feb,1,1,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,6,39.5,0,0.02,0,0,Feb,2,2,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,12,375,0.016666667,0.058333333,0,0,Feb,3,2,4,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0.8,Feb,2,2,2,1,Returning_Visitor,TRUE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Feb,1,1,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,7,150,0.057142857,0.085714286,0,0,Feb,2,2,2,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,138,0,0.066666667,0,0,Feb,1,1,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,7,337.5,0.028571429,0.023809524,0,0.4,Feb,4,1,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,19,620.0333333,0,0.007894737,0,0,Feb,1,1,4,2,Returning_Visitor,FALSE,FALSE
2,36,0,0,15,168.8461538,0,0.011764706,0,0.4,Feb,1,1,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Feb,1,1,1,2,Returning_Visitor,TRUE,FALSE
0,0,0,0,2,52,0,0.1,0,0,Feb,1,1,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,13,649.25,0,0.015384615,0,0,Feb,2,2,1,5,New_Visitor,FALSE,FALSE
0,0,0,0,27,925.3333333,0.003703704,0.025925926,0,0.6,Feb,4,1,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,33,0,0.1,0,0.2,Feb,1,1,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,6,1566.5,0.05,0.066666667,0,0.2,Feb,1,1,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,105,0,0.025,0,0.6,Feb,1,1,1,4,Returning_Visitor,FALSE,FALSE
0,0,1,0,7,50,0.038095238,0.080952381,0,0.6,Feb,2,4,1,7,Returning_Visitor,FALSE,FALSE
0,0,0,0,16,644.2,0.004166667,0.031666667,0,0,Feb,3,2,3,4,Returning_Visitor,FALSE,FALSE
3,18.33333333,0,0,38,2635.177778,0,0.008947368,0,0.4,Feb,2,4,1,2,Returning_Visitor,FALSE,FALSE
4,61,0,0,19,607,0,0.026984127,17.53595893,1,Feb,1,1,7,4,Returning_Visitor,TRUE,TRUE
0,0,0,0,6,415,0,0.033333333,0,0.4,Feb,1,1,3,2,Returning_Visitor,FALSE,FALSE
2,31,1,16,36,2083.530952,0,0.01351025,0,0.8,Feb,2,2,4,3,Returning_Visitor,FALSE,FALSE
3,58.5,0,0,17,281.6666667,0.007058824,0.017647059,0,0,Feb,1,1,3,4,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,27,0.15,0.15,0,0,Feb,1,1,7,2,Returning_Visitor,FALSE,FALSE
0,0,1,0,9,215,0.044444444,0.074074074,0,0.8,Feb,4,1,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,12,162,0.05,0.066666667,0,0,Feb,1,1,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,114,0.05,0.066666667,0,0.8,Feb,3,3,1,3,Returning_Visitor,FALSE,FALSE
6,326.25,4,94,128,5062.213753,0.000854701,0.01791847,0,0,Feb,2,5,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,253,0,0.016666667,0,0.6,Feb,2,2,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,0,0.2,0.2,0,0.4,Feb,2,2,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0.8,Feb,1,1,2,3,Returning_Visitor,FALSE,FALSE
2,22,0,0,25,436.5,0.008,0.024,0,0.2,Feb,2,4,1,1,Returning_Visitor,FALSE,FALSE
0,0,1,93,30,1045.833333,0.012903226,0.035483871,0,0.2,Feb,1,1,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,12,317.8333333,0,0.005555556,0,0,Feb,1,1,1,4,Returning_Visitor,TRUE,FALSE
0,0,0,0,21,1146.333333,0,0.012962963,0,0.8,Feb,3,2,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,11,577,0.018181818,0.027272727,0,0.2,Feb,2,2,3,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,8,95,0,0.075,0,0,Feb,4,1,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,6,301.5,0,0.111111111,0,0,Feb,2,4,9,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,6,243,0,0.033333333,0,0,Feb,2,4,4,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,135.5,0,0.05,0,0.6,Feb,2,2,1,2,Returning_Visitor,FALSE,FALSE
0,0,2,75,14,442.3333333,0,0.034375,0,0.8,Feb,1,1,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,41,0,0.066666667,0,0,Feb,1,1,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,11,292.9,0.028,0.11952381,0,0,Feb,2,4,3,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Feb,1,1,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,9,1238.333333,0,0.040740741,0,0.4,Feb,2,2,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,10,225.4666667,0,0.05,0,0.4,Feb,1,1,8,3,Returning_Visitor,FALSE,FALSE
4,462,0,0,51,1873.216667,0,0.00754717,0,0.6,Feb,2,2,9,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,13,0.133333333,0.166666667,0,0,Feb,2,4,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,222,0,0.1,0,0,Feb,2,6,1,2,Returning_Visitor,TRUE,FALSE
2,20,0,0,16,214.8333333,0,0.022222222,0,0,Feb,2,2,1,6,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Feb,3,2,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,6,2017.166667,0,0.011111111,0,0.8,Feb,2,2,4,3,Returning_Visitor,FALSE,FALSE
6,111.5,0,0,26,449.0277778,0,0.018518519,0,0.6,Feb,1,1,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,6,158.1666667,0,0.033333333,0,0,Feb,3,2,4,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,9,303.6666667,0.005555556,0.046296296,0,0,Feb,2,4,5,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,25,0,0.066666667,0,0,Feb,2,4,1,5,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,42,0.05,0.15,0,0.4,Feb,2,2,1,4,Returning_Visitor,FALSE,FALSE
4,103.625,0,0,14,1003.416667,0,0.018039216,0,0.2,Feb,1,1,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Feb,2,2,7,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,9,272.5,0,0.011851852,0,0.2,Feb,1,1,6,3,Returning_Visitor,FALSE,FALSE
3,19,0,0,8,344,0,0.007407407,0,0,Feb,2,4,2,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Feb,2,2,2,3,Returning_Visitor,FALSE,FALSE
0,0,1,19,10,852,0,0.009090909,0,0,Feb,2,2,3,6,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,780,0.066666667,0.066666667,0,0.4,Feb,2,4,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,1038,0,0.033333333,0,0,Feb,2,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,573,0,0.05,0,0,Feb,2,2,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,28,1231.233333,0.007142857,0.030357143,0,0,Feb,1,1,4,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,11,316.6666667,0,0.027272727,0,0.8,Feb,2,2,2,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,20,873.7365079,0.0075,0.028166667,0,0,Feb,1,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0.4,Feb,2,2,3,4,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,16,0.1,0.15,0,0,Feb,2,5,5,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,19,615,0,0.026315789,0,0.2,Feb,2,2,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,9,261.75,0,0.026666667,0,0,Feb,2,6,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,21,615.8831169,0.033333333,0.04993081,0,0,Feb,3,2,2,1,Returning_Visitor,TRUE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Feb,3,3,3,2,Returning_Visitor,TRUE,FALSE
0,0,0,0,6,117.5,0,0.033333333,0,0.8,Feb,1,1,1,3,Returning_Visitor,TRUE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Feb,1,1,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Feb,3,2,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,23,501.6666667,0.008695652,0.01884058,0,0.6,Feb,1,1,4,2,Returning_Visitor,FALSE,FALSE
2,58,2,22,31,829.1666667,0.03030303,0.040606061,0,0,Feb,1,1,1,1,Returning_Visitor,TRUE,FALSE
1,9.5,0,0,23,1223,0.015217391,0.012463768,0,0,Feb,1,1,1,2,Returning_Visitor,TRUE,FALSE
0,0,0,0,6,467,0,0.016666667,0,0.4,Feb,1,1,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,23,737.1666667,0.008695652,0.011594203,0,0.6,Feb,2,2,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,12,129,0,0.033333333,0,0,Feb,1,1,3,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,5,63,0,0.04,0,0,Feb,2,2,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,5,125,0.086666667,0.166666667,0,0,Feb,2,2,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,11,684.3333333,0.018181818,0.063636364,0,0,Feb,2,4,6,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,20,665.4722222,0,0.0145,0,0.8,Feb,3,2,7,4,Returning_Visitor,TRUE,FALSE
1,0,0,0,15,487.5,0,0.019166667,0,0.8,Feb,1,1,2,4,Returning_Visitor,TRUE,FALSE
0,0,0,0,17,437.1666667,0.011111111,0.033333333,0,0,Feb,2,4,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,55,0.066666667,0.1,0,0.6,Feb,1,1,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0.8,Feb,1,1,1,2,Returning_Visitor,TRUE,FALSE
5,41.3,0,0,24,446.9277778,0,0.008602151,0,1,Feb,2,2,8,1,Returning_Visitor,TRUE,FALSE
3,87,0,0,10,320.5,0,0.015384615,0,0,Feb,1,1,2,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,7,666,0,0.014285714,0,0,Feb,1,1,6,2,Returning_Visitor,FALSE,FALSE
1,0,0,0,21,405.7095238,0.010743802,0.047002635,0,0,Feb,1,1,1,4,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Feb,3,2,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,6,163.25,0.033333333,0.033333333,0,0.6,Feb,1,1,6,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,17,284.25,0,0.011764706,0,0,Feb,3,2,6,2,Returning_Visitor,TRUE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0.6,Feb,4,2,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Feb,2,4,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,8,260,0.008333333,0.025,0,0.8,Feb,3,2,1,3,Returning_Visitor,TRUE,FALSE
0,0,16,1210.397619,5,279.8571429,0.003174603,0.012764202,0,0,Mar,2,2,1,8,Returning_Visitor,FALSE,FALSE
0,0,0,0,20,927.45,0.011111111,0.027248677,8.000740741,0,Mar,1,1,3,1,Returning_Visitor,FALSE,FALSE
2,9,0,0,50,836.8,0,0.006339869,0,0,Mar,2,2,3,2,Returning_Visitor,FALSE,FALSE
10,293.7782051,2,153,96,3283.166739,0.001960784,0.013509414,0,0,Mar,3,2,6,2,Returning_Visitor,TRUE,FALSE
9,111.5,1,48.5,49,1868.819697,0,0.020708874,1.706014966,0,Mar,2,2,7,2,Returning_Visitor,FALSE,TRUE
3,47,1,51,68,3008.124108,0.007142857,0.016727891,46.53017511,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,0,0.2,0.2,0,0,Mar,1,1,1,3,Returning_Visitor,FALSE,FALSE
3,1226,5,3,24,3230.25,0.036190476,0.096,0,0,Mar,2,2,1,2,Returning_Visitor,FALSE,FALSE
3,52,0,0,9,319,0,0.02,0,0,Mar,1,1,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,42,0,0.066666667,0,0,Mar,2,2,3,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,22,354.3333333,0.009090909,0.057662338,0,0,Mar,1,1,7,2,Returning_Visitor,TRUE,FALSE
0,0,0,0,98,3556.61241,0.002061856,0.010173465,0,0,Mar,1,1,1,3,Returning_Visitor,FALSE,FALSE
2,56,1,144,67,2563.783333,0,0.005797101,19.34265017,0,Mar,2,2,4,2,New_Visitor,FALSE,TRUE
3,112.9607843,0,0,13,3014.018519,0.013068182,0.06140625,0,0,Mar,2,2,1,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,17,840.2333333,0,0.001666667,109.176,0,Mar,2,2,9,2,New_Visitor,FALSE,TRUE
3,94,2,125,55,1970.844805,0,0.001724138,96.25511582,0,Mar,2,4,1,2,New_Visitor,TRUE,TRUE
1,32,0,0,50,2867,0,0.004,153.4432478,0,Mar,2,2,7,8,Returning_Visitor,TRUE,TRUE
0,0,0,0,5,43,0,0.04,0,0,Mar,1,1,1,9,Returning_Visitor,TRUE,FALSE
5,218,0,0,13,284.5,0,0.004166667,0,0,Mar,1,1,1,2,New_Visitor,FALSE,FALSE
0,0,0,0,3,133.5,0,0.088888889,0,0,Mar,1,2,1,8,Returning_Visitor,FALSE,FALSE
1,119,0,0,12,297.6666667,0,0.008333333,0,0,Mar,3,2,1,10,Returning_Visitor,FALSE,FALSE
3,281,0,0,16,453.75,0,0.005263158,0,0,Mar,2,2,5,2,New_Visitor,FALSE,FALSE
1,18,0,0,16,1331.75,0,0.0125,33.79956701,0,Mar,2,5,2,3,New_Visitor,FALSE,TRUE
2,40,0,0,5,558.5,0,0.028571429,0,0,Mar,2,2,7,2,New_Visitor,TRUE,FALSE
3,107,0,0,4,145.8333333,0,0.016666667,0,0,Mar,3,2,7,1,New_Visitor,FALSE,FALSE
0,0,0,0,8,731,0,0.04375,0,0,Mar,2,4,1,3,Returning_Visitor,FALSE,FALSE
2,49,1,127,4,188,0.033333333,0.0375,0,0,Mar,3,2,3,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,14,565.3333333,0.037619048,0.04952381,0,0,Mar,2,6,3,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,50,0,0.05,0,0,Mar,3,2,8,11,Returning_Visitor,FALSE,FALSE
4,57,0,0,7,591,0.006666667,0.033333333,0,0,Mar,1,2,6,6,Returning_Visitor,TRUE,FALSE
2,2,3,261,10,281,0,0.042857143,0,0,Mar,2,2,1,2,Returning_Visitor,FALSE,FALSE
2,123,2,306.3333333,18,483.8333333,0,0.02,0,0,Mar,2,2,4,1,Returning_Visitor,FALSE,FALSE
2,118,0,0,4,42,0,0.066666667,0,0,Mar,1,2,7,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,35,1192.386111,0.005714286,0.028571429,0,0,Mar,2,4,2,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,12,198,0.016666667,0.075,0,0,Mar,2,2,3,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,15,0,0.066666667,0,0,Mar,2,4,3,12,Returning_Visitor,FALSE,FALSE
2,38,0,0,14,643,0,0.013333333,35.0928,0,Mar,2,2,5,1,Returning_Visitor,FALSE,TRUE
0,0,0,0,5,23,0.08,0.12,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,14,0.1,0.15,0,0,Mar,3,2,1,1,Returning_Visitor,FALSE,FALSE
1,54,0,0,6,210.5,0,0.02,0,0,Mar,2,2,1,8,New_Visitor,FALSE,FALSE
1,993,0,0,28,1529.30467,0.001481481,0.009150327,0,0,Mar,3,2,4,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,19,0,0.1,0,0,Mar,2,2,3,11,Returning_Visitor,TRUE,FALSE
5,74.25,2,84,37,1599.083333,0,0.006578947,0,0,Mar,2,2,4,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,9,102.5,0,0.022222222,0,0,Mar,2,2,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,16,2337,0,0.013333333,17.76266667,0,Mar,2,2,1,1,Returning_Visitor,FALSE,TRUE
0,0,0,0,19,1883.5,0.010526316,0.021052632,0,0,Mar,2,2,1,3,Returning_Visitor,FALSE,FALSE
2,32,0,0,50,1245.3,0.004,0.020666667,7.146260888,0,Mar,2,2,7,9,Returning_Visitor,TRUE,FALSE
6,666.8333333,0,0,22,1674.583333,0,0.014666667,0,0,Mar,2,2,3,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,9,132,0.011111111,0.033333333,0,0,Mar,4,1,1,3,Returning_Visitor,TRUE,FALSE
1,73,1,740,50,1434.255128,0,0.019230769,22.03276923,0,Mar,2,2,3,2,Returning_Visitor,TRUE,FALSE
2,154,0,0,18,367.25,0.005263158,0.044210526,0,0,Mar,3,2,2,1,Returning_Visitor,TRUE,FALSE
3,49.33333333,5,303.25,7,148.5,0,0.014081633,0,0,Mar,3,2,2,2,Returning_Visitor,FALSE,FALSE
3,118.5,0,0,29,1482.210784,0.006896552,0.010600255,0,0,Mar,3,2,1,8,Returning_Visitor,TRUE,FALSE
6,153.5,0,0,34,1048.492063,0.011578947,0.032225685,0,0,Mar,2,6,1,1,Returning_Visitor,TRUE,FALSE
0,0,0,0,9,478,0,0.011111111,0,0,Mar,3,2,2,3,Returning_Visitor,TRUE,FALSE
0,0,0,0,16,980.25,0,0.04,0,0,Mar,2,2,4,3,Returning_Visitor,FALSE,FALSE
8,72.25,1,21.5,51,1124.693074,0.022807018,0.036550087,0,0,Mar,2,2,2,2,Returning_Visitor,FALSE,FALSE
2,24.5,0,0,22,353.1666667,0.018181818,0.031818182,0,0,Mar,2,5,1,3,Returning_Visitor,FALSE,FALSE
1,0,0,0,18,1489.083333,0.023529412,0.046470588,0,0,Mar,2,2,8,1,Returning_Visitor,FALSE,FALSE
0,0,1,1220,28,2389.333333,0.016666667,0.030833333,0,0,Mar,2,2,1,3,Returning_Visitor,TRUE,FALSE
0,0,0,0,7,753,0,0.00952381,0,0,Mar,2,10,1,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,31,688.1666667,0,0.019354839,0,0,Mar,4,1,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,14,811,0.015384615,0.041025641,0,0,Mar,2,2,8,1,Returning_Visitor,FALSE,FALSE
1,22,0,0,9,415.25,0.033333333,0.048148148,0,0,Mar,3,3,1,1,Returning_Visitor,FALSE,FALSE
16,155.6313131,0,0,32,908.013456,0.005,0.01805276,4.368515556,0,Mar,2,2,3,2,Returning_Visitor,FALSE,TRUE
1,21.33333333,1,235,71,2753.378571,0.012676056,0.015201207,0,0,Mar,3,2,2,1,Returning_Visitor,TRUE,FALSE
2,191,1,100,46,2452.582143,0.007246377,0.022253906,0,0,Mar,3,2,9,3,Returning_Visitor,TRUE,FALSE
0,0,0,0,18,5188.5,0,0.05,0,0,Mar,2,5,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,0,0.2,0.2,0,0,Mar,1,1,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,5,57,0.08,0.12,0,0,Mar,2,5,2,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,8,0,0.1,0,0,Mar,2,2,5,1,Returning_Visitor,TRUE,FALSE
4,96.5,0,0,19,1430.659091,0.01,0.025666667,0,0,Mar,1,1,1,1,Returning_Visitor,FALSE,FALSE
1,13,0,0,2,20,0,0.05,0,0,Mar,3,2,3,2,Returning_Visitor,FALSE,FALSE
5,1388.75,0,0,4,1373.75,0,0.02,0,0,Mar,1,1,7,8,Returning_Visitor,FALSE,FALSE
0,0,0,0,45,844.25,0,0.01037037,0,0,Mar,1,1,3,1,Returning_Visitor,FALSE,FALSE
0,0,1,0,7,188,0,0.033333333,0,0,Mar,2,2,1,8,New_Visitor,FALSE,FALSE
3,51,0,0,14,527.375,0.015555556,0.033862434,0,0,Mar,7,1,6,1,Returning_Visitor,TRUE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,3,3,5,2,Returning_Visitor,FALSE,FALSE
1,158,1,64,29,1916.761905,0.006451613,0.018709677,8.772473118,0,Mar,2,2,3,2,Returning_Visitor,TRUE,TRUE
0,0,0,0,9,116.3333333,0,0.066666667,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,30,397,0,0.02,0,0,Mar,2,2,7,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,63,5220.083333,0,0.003329865,51.46331148,0,Mar,2,5,3,1,Returning_Visitor,TRUE,TRUE
0,0,0,0,20,219.3333333,0,0.011666667,0,0,Mar,1,8,7,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,5,74,0,0.04,0,0,Mar,2,2,1,10,Returning_Visitor,FALSE,FALSE
0,0,0,0,15,1559.6,0,0.033846154,0,0,Mar,2,4,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,6,236.5,0,0.016666667,0,0,Mar,1,1,1,3,Returning_Visitor,TRUE,FALSE
1,10,0,0,14,348.6666667,0.035714286,0.053571429,0,0,Mar,3,2,1,1,Returning_Visitor,TRUE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,2,5,1,1,Returning_Visitor,FALSE,FALSE
1,28,1,47,13,224.5,0,0.014285714,0,0,Mar,1,1,1,8,New_Visitor,FALSE,FALSE
4,27,0,0,42,601.7666667,0,0.004545455,0,0,Mar,2,5,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,5,75.5,0.02,0.013333333,0,0,Mar,1,1,2,9,Returning_Visitor,TRUE,FALSE
0,0,0,0,2,153,0,0.05,0,0,Mar,2,5,6,1,Returning_Visitor,FALSE,FALSE
4,15,0,0,10,197.2,0,0.016666667,38.99,0,Mar,1,1,1,3,Returning_Visitor,TRUE,TRUE
0,0,0,0,18,3658.5,0.016666667,0.05,0,0,Mar,4,2,9,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,5,1162.5,0,0.025,0,0,Mar,2,2,2,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,32,556.6,0.014583333,0.039583333,0,0,Mar,2,2,3,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,41,0,0.033333333,0,0,Mar,2,2,1,3,Returning_Visitor,TRUE,FALSE
0,0,0,0,11,300.0714286,0,0.02,53.9892,0,Mar,2,2,1,11,Returning_Visitor,TRUE,TRUE
13,1249.809524,4,205,36,1626.625433,0.010638298,0.026186255,6.831792392,0,Mar,3,2,2,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,6,69.25,0,0.044444444,0,0,Mar,2,2,4,3,Returning_Visitor,FALSE,FALSE
2,390,0,0,10,1169.1,0.02,0.05,0,0,Mar,3,9,9,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,8,402,0,0.038095238,0,0,Mar,2,2,2,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,35,3324.333333,0.011428571,0.024761905,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
11,215.5238095,1,70,87,3037.499952,0.002150538,0.007722385,0,0,Mar,2,2,5,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,59,0,0.05,0,0,Mar,1,1,1,10,Returning_Visitor,FALSE,FALSE
1,11,0,0,51,1059.253472,0.010588235,0.022643039,0,0,Mar,3,2,6,3,Returning_Visitor,FALSE,FALSE
2,20,0,0,7,720,0,0.011111111,0,0,Mar,2,2,3,6,Returning_Visitor,FALSE,FALSE
0,0,0,0,40,905.4856061,0.0135,0.03747619,0,0,Mar,3,2,2,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,1,1,1,1,Returning_Visitor,TRUE,FALSE
2,8,1,14.33333333,14,603.6666667,0,0.0125,44.67925,0,Mar,2,2,1,7,Returning_Visitor,FALSE,TRUE
0,0,0,0,13,328.9166667,0,0.014285714,59.79014286,0,Mar,3,2,1,3,Returning_Visitor,FALSE,TRUE
0,0,0,0,33,778.8166667,0,0.022424242,0,0,Mar,2,5,1,1,Returning_Visitor,FALSE,FALSE
4,171.25,0,0,22,851.5595238,0.004545455,0.031907308,0,0,Mar,3,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,1,1,8,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,227.5,0,0.022222222,0,0,Mar,2,2,1,3,Returning_Visitor,FALSE,FALSE
5,227.3333333,0,0,17,528.9,0,0.002272727,0,0,Mar,1,1,1,9,Returning_Visitor,TRUE,FALSE
0,0,0,0,15,872.8333333,0,0.026666667,0,0,Mar,2,2,2,3,Returning_Visitor,TRUE,FALSE
0,0,0,0,2,0,0.2,0.2,0,0,Mar,3,2,3,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,35,835.0666667,0.012571429,0.044761905,0,0,Mar,2,2,6,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,82.5,0,0.05,0,0,Mar,3,2,1,3,Returning_Visitor,FALSE,FALSE
0,0,1,0,1,13,0,0.1,0,0,Mar,3,2,3,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,9,0,0.1,0,0,Mar,2,2,1,3,Returning_Visitor,TRUE,FALSE
0,0,0,0,2,7,0,0.1,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,12,94.5,0.033333333,0.025555556,0,0,Mar,3,2,4,11,Returning_Visitor,FALSE,FALSE
5,86,0,0,23,267.3,0,0.016,0,0,Mar,1,1,4,9,Returning_Visitor,TRUE,FALSE
0,0,0,0,29,3312.5,0.013793103,0.028965517,0,0,Mar,2,2,1,13,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,75,0,0.066666667,0,0,Mar,2,5,1,3,Returning_Visitor,TRUE,FALSE
2,7,0,0,10,75,0.05,0.11,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,1,24,27,1547.5,0.003703704,0.014814815,0,0,Mar,3,2,1,1,Returning_Visitor,FALSE,FALSE
7,186.9761905,2,40,35,1276.157071,0,0.008681765,0,0,Mar,1,1,6,2,Returning_Visitor,FALSE,FALSE
3,138,2,136,54,2631.1,0,0.00969697,0,0,Mar,1,2,1,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,96,0,0.1,0,0,Mar,4,1,1,1,Returning_Visitor,FALSE,FALSE
2,374,0,0,3,1370,0,0.025,0,0,Mar,2,2,1,8,Returning_Visitor,FALSE,FALSE
2,61,0,0,5,97,0,0.04,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
1,14,0,0,46,1380.166667,0,0.01037037,0,0,Mar,4,1,1,1,Returning_Visitor,FALSE,FALSE
1,38,0,0,23,1483.6,0.022916667,0.038373016,7.103020833,0,Mar,3,2,6,1,Returning_Visitor,FALSE,TRUE
0,0,0,0,5,156,0,0.04,0,0,Mar,2,2,4,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,10,240.75,0,0.02,0,0,Mar,2,2,9,2,Returning_Visitor,FALSE,FALSE
2,96,0,0,37,1238.5,0.005128205,0.016410256,0,0,Mar,2,2,1,2,New_Visitor,FALSE,FALSE
6,615.25,0,0,68,2524.719048,0,0.000175593,0,0,Mar,1,2,6,1,Returning_Visitor,FALSE,FALSE
4,111,0,0,4,54,0,0.028571429,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
2,147,0,0,2,35,0,0.05,0,0,Mar,2,2,1,2,New_Visitor,FALSE,FALSE
0,0,0,0,15,175.9166667,0.013333333,0.026666667,0,0,Mar,1,1,1,1,Returning_Visitor,TRUE,FALSE
3,53.16666667,0,0,11,263.6,0,0.003571429,0,0,Mar,3,2,1,9,Returning_Visitor,FALSE,FALSE
2,58,0,0,7,101.8,0,0.011111111,0,0,Mar,3,2,8,2,New_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,3,2,3,1,Returning_Visitor,FALSE,FALSE
3,48.5,0,0,55,1042.242857,0,0.002222222,0,0,Mar,4,2,1,2,New_Visitor,FALSE,FALSE
1,21,3,116,21,613.6666667,0.008333333,0.023611111,0,0,Mar,1,2,1,1,Returning_Visitor,FALSE,FALSE
4,115.3333333,0,0,64,1588.944444,0.003076923,0.009213675,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,1,929,75,4105.666667,0.002631579,0.017324561,0,0,Mar,2,2,3,1,Returning_Visitor,FALSE,FALSE
1,8,0,0,14,269.5,0,0.019047619,0,0,Mar,2,2,3,1,Returning_Visitor,FALSE,FALSE
1,32.28571429,0,0,8,1236.2,0,0.028571429,0,0,Mar,3,2,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,49,1384.016667,0,0.011904762,0,0,Mar,2,2,1,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,52,0,0.025,0,0,Mar,2,2,1,2,Returning_Visitor,FALSE,FALSE
1,11,0,0,29,664.75,0,0.005057471,0,0,Mar,3,2,1,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,7,64,0,0.014285714,0,0,Mar,2,2,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,2,2,4,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,8,326.5,0.1,0.125,0,0,Mar,1,1,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,25,1690.977778,0.008,0.037333333,0,0,Mar,1,1,8,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,2,2,8,1,Returning_Visitor,FALSE,FALSE
4,277.75,0,0,3,178.75,0,0.008,0,0,Mar,3,2,3,8,New_Visitor,FALSE,FALSE
0,0,0,0,12,407,0,0.033333333,0,0,Mar,2,2,4,3,Returning_Visitor,FALSE,FALSE
6,241.1666667,0,0,39,1513.566667,0.005128205,0.021367521,0,0,Mar,1,1,1,3,Returning_Visitor,FALSE,FALSE
3,64,0,0,24,832.0909091,0,0.009876543,0,0,Mar,2,10,1,3,New_Visitor,FALSE,FALSE
1,25.5,0,0,12,250.8333333,0,0.016666667,0,0,Mar,3,2,2,1,Returning_Visitor,TRUE,FALSE
2,64,0,0,15,565.6666667,0,0.00625,0,0,Mar,2,2,1,1,New_Visitor,FALSE,FALSE
0,0,0,0,10,194,0.02,0.04,0,0,Mar,2,5,7,1,Returning_Visitor,FALSE,FALSE
8,130,1,18,19,298,0,0.016666667,19.66818546,0,Mar,2,2,3,1,Returning_Visitor,TRUE,FALSE
9,79,1,155.5,55,1743.066667,0,0.004371585,0,0,Mar,2,2,6,2,Returning_Visitor,FALSE,FALSE
3,84,0,0,27,655.9166667,0,0.011111111,0,0,Mar,2,2,2,1,Returning_Visitor,FALSE,FALSE
0,0,1,9,30,1992.833333,0,0.003333333,9.227000967,0,Mar,2,4,1,3,Returning_Visitor,FALSE,TRUE
0,0,0,0,3,0,0.2,0.2,0,0,Mar,2,2,4,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,24,308.8635531,0,0.028030303,0,0,Mar,2,6,2,2,Returning_Visitor,FALSE,FALSE
3,41,0,0,46,2749.666667,0,0.005555556,0,0,Mar,2,2,1,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,3,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,25,812,0,0.008,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,12,166,0.028571429,0.071428571,0,0,Mar,2,2,1,1,Returning_Visitor,TRUE,FALSE
1,14,0,0,4,65,0,0.05,0,0,Mar,2,4,3,1,Returning_Visitor,FALSE,FALSE
4,86,0,0,46,2450.688095,0.027083333,0.047905093,0,0,Mar,1,1,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,10,226.8333333,0,0.01,0,0,Mar,1,1,1,2,Returning_Visitor,TRUE,FALSE
3,618,0,0,9,341,0,0.007692308,34.43601877,0,Mar,2,2,9,3,New_Visitor,FALSE,TRUE
0,0,0,0,13,226,0,0.053846154,0,0,Mar,2,2,4,3,Returning_Visitor,TRUE,FALSE
1,11.88888889,0,0,111,3510.879903,9.83E-05,0.009438427,12.01656549,0,Mar,3,2,5,2,Returning_Visitor,FALSE,FALSE
5,51.5,0,0,2,6,0,0.033333333,0,0,Mar,2,5,2,1,Returning_Visitor,FALSE,FALSE
2,7,0,0,27,559.4,0.014814815,0.030452675,0,0,Mar,2,4,4,3,Returning_Visitor,TRUE,FALSE
8,269,0,0,33,1109.883333,0.013888889,0.027742165,0,0,Mar,1,1,4,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,5,239,0,0.04,0,0,Mar,2,2,9,1,Returning_Visitor,FALSE,FALSE
2,44.5,0,0,7,212.1666667,0,0.00625,0,0,Mar,3,2,1,8,New_Visitor,TRUE,FALSE
1,3,14,1165.166667,81,2820.952419,0.008897485,0.029431012,0,0,Mar,2,2,3,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,6,44,0.066666667,0.1,0,0,Mar,2,2,3,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,8,781,0.028571429,0.057142857,0,0,Mar,3,2,4,1,Returning_Visitor,FALSE,FALSE
4,61,0,0,14,175.6666667,0,0.010588235,0,0,Mar,2,2,5,2,Returning_Visitor,FALSE,FALSE
3,90,0,0,25,397.8846154,0.005333333,0.033504762,0,0,Mar,2,2,1,1,Returning_Visitor,TRUE,FALSE
0,0,0,0,25,770.0285714,0.0112,0.034933333,0,0,Mar,3,2,8,10,Returning_Visitor,FALSE,FALSE
2,102.5,3,60,22,1034.975,0,0.014,16.14384,0,Mar,1,1,4,2,Returning_Visitor,FALSE,TRUE
0,0,0,0,2,12,0,0.1,0,0,Mar,1,1,5,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,8,0.066666667,0.133333333,0,0,Mar,2,4,1,3,Returning_Visitor,FALSE,FALSE
1,17,0,0,22,399.8,0.019047619,0.038095238,0,0,Mar,1,5,7,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,2,2,2,3,Returning_Visitor,FALSE,FALSE
9,213.3214286,5,528,61,2258.430586,0.01,0.020655014,2.810812468,0,Mar,1,1,4,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,254,0,0.1,0,0,Mar,3,2,4,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,7,67,0,0.028571429,0,0,Mar,2,2,1,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,57,0,0.025,0,0,Mar,2,2,6,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,12,240.4166667,0,0.061688312,0,0,Mar,3,2,1,6,Returning_Visitor,FALSE,FALSE
0,0,0,0,8,551.1666667,0.025,0.035,0,0,Mar,3,2,2,3,Returning_Visitor,FALSE,FALSE
6,71.5,0,0,47,1532.2,0.009929078,0.019797366,27.26888014,0,Mar,2,2,1,1,Returning_Visitor,FALSE,TRUE
0,0,0,0,7,379.5,0.057142857,0.085714286,0,0,Mar,3,2,8,1,Returning_Visitor,FALSE,FALSE
1,6,0,0,14,548.1857143,0.028571429,0.02987013,0,0,Mar,3,2,3,1,Returning_Visitor,TRUE,FALSE
3,304,0,0,31,1735.301587,0.015625,0.0515625,0,0,Mar,1,1,2,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,103,0,0.022222222,0,0,Mar,1,1,1,3,Returning_Visitor,TRUE,FALSE
7,151,0,0,44,1406.1,0.004081633,0.006501458,0,0,Mar,1,1,4,2,Returning_Visitor,FALSE,FALSE
3,199.75,0,0,8,331.4,0,0.003333333,0,0,Mar,3,2,2,10,New_Visitor,FALSE,FALSE
1,13.5,1,28,88,1759.275703,0.004545455,0.020644542,0,0,Mar,2,2,1,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,2,4,1,1,Returning_Visitor,FALSE,FALSE
7,191.2,4,654.3333333,31,1204.600433,0.000854701,0.013342491,11.92009615,0,Mar,2,2,7,2,Returning_Visitor,FALSE,TRUE
2,47,0,0,39,1743.366667,0,0.016410256,78.93483561,0,Mar,3,3,2,1,Returning_Visitor,FALSE,TRUE
0,0,0,0,10,236,0,0.026666667,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
5,197,4,246,17,427.0833333,0,0.008695652,0,0,Mar,1,1,3,2,New_Visitor,FALSE,FALSE
3,115.125,0,0,46,909.522619,0.004255319,0.020449173,0,0,Mar,2,2,6,1,Returning_Visitor,FALSE,FALSE
4,312.75,0,0,14,702.9166667,0,0.014259259,0,0,Mar,3,2,1,2,New_Visitor,FALSE,FALSE
0,0,0,0,40,962.3333333,0,0.01625,0,0,Mar,2,2,9,1,Returning_Visitor,FALSE,FALSE
4,724,0,0,2,159,0,0.008,0,0,Mar,4,2,1,7,New_Visitor,FALSE,FALSE
0,0,0,0,2,24,0,0.1,0,0,Mar,2,6,1,2,Returning_Visitor,FALSE,FALSE
8,237.5,4,142,30,1569.625,0,0.008108108,15.88906362,0,Mar,1,2,1,9,Returning_Visitor,TRUE,TRUE
3,66.33333333,0,0,15,424.8333333,0,0.0125,0,0,Mar,2,2,6,6,Returning_Visitor,FALSE,FALSE
0,0,0,0,16,154.8333333,0,0.00625,0,0,Mar,2,4,7,1,Returning_Visitor,FALSE,FALSE
2,190,1,0,37,758.4428571,0,0.010526316,0,0,Mar,1,1,6,1,Returning_Visitor,TRUE,FALSE
4,174,1,18.5,11,305.875,0,0.001709402,0,0,Mar,1,2,3,8,New_Visitor,TRUE,FALSE
3,227,0,0,2,62,0,0.025,0,0,Mar,3,2,1,10,Returning_Visitor,TRUE,FALSE
1,23,0,0,15,656.25,0.028571429,0.028571429,0,0,Mar,1,1,8,2,Returning_Visitor,TRUE,FALSE
0,0,0,0,29,617.5,0.006896552,0.01954023,0,0,Mar,2,2,3,10,Returning_Visitor,FALSE,FALSE
0,0,2,39,15,245,0,0.0125,11.9955404,0,Mar,2,2,1,3,Returning_Visitor,TRUE,TRUE
0,0,0,0,3,20,0,0.066666667,0,0,Mar,2,2,2,1,Returning_Visitor,TRUE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,1,1,1,1,Returning_Visitor,TRUE,FALSE
0,0,0,0,2,22,0,0.1,0,0,Mar,1,2,9,2,Returning_Visitor,FALSE,FALSE
1,26,1,0,55,872.4,0.003508772,0.01754386,0,0,Mar,2,5,1,1,Returning_Visitor,TRUE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,3,2,2,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,38,1372,0.005405405,0.018918919,0,0,Mar,2,2,1,2,Returning_Visitor,FALSE,FALSE
2,41,0,0,7,139,0.022222222,0.055555556,0,0,Mar,2,5,6,2,Returning_Visitor,TRUE,FALSE
4,74,2,629,149,5042.458059,0.003870968,0.007285123,18.36804916,0,Mar,2,2,1,2,Returning_Visitor,FALSE,TRUE
0,0,0,0,5,288.5,0,0.0125,0,0,Mar,2,2,1,2,Returning_Visitor,TRUE,FALSE
0,0,0,0,2,0,0.2,0.2,0,0,Mar,2,2,1,3,Returning_Visitor,TRUE,FALSE
0,0,0,0,6,192,0,0.04,0,0,Mar,2,10,4,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,27,954.6666667,0,0.003846154,0,0,Mar,2,2,1,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,2,2,4,11,Returning_Visitor,FALSE,FALSE
2,74,0,0,13,429,0.013333333,0.040444444,0,0,Mar,2,4,3,6,Returning_Visitor,FALSE,FALSE
0,0,0,0,41,1546.5,0,0.008333333,0,0,Mar,3,2,1,1,Returning_Visitor,TRUE,FALSE
2,45,0,0,9,96.46666667,0,0.018181818,0,0,Mar,2,2,3,1,Returning_Visitor,FALSE,FALSE
2,112,0,0,9,198.8333333,0,0.006060606,0,0,Mar,3,2,3,2,New_Visitor,TRUE,FALSE
0,0,0,0,8,181,0.075,0.1,0,0,Mar,3,2,1,13,Returning_Visitor,TRUE,FALSE
2,37,0,0,15,208.5,0,0.011764706,0,0,Mar,2,2,3,2,New_Visitor,TRUE,FALSE
0,0,0,0,21,517.4238095,0.019047619,0.025,0,0,Mar,2,5,2,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,12,358.0666667,0,0.025,0,0,Mar,3,3,2,1,Returning_Visitor,FALSE,FALSE
1,5.5,0,0,22,339.25,0,0.026984127,0,0,Mar,2,2,2,3,Returning_Visitor,FALSE,FALSE
3,50,0,0,13,796,0,0.013333333,0,0,Mar,2,2,5,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,31,1759.416667,0,0.002903226,0,0,Mar,2,2,4,2,Returning_Visitor,TRUE,FALSE
2,26,0,0,19,3277,0.015789474,0.037894737,0,0,Mar,2,2,4,6,Returning_Visitor,FALSE,FALSE
0,0,0,0,13,265.1666667,0,0.046153846,0,0,Mar,2,2,4,2,Returning_Visitor,FALSE,FALSE
5,113.5,0,0,13,437.2,0,0.002222222,0,0,Mar,1,8,4,11,New_Visitor,FALSE,FALSE
0,0,0,0,6,92,0,0.066666667,0,0,Mar,1,1,3,10,Returning_Visitor,FALSE,FALSE
3,279,0,0,0,0,0,0.05,0,0,Mar,3,2,1,10,Returning_Visitor,TRUE,FALSE
3,228,1,267.5,23,1266.267677,0.002197802,0.037765568,0,0,Mar,2,2,3,2,Returning_Visitor,FALSE,FALSE
3,55,2,4,2,19,0,0.033333333,0,0,Mar,1,1,8,2,New_Visitor,FALSE,FALSE
6,112.5,0,0,47,1882.113409,0.004,0.019314286,17.527656,0,Mar,1,1,4,3,Returning_Visitor,FALSE,FALSE
1,17,0,0,12,616.4,0,0.018181818,0,0,Mar,1,1,3,1,Returning_Visitor,TRUE,FALSE
0,0,0,0,5,155,0.04,0.053333333,0,0,Mar,2,2,1,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,11,814.5,0,0.01,0,0,Mar,1,1,1,2,New_Visitor,FALSE,FALSE
0,0,0,0,21,460.4166667,0.019047619,0.036507937,0,0,Mar,2,2,6,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,5,819.5,0,0.036,0,0,Mar,2,2,1,2,Returning_Visitor,TRUE,FALSE
1,8.5,0,0,30,659.2,0,0.006451613,0,0,Mar,2,2,3,3,New_Visitor,TRUE,FALSE
0,0,0,0,5,427,0,0.04,0,0,Mar,3,3,3,9,Returning_Visitor,TRUE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,2,2,4,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,17,766.5,0,0.0125,61.9395,0,Mar,2,2,1,2,New_Visitor,TRUE,TRUE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,2,5,5,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,14,2425,0,0.007142857,0,0,Mar,2,2,1,3,Returning_Visitor,FALSE,FALSE
7,319.5,0,0,11,416.5,0,0.007142857,0,0,Mar,3,2,1,9,New_Visitor,TRUE,FALSE
0,0,0,0,15,638.6428571,0.003571429,0.053571429,0,0,Mar,3,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,1,132,8,445,0,0.014285714,0,0,Mar,3,2,4,14,Returning_Visitor,TRUE,FALSE
0,0,0,0,4,81,0,0.025,0,0,Mar,2,2,3,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,20,1985,0.03,0.055,0,0,Mar,1,1,1,1,Returning_Visitor,FALSE,FALSE
5,97.5,0,0,24,758.1444444,0.04,0.059846154,0,0,Mar,3,2,2,1,Returning_Visitor,TRUE,FALSE
7,182.0833333,0,0,15,310.9,0,0.01,0,0,Mar,2,2,4,2,Returning_Visitor,FALSE,FALSE
3,97,0,0,15,482,0.0125,0.025,0,0,Mar,2,2,6,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,0,0.2,0.2,0,0,Mar,2,5,1,1,Returning_Visitor,FALSE,FALSE
3,34.83333333,0,0,30,709.8333333,0.026666667,0.046666667,0,0,Mar,1,1,2,1,Returning_Visitor,TRUE,FALSE
0,0,3,57,31,4547.166667,0.012903226,0.039247312,8.682741935,0,Mar,2,4,5,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,9,1040,0.077777778,0.116666667,0,0,Mar,2,4,3,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,223,0.066666667,0.133333333,0,0,Mar,1,1,8,3,Returning_Visitor,FALSE,FALSE
0,0,2,14,11,687.5,0.020512821,0.035897436,0,0,Mar,3,2,1,3,Returning_Visitor,TRUE,FALSE
0,0,0,0,30,632.5833333,0,0.021666667,0,0,Mar,2,5,1,1,Returning_Visitor,FALSE,FALSE
1,77,0,0,9,312,0,0.044444444,0,0,Mar,1,1,3,3,New_Visitor,TRUE,FALSE
3,107,0,0,45,2502.966667,0,0.008510638,9.702113281,0,Mar,2,4,1,2,New_Visitor,TRUE,FALSE
10,614.1666667,0,0,47,3608.9,0,0.019871795,7.256219133,0,Mar,2,2,3,1,Returning_Visitor,FALSE,FALSE
13,315.9666667,1,0,15,406.575,0.019047619,0.032380952,0,0,Mar,3,2,3,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,2,2,3,3,Returning_Visitor,FALSE,FALSE
1,0,0,0,39,2487.5,0.017105263,0.047105263,0,0,Mar,2,2,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,15,212.8,0.019047619,0.042857143,0,0,Mar,1,1,3,1,Returning_Visitor,FALSE,FALSE
2,11,0,0,20,510,0.013636364,0.034848485,0,0,Mar,4,1,6,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,3,2,3,1,Returning_Visitor,FALSE,FALSE
2,47.66666667,0,0,5,72.33333333,0,0.014285714,0,0,Mar,1,1,8,2,New_Visitor,FALSE,FALSE
0,0,0,0,13,96.5,0.030769231,0.076923077,0,0,Mar,2,6,4,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,8,267,0,0.05,0,0,Mar,2,2,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,8,481.1666667,0,0.025,0,0,Mar,2,2,7,7,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,2528,0,0.066666667,0,0,Mar,2,2,9,1,Returning_Visitor,TRUE,FALSE
2,30,1,148.5,24,1530.194444,0.007407407,0.014814815,10.10222222,0,Mar,1,1,1,10,Returning_Visitor,FALSE,FALSE
0,0,0,0,7,289.5,0,0.014285714,0,0,Mar,1,1,1,1,Returning_Visitor,TRUE,FALSE
0,0,0,0,1,10,0,0.1,0,0,Mar,3,2,3,9,Returning_Visitor,TRUE,FALSE
0,0,0,0,16,676.75,0.014285714,0.035714286,0,0,Mar,4,2,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,36,0.05,0.1,0,0,Mar,2,2,6,1,Returning_Visitor,FALSE,FALSE
2,25,0,0,6,65,0,0.025,0,0,Mar,2,2,1,2,New_Visitor,TRUE,FALSE
0,0,0,0,16,630.75,0,0.04047619,0,0,Mar,3,2,1,1,Returning_Visitor,TRUE,FALSE
8,359,2,954,14,336.5,0,0.005555556,0,0,Mar,3,2,7,9,Returning_Visitor,TRUE,FALSE
0,0,0,0,5,77,0,0.04,0,0,Mar,2,4,1,3,Returning_Visitor,TRUE,FALSE
5,59,0,0,3,44.66666667,0,0.025,0,0,Mar,2,4,6,2,Returning_Visitor,TRUE,FALSE
4,1347.75,0,0,22,3410.875,0.019871795,0.09,0,0,Mar,2,2,1,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,10,322.5,0.04,0.07,0,0,Mar,2,2,4,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,11,919,0,0.027272727,0,0,Mar,2,6,2,3,Returning_Visitor,FALSE,FALSE
18,280.95,6,762.5,79,2096.911364,0.003333333,0.014008551,25.96702005,0,Mar,2,4,2,2,Returning_Visitor,FALSE,FALSE
4,100.3,0,0,66,2868.133333,0.011428571,0.01725974,9.162351243,0,Mar,3,2,1,1,Returning_Visitor,FALSE,TRUE
1,23,0,0,27,1058.893939,0,0.010493827,1.865777778,0,Mar,2,2,3,13,Returning_Visitor,FALSE,FALSE
6,53.38095238,0,0,5,54.38095238,0,0.003571429,0,0,Mar,2,2,6,2,New_Visitor,TRUE,FALSE
2,8,0,0,11,543.5,0.007692308,0.038461538,0,0,Mar,2,2,3,13,Returning_Visitor,FALSE,FALSE
0,0,0,0,29,1089,0.006896552,0.013793103,0,0,Mar,1,6,1,1,Returning_Visitor,FALSE,FALSE
1,0,1,60,43,1131.808333,0.028787879,0.047348485,0,0,Mar,1,1,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,7,314.5,0.033333333,0.066666667,0,0,Mar,2,2,3,1,Returning_Visitor,FALSE,FALSE
14,416.3928571,6,449.3333333,258,11301.20416,0,0.00742538,33.6117917,0,Mar,2,4,9,2,Returning_Visitor,FALSE,TRUE
6,573.5,1,0,33,1946.942857,0.005882353,0.020602653,0,0,Mar,3,2,3,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
6,465.8333333,2,71,26,1558,0.006666667,0.013333333,7.169617487,0,Mar,2,2,1,1,Returning_Visitor,TRUE,FALSE
0,0,1,212.5,21,1198.75,0,0.003174603,0,0,Mar,2,4,7,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,2,2,4,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,17,927.1666667,0,0.014705882,0,0,Mar,1,1,2,3,Returning_Visitor,FALSE,FALSE
9,97.64285714,0,0,37,584.5958874,0.005128205,0.013043478,0,0,Mar,2,4,1,3,Returning_Visitor,TRUE,FALSE
0,0,0,0,4,135.5,0,0.066666667,0,0,Mar,2,2,3,14,Returning_Visitor,FALSE,FALSE
3,148,0,0,8,292.5,0,0.027272727,0,0,Mar,2,2,1,3,Returning_Visitor,TRUE,FALSE
0,0,0,0,2,68.5,0,0.033333333,0,0,Mar,3,2,1,10,Returning_Visitor,FALSE,FALSE
3,58,0,0,23,364.1666667,0.004,0.02,0,0,Mar,2,2,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,26,694.3,0.023076923,0.036410256,0,0,Mar,3,2,2,3,Returning_Visitor,TRUE,FALSE
1,3,0,0,3,236,0,0.025,0,0,Mar,3,2,1,3,Returning_Visitor,TRUE,FALSE
4,97.61111111,0,0,24,1128.468254,0.038461538,0.058577534,0,0,Mar,2,4,3,1,Returning_Visitor,FALSE,FALSE
4,57,0,0,5,81,0,0.025,0,0,Mar,1,1,8,10,Returning_Visitor,FALSE,FALSE
2,34,0,0,21,521.5,0.018181818,0.021212121,0,0,Mar,3,2,5,1,Returning_Visitor,TRUE,FALSE
0,0,0,0,7,496.75,0,0.011111111,0,0,Mar,3,2,6,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,9,104.8333333,0.022222222,0.072222222,0,0,Mar,2,2,4,2,Returning_Visitor,FALSE,FALSE
1,7,0,0,4,45,0,0.0125,0,0,Mar,3,2,3,1,Returning_Visitor,FALSE,FALSE
2,37.5,0,0,2,492.5,0,0.05,0,0,Mar,2,2,1,2,Returning_Visitor,FALSE,FALSE
1,3,0,0,40,624.75,0,0.014634146,0,0,Mar,3,7,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,3,2,7,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,6,116.5,0,0.066666667,0,0,Mar,2,2,2,3,Returning_Visitor,TRUE,FALSE
0,0,0,0,8,144,0.025,0.045833333,0,0,Mar,3,2,7,3,Returning_Visitor,TRUE,FALSE
2,22.5,0,0,28,686.3222222,0,0.001190476,0,0,Mar,2,4,3,1,Returning_Visitor,FALSE,FALSE
0,0,1,1411,1,1411,0,0.1,0,0,Mar,2,2,1,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,7,126,0.028571429,0.057142857,0,0,Mar,2,5,2,10,Returning_Visitor,FALSE,FALSE
0,0,0,0,6,185,0,0.1,0,0,Mar,1,1,1,10,Returning_Visitor,FALSE,FALSE
0,0,0,0,6,218,0,0.066666667,0,0,Mar,2,2,3,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,3,2,3,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,30,484.672619,0,0.018965517,0,0,Mar,2,6,7,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,19,439.8333333,0.005555556,0.003703704,0,0,Mar,1,1,7,2,New_Visitor,FALSE,FALSE
2,38,0,0,21,733.7,0,0.014035088,0,0,Mar,2,7,1,3,Returning_Visitor,TRUE,FALSE
6,77,3,447,34,1469.702381,0,0.02398374,22.80152439,0,Mar,2,2,1,2,Returning_Visitor,FALSE,FALSE
2,58.5,2,125,16,485.8333333,0,0.002222222,0,0,Mar,2,2,7,2,New_Visitor,TRUE,FALSE
0,0,0,0,3,19,0,0.066666667,0,0,Mar,2,4,1,1,Returning_Visitor,TRUE,FALSE
6,99.33333333,1,28.5,5,345.5,0,0.011111111,0,0,Mar,2,2,3,8,New_Visitor,FALSE,FALSE
3,117,0,0,20,543.8,0.00952381,0.019047619,0,0,Mar,1,1,1,2,New_Visitor,FALSE,FALSE
0,0,0,0,3,48,0,0.066666667,0,0,Mar,4,1,1,1,Returning_Visitor,FALSE,FALSE
2,16.66666667,0,0,22,343.3690476,0.001298701,0.039924242,0,0,Mar,3,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,9,171,0.022222222,0.066666667,0,0,Mar,2,10,4,3,Returning_Visitor,FALSE,FALSE
12,81.5,0,0,61,2202.579167,0.005797101,0.017153855,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,11,299.5,0.036363636,0.072727273,0,0,Mar,1,1,3,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,1,90,11,1056.5,0.018181818,0.054545455,0,0,Mar,4,2,1,2,Returning_Visitor,FALSE,FALSE
4,34,0,0,46,627.3083333,0,0.004166667,0,0,Mar,2,2,7,8,New_Visitor,FALSE,FALSE
4,38.5,0,0,33,583.8333333,0.002631579,0.007894737,0,0,Mar,2,2,4,3,Returning_Visitor,TRUE,FALSE
0,0,0,0,7,221.5,0,0.028571429,0,0,Mar,4,1,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,44,441.7916667,0.004545455,0.018181818,0,0,Mar,4,2,1,3,Returning_Visitor,FALSE,FALSE
7,156.25,0,0,37,1037.355013,0,0.0165,0,0,Mar,3,2,8,2,Returning_Visitor,FALSE,FALSE
3,15,0,0,11,246,0.018181818,0.054545455,0,0,Mar,2,2,1,8,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,10,0,0.066666667,0,0,Mar,2,2,7,1,Returning_Visitor,FALSE,FALSE
0,0,2,18,1,46,0,0.066666667,0,0,Mar,2,2,7,10,Returning_Visitor,FALSE,FALSE
0,0,0,0,80,801.802381,0,0.0035,0,0,Mar,2,2,3,1,Returning_Visitor,FALSE,FALSE
1,19,0,0,40,1361.166667,0.005,0.0225,0,0,Mar,4,1,2,3,Returning_Visitor,TRUE,FALSE
0,0,0,0,5,53,0.04,0.08,0,0,Mar,2,5,2,2,Returning_Visitor,TRUE,FALSE
1,7,0,0,17,2648.5,0.0125,0.03125,0,0,Mar,2,2,1,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,27,0.066666667,0.133333333,0,0,Mar,2,2,1,13,Returning_Visitor,FALSE,FALSE
0,0,0,0,13,255,0,0.015384615,0,0,Mar,2,4,1,1,Returning_Visitor,TRUE,FALSE
0,0,0,0,2,221.5,0,0.05,0,0,Mar,3,2,3,10,Returning_Visitor,TRUE,FALSE
0,0,0,0,7,225,0.028571429,0.085714286,0,0,Mar,4,1,4,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,7,125,0,0.028571429,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,12,323,0.033333333,0.066666667,0,0,Mar,2,2,1,3,Returning_Visitor,TRUE,FALSE
5,67.5,3,245,32,1929.329762,0,0.00430839,0,0,Mar,2,4,1,1,Returning_Visitor,FALSE,FALSE
12,311.4090909,0,0,96,4233.4807,0.006635802,0.027174712,3.541145833,0,Mar,2,4,1,1,Returning_Visitor,TRUE,FALSE
0,0,0,0,5,116,0,0.04,0,0,Mar,2,5,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,0,0.2,0.2,0,0,Mar,3,2,6,1,Returning_Visitor,TRUE,FALSE
3,14,0,0,27,1585.666667,0.026666667,0.058333333,0,0,Mar,2,2,6,1,Returning_Visitor,TRUE,FALSE
6,145,0,0,13,644,0,0.013333333,0,0,Mar,2,2,1,2,New_Visitor,FALSE,FALSE
0,0,0,0,5,488.5,0.032727273,0.033846154,0,0,Mar,2,7,7,6,Returning_Visitor,FALSE,FALSE
0,0,1,15,25,1235.65,0.041666667,0.05327381,0,0,Mar,1,1,1,3,Returning_Visitor,TRUE,FALSE
1,43,0,0,37,1505.166667,0,0.005263158,0,0,Mar,2,2,4,8,New_Visitor,FALSE,FALSE
0,0,0,0,7,495,0,0.00952381,0,0,Mar,4,1,3,2,Returning_Visitor,FALSE,FALSE
4,84,0,0,21,270,0,0.002380952,0,0,Mar,1,1,3,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,0,0.2,0.2,0,0,Mar,3,2,1,10,Returning_Visitor,FALSE,FALSE
4,120,0,0,13,293,0,0.014285714,0,0,Mar,1,2,1,10,Returning_Visitor,FALSE,FALSE
0,0,1,0,51,2122.656061,0,0.007051282,9.294775641,0,Mar,2,2,1,10,Returning_Visitor,FALSE,TRUE
0,0,0,0,35,1231.160256,0.005714286,0.023619048,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,17,341.6666667,0.011764706,0.041176471,0,0,Mar,2,6,9,6,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,1,1,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,21,1686.333333,0,0.030952381,0,0,Mar,2,5,2,1,Returning_Visitor,FALSE,FALSE
5,263,0,0,3,212,0,0.028571429,0,0,Mar,1,1,9,8,New_Visitor,FALSE,FALSE
1,0,0,0,34,2161.979365,0.00625,0.020233586,0,0,Mar,3,2,1,1,Returning_Visitor,FALSE,FALSE
9,72.94444444,2,125.0952381,17,318.0730159,0.008695652,0.035397453,0,0,Mar,3,2,8,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,13,0,0.1,0,0,Mar,2,2,3,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,30,390.6666667,0.006666667,0.056666667,0,0,Mar,2,6,6,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,11,253,0,0.027272727,0,0,Mar,2,2,2,1,Returning_Visitor,FALSE,FALSE
1,18.5,0,0,12,208,0.045454545,0.081818182,0,0,Mar,2,2,4,1,Returning_Visitor,FALSE,FALSE
6,87.33333333,0,0,62,1470.853037,0,0.009683372,0,0,Mar,2,4,6,3,Returning_Visitor,TRUE,FALSE
6,99.60588235,0,0,83,2585.61835,0,0.00761877,6.871308983,0,Mar,2,2,2,2,Returning_Visitor,FALSE,TRUE
3,63,0,0,13,400.3333333,0.030769231,0.046153846,0,0,Mar,4,1,3,1,Returning_Visitor,FALSE,FALSE
3,68,1,103,10,808.5,0,0.015384615,35.99261538,0,Mar,2,2,3,7,Returning_Visitor,TRUE,TRUE
0,0,0,0,12,1484,0,0.016666667,0,0,Mar,2,2,7,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,505,0,0.05,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
3,68.5,0,0,37,1121.205556,0.005405405,0.00113798,0,0,Mar,1,1,1,2,Returning_Visitor,TRUE,FALSE
1,135,0,0,2,141,0,0.066666667,0,0,Mar,2,2,1,10,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,234,0,0.033333333,0,0,Mar,1,2,1,2,Returning_Visitor,TRUE,FALSE
1,34,0,0,7,179,0,0.028571429,53.13428571,0,Mar,2,4,2,8,New_Visitor,FALSE,TRUE
6,176.25,12,404,41,2720.671429,0.012962963,0.033262108,8.833825926,0,Mar,2,2,2,2,Returning_Visitor,TRUE,TRUE
16,315.1449864,6,147.8666667,173,6255.017866,0.002531328,0.010737154,0,0,Mar,2,2,2,2,Returning_Visitor,FALSE,FALSE
6,523.2142857,2,263,48,2309.732468,0.003846154,0.014903846,10.60089168,0,Mar,2,2,3,1,Returning_Visitor,FALSE,TRUE
4,76,0,0,39,1936.55,0.004761905,0.023809524,5.51397619,0,Mar,4,1,3,2,Returning_Visitor,FALSE,FALSE
3,118.6666667,0,0,17,694,0.003703704,0.008333333,27.45138186,0,Mar,3,2,1,2,Returning_Visitor,TRUE,TRUE
0,0,0,0,11,125,0.018181818,0.081818182,0,0,Mar,2,2,1,13,Returning_Visitor,FALSE,FALSE
8,174.5,0,0,10,195.5,0,0.006060606,0,0,Mar,1,1,3,2,Returning_Visitor,FALSE,FALSE
1,40,0,0,27,1400.5,0,0.007142857,0,0,Mar,1,1,4,2,Returning_Visitor,FALSE,FALSE
8,201.1666667,3,41,18,914.1666667,0,0.0125,0,0,Mar,1,1,1,3,Returning_Visitor,FALSE,FALSE
13,374.875,1,53,88,5958.071931,0.002105263,0.00954386,0,0,Mar,2,2,3,2,Returning_Visitor,FALSE,FALSE
4,56,0,0,31,270.4916667,0,0.00234375,0,0,Mar,2,2,1,3,Returning_Visitor,FALSE,FALSE
3,92.83333333,0,0,24,463.8166667,0.002666667,0.015333333,17.84230699,0,Mar,1,1,1,2,Returning_Visitor,FALSE,TRUE
0,0,0,0,16,371.5,0.0125,0.025,0,0,Mar,2,5,7,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,6,13,0.133333333,0.166666667,0,0,Mar,2,2,1,3,Returning_Visitor,FALSE,FALSE
1,4,3,148.5,5,185.8333333,0,0.01875,0,0,Mar,2,2,7,2,Returning_Visitor,FALSE,FALSE
2,102,0,0,16,502.8333333,0,0.004444444,0,0,Mar,3,2,4,2,Returning_Visitor,TRUE,FALSE
0,0,0,0,3,1016.5,0.066666667,0.066666667,0,0,Mar,3,2,5,1,Returning_Visitor,FALSE,FALSE
1,11,0,0,16,253,0,0.023529412,0,0,Mar,2,2,1,3,New_Visitor,FALSE,FALSE
0,0,1,126,17,887.0666667,0.0125,0.0296875,0,0,Mar,2,2,1,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,58,3200.366667,0.003448276,0.027586207,0,0,Mar,2,2,6,1,Returning_Visitor,FALSE,FALSE
3,187,2,41,48,1769.697383,0.000606061,0.011616162,16.71534488,0,Mar,2,2,3,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,14,1037.5,0.014285714,0.047619048,0,0,Mar,2,2,4,2,Returning_Visitor,FALSE,FALSE
4,185,0,0,40,1694.75,0.020512821,0.031196581,0,0,Mar,2,2,6,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,37,1643.435516,0.005555556,0.032271242,2.188718519,0,Mar,2,4,3,2,Returning_Visitor,TRUE,TRUE
0,0,0,0,7,383.5,0,0.023809524,0,0,Mar,3,2,6,3,Returning_Visitor,FALSE,FALSE
8,166.2,5,371,23,626.2213675,0.004444444,0.008888889,0,0,Mar,1,1,8,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,34,0.1,0.125,0,0,Mar,3,2,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,27,1070.461905,0,0.007407407,57.7293604,0,Mar,2,2,3,2,Returning_Visitor,FALSE,TRUE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,3,2,3,3,Returning_Visitor,FALSE,FALSE
2,84,0,0,3,195,0,0.02,0,0,Mar,2,2,5,2,Returning_Visitor,FALSE,FALSE
3,86,0,0,22,1187.833333,0.009090909,0.027272727,0,0,Mar,3,2,3,1,Returning_Visitor,TRUE,FALSE
17,754.1095238,2,77,31,1021.619336,0.004545455,0.026479076,2.08053355,0,Mar,1,1,3,2,Returning_Visitor,FALSE,TRUE
3,24,0,0,6,58,0,0.028571429,0,0,Mar,2,2,8,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,18,771.0833333,0.055555556,0.071428571,0,0,Mar,2,2,3,1,Returning_Visitor,FALSE,FALSE
8,17.34848485,0,0,19,291.2589744,0,0.043589744,0,0,Mar,2,2,7,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,15,695.4,0.014285714,0.028571429,0,0,Mar,2,2,2,1,Returning_Visitor,FALSE,FALSE
2,15,0,0,3,21,0,0.05,0,0,Mar,3,2,4,8,Returning_Visitor,FALSE,FALSE
0,0,0,0,45,1594.283333,0,0.015227273,45.4316713,0,Mar,2,2,1,2,Returning_Visitor,TRUE,TRUE
3,36,1,395,12,343.5833333,0,0.014285714,0,0,Mar,2,2,1,2,New_Visitor,FALSE,FALSE
2,34,0,0,81,2241.002381,0.002439024,0.007012195,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,5,0,0.1,0,0,Mar,2,2,1,13,Returning_Visitor,TRUE,FALSE
0,0,0,0,2,63,0,0.05,0,0,Mar,3,2,1,1,Returning_Visitor,FALSE,FALSE
2,47,0,0,21,825.0833333,0,0.009090909,10.7929507,0,Mar,2,2,2,2,New_Visitor,FALSE,TRUE
0,0,0,0,54,1357.61783,0,0.004812274,0,0,Mar,2,2,2,2,Returning_Visitor,TRUE,FALSE
5,44.5,1,4,37,836.3333333,0.005,0.045416667,0,0,Mar,2,2,4,1,Returning_Visitor,FALSE,FALSE
6,125.5,0,0,19,1409.416667,0.002469136,0.023703704,0,0,Mar,1,8,3,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,10,60.5,0.02,0.04,0,0,Mar,2,2,3,1,Returning_Visitor,FALSE,FALSE
2,42,2,54,10,420,0,0.008333333,0,0,Mar,2,2,8,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,2,5,9,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,0,0.2,0.2,0,0,Mar,2,5,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,9,389,0,0.011111111,0,0,Mar,2,2,3,3,Returning_Visitor,TRUE,FALSE
2,95,0,0,15,449.5,0.0125,0.04375,0,0,Mar,2,2,4,1,Returning_Visitor,FALSE,FALSE
4,56.5,0,0,8,202.1666667,0,0.01,0,0,Mar,3,2,1,8,New_Visitor,TRUE,FALSE
0,0,0,0,2,17,0,0.1,0,0,Mar,1,1,8,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,12,689.2857143,0,0.058333333,0,0,Mar,3,2,3,1,Returning_Visitor,TRUE,FALSE
5,134.9285714,2,41,31,2013.595238,0,0.014141414,8.482727273,0,Mar,2,2,8,2,Returning_Visitor,FALSE,TRUE
0,0,0,0,17,933.4166667,0.031932773,0.043075335,0,0,Mar,3,2,1,3,Returning_Visitor,FALSE,FALSE
2,64,0,0,19,371.2272727,0.001666667,0.029166667,0,0,Mar,2,4,9,10,Returning_Visitor,FALSE,FALSE
3,68,0,0,8,306,0,0.008888889,0,0,Mar,1,1,9,3,New_Visitor,TRUE,FALSE
2,20.5,0,0,21,719.7380952,0.004347826,0.010434783,0,0,Mar,2,2,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,2,4,6,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,56,0,0.1,0,0,Mar,3,2,1,1,Returning_Visitor,FALSE,FALSE
3,11.33333333,0,0,20,302.3888889,0,0.002380952,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,19,491.6666667,0.011111111,0.012222222,0,0,Mar,1,1,1,6,Returning_Visitor,TRUE,FALSE
5,504,0,0,13,922.0833333,0.023529412,0.023529412,0,0,Mar,3,2,8,2,Returning_Visitor,FALSE,FALSE
2,25,0,0,20,667.9166667,0,0.00952381,18.5847619,0,Mar,4,1,1,3,Returning_Visitor,FALSE,FALSE
2,20,0,0,13,181.5,0,0.013333333,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
1,19.66666667,0,0,14,512.1111111,0.028571429,0.03,0,0,Mar,3,2,3,9,Returning_Visitor,TRUE,FALSE
1,13,0,0,15,317,0,0.006666667,0,0,Mar,2,2,1,2,New_Visitor,TRUE,FALSE
0,0,0,0,17,85.66666667,0.023529412,0.080392157,0,0,Mar,2,2,6,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,8,128.5,0,0.025,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
6,76.33333333,0,0,7,78.83333333,0.004444444,0.010666667,0,0,Mar,2,2,8,2,Returning_Visitor,FALSE,FALSE
2,45.44444444,1,40.66666667,57,851.6426534,0,0.007923497,3.077836066,0,Mar,2,4,3,1,Returning_Visitor,TRUE,TRUE
3,31,0,0,58,1400.438961,0,0.005951036,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,6,84,0,0.033333333,0,0,Mar,1,1,8,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,12,167.2222222,0,0.001666667,0,0,Mar,3,2,1,3,Returning_Visitor,TRUE,FALSE
0,0,0,0,12,396.5,0,0.037222222,0,0,Mar,2,4,3,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,22,0,0.05,0,0,Mar,1,1,3,15,Returning_Visitor,TRUE,FALSE
0,0,0,0,5,371,0,0.02,0,0,Mar,2,2,4,10,Returning_Visitor,FALSE,FALSE
0,0,4,399.3333333,46,1814.583333,0.003673469,0.02675737,0,0,Mar,2,2,2,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,30.5,0,0.05,0,0,Mar,2,4,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,27,644,0.007692308,0.051923077,0,0,Mar,3,2,2,3,Returning_Visitor,FALSE,FALSE
8,125.1666667,0,0,27,1802.25,0.006060606,0.011774152,0,0,Mar,3,2,1,8,Returning_Visitor,TRUE,FALSE
2,13,0,0,23,855.1666667,0.008,0.025333333,0,0,Mar,2,5,1,3,Returning_Visitor,FALSE,FALSE
1,72.66666667,4,345,24,879.9090909,0,0.035897436,6.482798269,0,Mar,2,4,4,1,Returning_Visitor,FALSE,TRUE
5,100.9166667,0,0,56,1432.223333,0,0.002185792,69.43043195,0,Mar,2,2,3,3,Returning_Visitor,TRUE,TRUE
7,60,3,23,111,2524.501905,0.001694915,0.018834175,6.445051499,0,Mar,3,2,1,2,Returning_Visitor,TRUE,FALSE
3,49.5,1,29.5,45,1545.5,0,0.004,20.97144,0,Mar,2,4,3,8,Returning_Visitor,TRUE,TRUE
8,466.5,2,75.25,44,1616.425824,0.006944444,0.010974434,0,0,Mar,3,2,4,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,8,332,0,0.028571429,0,0,Mar,3,2,1,8,New_Visitor,TRUE,FALSE
0,0,0,0,1,40,0,0.1,0,0,Mar,3,2,1,10,Returning_Visitor,FALSE,FALSE
5,175.2307692,0,0,20,2224.85,0.004347826,0.023913043,0,0,Mar,4,2,8,1,Returning_Visitor,FALSE,FALSE
6,96.85714286,0,0,28,672.5452381,0,0.020707071,19.71468924,0,Mar,1,1,2,10,Returning_Visitor,FALSE,TRUE
0,0,0,0,6,551,0.033333333,0.05,0,0,Mar,1,1,3,1,Returning_Visitor,FALSE,FALSE
19,402.1857143,4,116,64,3179.354257,0.002531646,0.016289934,4.642,0,Mar,2,2,2,2,Returning_Visitor,FALSE,TRUE
0,0,0,0,10,203,0,0.026666667,0,0,Mar,3,2,2,3,Returning_Visitor,FALSE,FALSE
4,178.2,0,0,9,368.2,0.02,0.05,0,0,Mar,3,2,8,3,Returning_Visitor,TRUE,FALSE
7,156.5,1,122,26,694.7121212,0,0.00297619,0,0,Mar,2,4,1,2,Returning_Visitor,FALSE,FALSE
5,58,0,0,10,657.2619048,0,0.004166667,0,0,Mar,1,1,2,2,New_Visitor,FALSE,FALSE
0,0,0,0,7,974.6666667,0.085714286,0.128571429,0,0,Mar,2,2,1,10,Returning_Visitor,FALSE,FALSE
1,43,0,0,43,1223.347222,0,0.004545455,0,0,Mar,1,1,3,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,10,276,0.044444444,0.055555556,0,0,Mar,3,2,3,10,Returning_Visitor,FALSE,FALSE
0,0,1,844,6,1108,0.066666667,0.066666667,0,0,Mar,2,2,4,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,7,223,0,0.028571429,0,0,Mar,1,1,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,261,0,0.066666667,0,0,Mar,2,5,1,10,Returning_Visitor,FALSE,FALSE
0,0,0,0,21,1372.7,0.019047619,0.035714286,0,0,Mar,1,1,3,1,Returning_Visitor,FALSE,FALSE
2,306,0,0,14,964.5,0,0.030952381,0,0,Mar,2,2,4,1,Returning_Visitor,FALSE,FALSE
3,72,1,0,38,461.5,0.01,0.023666667,0,0,Mar,2,2,3,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,41,0.05,0.1,0,0,Mar,3,2,2,1,Returning_Visitor,FALSE,FALSE
1,202,0,0,2,8,0,0.066666667,0,0,Mar,2,2,8,6,New_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,1,1,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,7,39.25,0.028571429,0.034285714,0,0,Mar,2,2,1,2,Returning_Visitor,FALSE,FALSE
4,359.3,4,407,69,5485.105556,0.010526316,0.017493734,4.494741228,0,Mar,1,1,2,1,Returning_Visitor,TRUE,TRUE
0,0,0,0,8,450,0,0.025,0,0,Mar,4,1,9,3,Returning_Visitor,TRUE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,1,1,2,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,20,438.3333333,0.02,0.04,0,0,Mar,2,2,7,1,Returning_Visitor,FALSE,FALSE
1,39,0,0,15,787,0,0.021875,0,0,Mar,4,1,1,10,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,2,4,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,6,319,0,0.05,0,0,Mar,1,1,6,1,Returning_Visitor,TRUE,FALSE
0,0,0,0,15,1148,0.014285714,0.05,0,0,Mar,3,2,1,3,Returning_Visitor,FALSE,FALSE
2,41.5,2,60.5,21,534.5,0.004347826,0.02173913,0,0,Mar,2,2,2,13,Returning_Visitor,TRUE,FALSE
0,0,0,0,20,644.4,0,0.007777778,0,0,Mar,1,1,7,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,14,875,0,0.014285714,0,0,Mar,1,1,1,3,Returning_Visitor,TRUE,FALSE
2,123,0,0,7,873,0,0.011111111,0,0,Mar,1,2,2,2,Returning_Visitor,FALSE,FALSE
3,42,0,0,31,3121.369048,0.002857143,0.009285714,0,0,Mar,1,1,3,1,Returning_Visitor,TRUE,FALSE
0,0,1,81,82,3214.020563,0,0.007723577,4.667079268,0,Mar,3,3,2,10,Returning_Visitor,FALSE,TRUE
0,0,0,0,3,14,0,0.066666667,0,0,Mar,4,1,3,3,Returning_Visitor,FALSE,FALSE
1,22,0,0,52,1551.666667,0.001818182,0.019393939,7.882377258,0,Mar,1,1,3,2,Returning_Visitor,FALSE,FALSE
2,95.5,0,0,13,334.5,0,0.002666667,0,0,Mar,3,2,1,8,New_Visitor,FALSE,FALSE
2,48.66666667,0,0,48,3726.333333,0,0.004166667,0,0,Mar,3,2,1,9,Returning_Visitor,TRUE,FALSE
5,294.7,6,329.5,59,2816.781781,0.003214696,0.014766169,2.346800426,0,Mar,2,2,4,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,38,667.1666667,0,0.005263158,0,0,Mar,2,2,4,1,Returning_Visitor,TRUE,FALSE
1,0,0,0,41,1202.904762,0.011529933,0.033252033,0,0,Mar,2,2,2,13,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,0,0.2,0.2,0,0,Mar,1,8,2,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,20,1117.333333,0,0.000956938,0,0,Mar,2,4,7,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,9,211,0,0.044444444,0,0,Mar,2,2,3,2,Returning_Visitor,FALSE,FALSE
3,125,1,70,29,705.4,0,0.015625,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
3,12,1,24,3,5.333333333,0.033333333,0.083333333,0,0,Mar,2,2,1,3,Returning_Visitor,FALSE,FALSE
1,10.5,0,0,7,525,0,0.00952381,0,0,Mar,2,4,4,8,Returning_Visitor,FALSE,FALSE
0,0,0,0,13,635.3333333,0,0.009090909,0,0,Mar,2,2,4,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,50,1803.768849,0.001360544,0.017428305,3.609398514,0,Mar,2,4,7,3,Returning_Visitor,TRUE,TRUE
3,99,0,0,37,2419.133333,0.007894737,0.023245614,0,0,Mar,2,2,3,1,Returning_Visitor,FALSE,FALSE
6,171.0833333,0,0,28,952.2857143,0,0.013333333,52.10818182,0,Mar,2,2,1,2,Returning_Visitor,FALSE,TRUE
7,159.5,0,0,14,249,0.011764706,0.041176471,0,0,Mar,1,1,3,2,Returning_Visitor,TRUE,FALSE
1,5,0,0,13,271,0,0.003571429,0,0,Mar,1,1,2,2,New_Visitor,TRUE,FALSE
5,206,0,0,15,650.6961927,0,0.018487395,0,0,Mar,1,1,1,3,New_Visitor,FALSE,FALSE
2,40,2,162,17,481.6666667,0.024561404,0.036842105,32.64521053,0,Mar,2,7,3,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,7,258.5,0.028571429,0.071428571,0,0,Mar,3,2,6,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,14,510.5,0,0.015384615,31.3094364,0,Mar,2,2,1,2,New_Visitor,FALSE,TRUE
0,0,0,0,16,600.75,0,0.025,0,0,Mar,2,2,2,2,Returning_Visitor,FALSE,FALSE
6,262.25,3,298,49,2302.021242,0.000308642,0.026591844,43.3616369,0,Mar,1,1,1,2,Returning_Visitor,FALSE,TRUE
2,44,0,0,26,1636.016667,0.007692308,0.021794872,0,0,Mar,2,6,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,16,519.75,0.0125,0.04,0,0,Mar,3,2,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,1,1,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,11,673,0.018181818,0.063636364,0,0,Mar,2,6,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,173.5,0,0.05,0,0,Mar,3,3,4,3,Returning_Visitor,TRUE,FALSE
0,0,0,0,16,156.5333333,0,0.04375,0,0,Mar,2,4,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,21,574.5333333,0,0.011578947,0,0,Mar,2,2,3,1,Returning_Visitor,FALSE,FALSE
2,62.5,0,0,17,548.3333333,0,0.031372549,0,0,Mar,2,2,1,2,Returning_Visitor,FALSE,FALSE
15,937.1746032,3,357,109,6682.677557,0.000833333,0.005345441,2.526616865,0,Mar,1,2,3,2,Returning_Visitor,FALSE,FALSE
2,48,0,0,51,1671.375,0.001098901,0.016433566,0,0,Mar,2,2,1,6,Returning_Visitor,TRUE,FALSE
0,0,0,0,11,1390.166667,0.012121212,0.014545455,0,0,Mar,1,1,1,3,Returning_Visitor,TRUE,FALSE
6,437.3913043,2,235.55,83,2503.881781,0.002197802,0.004916136,2.086218493,0,Mar,2,2,3,2,Returning_Visitor,FALSE,TRUE
7,159.3333333,0,0,24,520.6666667,0,0.006666667,0,0,Mar,2,10,4,3,New_Visitor,TRUE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,2,2,4,1,Returning_Visitor,FALSE,FALSE
2,32.5,0,0,19,423.8166667,0.005952381,0.039104938,0,0,Mar,3,2,1,3,Returning_Visitor,FALSE,FALSE
0,0,2,30,11,1114.916667,0,0.030769231,0,0,Mar,3,2,1,3,Returning_Visitor,FALSE,FALSE
11,212.7416667,3,104,71,1678.905125,0,0.016037881,8.600043095,0,Mar,3,2,8,13,Returning_Visitor,TRUE,FALSE
0,0,0,0,29,438.8666667,0,0.020689655,0,0,Mar,4,2,3,1,Returning_Visitor,TRUE,FALSE
3,16.33333333,0,0,23,505.5833333,0.008,0.03,9.15008,0,Mar,4,1,1,2,Returning_Visitor,FALSE,TRUE
0,0,0,0,9,76,0.022222222,0.055555556,0,0,Mar,2,2,6,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,7,203.5,0,0.033333333,0,0,Mar,1,1,1,9,New_Visitor,TRUE,FALSE
4,130,0,0,28,818.7916667,0,0.003448276,0,0,Mar,2,2,1,2,New_Visitor,FALSE,FALSE
4,15,1,17,17,490,0,0.027272727,15.66445171,0,Mar,2,2,4,10,Returning_Visitor,FALSE,TRUE
0,0,1,0,12,645.9166667,0,0.05,0,0,Mar,1,1,1,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,8,142,0,0.05,0,0,Mar,2,7,2,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,6,25,0,0.033333333,0,0,Mar,2,2,1,2,Returning_Visitor,FALSE,FALSE
2,44,0,0,16,672.5,0.005555556,0.025925926,0,0,Mar,2,2,4,2,Returning_Visitor,TRUE,FALSE
9,140.5,0,0,35,1090.490476,0.013675214,0.016892552,0,0,Mar,1,1,3,2,Returning_Visitor,TRUE,FALSE
0,0,0,0,3,30,0,0.066666667,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,13,244.1666667,0,0.030769231,0,0,Mar,2,5,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,13,129.5,0.061538462,0.092307692,0,0,Mar,1,8,1,1,Returning_Visitor,FALSE,FALSE
4,56,1,88,22,1734.780952,0,0.010142857,0,0,Mar,3,2,3,9,Returning_Visitor,TRUE,FALSE
3,281,0,0,6,145,0,0.025,0,0,Mar,3,2,8,8,New_Visitor,FALSE,FALSE
2,88,0,0,16,1106.333333,0.025,0.053125,0,0,Mar,1,1,3,3,Returning_Visitor,FALSE,FALSE
1,0,0,0,17,684.9166667,0.015686275,0.049411765,0,0,Mar,2,6,4,1,Returning_Visitor,TRUE,FALSE
9,110.4090909,1,51,62,3120.211102,0.00056338,0.017396907,7.891171006,0,Mar,2,2,1,10,Returning_Visitor,FALSE,FALSE
0,0,0,0,12,1178.666667,0.024242424,0.053030303,0,0,Mar,1,1,6,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,58,0,0.066666667,0,0,Mar,1,8,4,11,Returning_Visitor,FALSE,FALSE
10,316.1405025,7,321.6666667,287,12983.78771,0.000668896,0.006998399,1.088158231,0,Mar,2,4,3,8,New_Visitor,FALSE,FALSE
0,0,0,0,6,139,0,0.01,0,0,Mar,1,2,1,8,New_Visitor,FALSE,FALSE
2,27,0,0,6,558,0,0.0125,0,0,Mar,2,2,3,8,New_Visitor,FALSE,FALSE
3,74,2,26,53,893.5111111,0.003571429,0.005357143,44.61199852,0,Mar,1,1,4,9,Returning_Visitor,TRUE,TRUE
0,0,0,0,5,26.5,0.04,0.12,0,0,Mar,1,1,3,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,0,0.2,0.2,0,0,Mar,2,2,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,0,0.2,0.2,0,0,Mar,3,2,6,3,Returning_Visitor,FALSE,FALSE
1,0,1,0,15,708.5333333,0,0.04,54.85543,0,Mar,2,4,3,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,8,244,0.025,0.075,0,0,Mar,3,2,1,3,Returning_Visitor,FALSE,FALSE
2,140,0,0,6,130,0,0.025,0,0,Mar,1,1,4,2,New_Visitor,TRUE,FALSE
3,119,0,0,41,1282.5,0,0.007142857,0,0,Mar,2,6,2,2,New_Visitor,FALSE,FALSE
7,301.7,6,336.5,42,1981.016667,0.005660377,0.021383648,13.00183962,0,Mar,1,1,2,2,Returning_Visitor,TRUE,TRUE
0,0,0,0,8,186.5,0,0.025,0,0,Mar,2,2,3,3,Returning_Visitor,TRUE,FALSE
0,0,0,0,6,119,0,0.033333333,0,0,Mar,3,2,7,1,Returning_Visitor,TRUE,FALSE
0,0,0,0,22,1310.5,0.00952381,0.028571429,23.86359286,0,Mar,2,2,1,1,Returning_Visitor,FALSE,TRUE
0,0,0,0,4,1111,0,0.05,0,0,Mar,4,5,1,1,Returning_Visitor,FALSE,FALSE
6,113.5,0,0,18,1066.5,0,0.005072464,0,0,Mar,2,2,7,2,New_Visitor,FALSE,FALSE
3,421,0,0,4,110.5,0,0.011111111,0,0,Mar,3,2,8,2,New_Visitor,TRUE,FALSE
2,115,0,0,5,36,0,0.033333333,0,0,Mar,1,1,3,11,Returning_Visitor,FALSE,FALSE
0,0,2,76.5,22,850.5333333,0.004545455,0.03446281,0,0,Mar,3,2,3,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,16,0.033333333,0.1,0,0,Mar,2,6,1,3,Returning_Visitor,FALSE,FALSE
1,9,0,0,5,49,0,0.05,0,0,Mar,2,2,8,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,10,214.25,0,0.025,0,0,Mar,3,2,2,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,0,0.2,0.2,0,0,Mar,1,1,3,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,7,141.8333333,0.064285714,0.15,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,5,143.5,0,0.04,0,0,Mar,2,5,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,51,5818.916667,0.000980392,0.022984749,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
2,208,1,50,30,1461.666667,0,0.02125,0,0,Mar,2,5,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,13,123,0,0.020833333,0,0,Mar,2,2,1,3,Returning_Visitor,FALSE,FALSE
5,193,1,13,66,2049.458471,0.004489796,0.012765306,29.45815149,0,Mar,3,2,3,1,Returning_Visitor,TRUE,FALSE
1,3,0,0,11,271.7166667,0,0.016666667,0,0,Mar,4,1,3,2,Returning_Visitor,TRUE,FALSE
4,87.5,1,20,36,1279.166667,0,0.010810811,0,0,Mar,2,2,1,6,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,0,0.2,0.2,0,0,Mar,1,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,70.5,0.05,0.1,0,0,Mar,3,2,4,3,Returning_Visitor,FALSE,FALSE
5,42.18181818,0,0,12,231.1818182,0,0.01,0,0,Mar,2,2,1,2,New_Visitor,TRUE,FALSE
3,132.5,0,0,36,1567.966667,0,0.007207207,0,0,Mar,3,3,2,8,Returning_Visitor,TRUE,FALSE
7,163.6666667,0,0,8,119.3333333,0.015384615,0.023076923,0,0,Mar,3,2,6,11,New_Visitor,TRUE,FALSE
2,83,0,0,15,605.8857143,0,0.005882353,0,0,Mar,1,1,3,2,Returning_Visitor,TRUE,FALSE
5,117.8333333,0,0,35,502.547619,0.01025641,0.036923077,3.148615385,0,Mar,2,2,2,2,Returning_Visitor,FALSE,TRUE
3,95,0,0,27,808.7,0.006896552,0.010344828,0,0,Mar,3,2,7,3,Returning_Visitor,TRUE,FALSE
0,0,0,0,3,58,0,0.066666667,0,0,Mar,1,1,1,10,Returning_Visitor,FALSE,FALSE
3,60,0,0,19,494.5,0,0.01,0,0,Mar,1,1,3,9,Returning_Visitor,TRUE,FALSE
0,0,0,0,6,203.15,0,0.051111111,0,0,Mar,2,2,7,2,Returning_Visitor,FALSE,FALSE
5,55.5,0,0,63,1656.316667,0.004166667,0.015989583,0,0,Mar,2,2,2,2,Returning_Visitor,TRUE,FALSE
0,0,0,0,32,1420.25,0.00625,0.027083333,0,0,Mar,4,2,1,1,Returning_Visitor,FALSE,FALSE
8,160.5,2,1467,26,721,0,0.031029186,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
4,64.33333333,1,13,27,1433.916667,0,0.018226601,3.691344828,0,Mar,1,4,1,8,New_Visitor,FALSE,TRUE
4,73.33333333,0,0,17,478.8333333,0,0.00877193,0,0,Mar,1,1,3,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,7,182,0.028571429,0.071428571,0,0,Mar,3,2,1,13,Returning_Visitor,TRUE,FALSE
9,215.2333333,5,450,35,1974.352381,0.004761905,0.018866213,15.32910159,0,Mar,2,2,3,2,Returning_Visitor,FALSE,FALSE
4,81.5,0,0,12,223.5833333,0,0.002666667,0,0,Mar,1,1,1,3,Returning_Visitor,FALSE,FALSE
0,0,1,26,15,817.4166667,0.026666667,0.038222222,0,0,Mar,2,2,6,1,Returning_Visitor,FALSE,FALSE
7,201.5,0,0,17,750.1666667,0,0.005555556,0,0,Mar,3,2,4,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,13,0.1,0.1,0,0,Mar,1,1,2,1,Returning_Visitor,TRUE,FALSE
8,492.4166667,4,384,52,4699.277778,0.007258065,0.018233487,11.1076505,0,Mar,2,2,1,2,Returning_Visitor,FALSE,TRUE
7,146.25,0,0,42,1030.266667,0,0.008695652,0,0,Mar,2,2,1,2,New_Visitor,FALSE,FALSE
5,156.2690476,4,90,35,776.0190476,0,0.005714286,0,0,Mar,3,2,4,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,558,0,0.066666667,0,0,Mar,4,1,3,1,Returning_Visitor,FALSE,FALSE
4,13.61904762,0,0,27,520.3333333,0,0.020322581,8.497935484,0,Mar,3,2,4,2,Returning_Visitor,TRUE,FALSE
0,0,0,0,8,349.5,0,0.028571429,25.188,0,Mar,1,2,1,8,New_Visitor,FALSE,TRUE
2,14,0,0,31,754.5,0,0.00625,0,0,Mar,2,2,1,8,Returning_Visitor,TRUE,FALSE
0,0,0,0,13,305,0,0.016666667,0,0,Mar,1,1,1,2,New_Visitor,FALSE,FALSE
0,0,0,0,21,399.8511905,0,0.023933659,0,0,Mar,3,2,1,1,Returning_Visitor,FALSE,FALSE
1,12,0,0,6,74,0,0.028571429,0,0,Mar,1,1,1,10,Returning_Visitor,FALSE,FALSE
6,352.5,0,0,21,696.6666667,0,0.0125,75.06781572,0,Mar,2,2,6,10,New_Visitor,TRUE,TRUE
0,0,0,0,3,59,0,0.033333333,0,0,Mar,3,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,50,0,0.033333333,0,0,Mar,2,2,1,2,Returning_Visitor,FALSE,FALSE
5,92.75,1,74.75,84,2756.215152,0,0.002462121,0,0,Mar,2,2,9,3,New_Visitor,TRUE,FALSE
0,0,0,0,12,425.1666667,0,0.016666667,0,0,Mar,1,1,6,10,Returning_Visitor,FALSE,FALSE
0,0,0,0,78,1781.69697,0.003205128,0.015811966,0,0,Mar,2,2,8,3,Returning_Visitor,FALSE,FALSE
3,168,0,0,7,296.1666667,0,0.011111111,0,0,Mar,2,2,3,2,New_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,2,4,1,1,Returning_Visitor,TRUE,FALSE
5,179.5,0,0,36,1792.8,0,0.004390244,0,0,Mar,2,2,3,10,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,3,2,3,1,Returning_Visitor,FALSE,FALSE
8,274.5,0,0,24,515.5757576,0,0.003703704,0,0,Mar,3,2,2,2,Returning_Visitor,TRUE,FALSE
3,64.5,0,0,35,1334.551371,0,0.007309582,0,0,Mar,3,2,4,2,Returning_Visitor,TRUE,FALSE
0,0,0,0,6,64,0.1,0.133333333,0,0,Mar,4,1,1,1,Returning_Visitor,FALSE,FALSE
1,4,2,102,31,624.5833333,0.016216216,0.031531532,8.708324324,0,Mar,2,2,3,13,Returning_Visitor,TRUE,FALSE
9,171.6666667,3,109.75,41,1284.663492,0.016326531,0.032653061,21.22386735,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,10,316.5,0,0.025,17.538,0,Mar,2,4,1,8,New_Visitor,TRUE,TRUE
0,0,0,0,22,925.8333333,0.018181818,0.048484848,0,0,Mar,2,2,3,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,7,97,0.057142857,0.1,0,0,Mar,2,2,4,1,Returning_Visitor,FALSE,FALSE
1,0,0,0,1,28,0,0.1,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
9,311.9166667,0,0,40,633.4,0.002272727,0.017954545,0,0,Mar,2,2,1,3,Returning_Visitor,FALSE,FALSE
1,98.5,0,0,5,436.5,0,0.016666667,0,0,Mar,7,1,1,2,New_Visitor,TRUE,FALSE
9,867.922619,0,0,137,3909.36829,0,0.005055944,9.930187005,0,Mar,2,2,6,2,Returning_Visitor,FALSE,FALSE
3,147,0,0,3,24,0,0.02,0,0,Mar,3,2,7,1,Returning_Visitor,FALSE,FALSE
2,27,0,0,18,915.1666667,0.021052632,0.036842105,0,0,Mar,2,2,4,1,Returning_Visitor,FALSE,FALSE
3,106.75,0,0,5,137.3333333,0,0.005,0,0,Mar,3,2,1,2,New_Visitor,TRUE,FALSE
0,0,0,0,5,95,0.04,0.12,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,1,1,2,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,24,778.1666667,0,0.0125,0,0,Mar,2,2,1,2,Returning_Visitor,FALSE,FALSE
1,55,1,47,47,1842.95,0,0.01257764,0,0,Mar,2,2,6,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,27,1206,0.016,0.032,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,9,324.5,0.014814815,0.022222222,0,0,Mar,1,2,6,1,Returning_Visitor,FALSE,FALSE
5,241.6666667,5,229,38,1054.944444,0.010869565,0.014565217,8.224168543,0,Mar,2,4,3,2,Returning_Visitor,TRUE,FALSE
0,0,0,0,12,402.1666667,0.041666667,0.065,0,0,Mar,3,2,2,1,Returning_Visitor,FALSE,FALSE
1,47,0,0,5,388,0,0.04,31.188,0,Mar,1,1,7,3,Returning_Visitor,TRUE,TRUE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,3,2,3,11,Returning_Visitor,FALSE,FALSE
3,35,0,0,16,352,0,0.011764706,0,0,Mar,2,2,2,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,11,194,0,0.018181818,0,0,Mar,2,2,6,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,15,751.8,0.026666667,0.04,0,0,Mar,1,2,2,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,9,465.5,0.006666667,0.056666667,43.79717364,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,25,585,0,0.016,0,0,Mar,4,1,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,10,253.5,0,0.022222222,63.588,0,Mar,1,1,1,2,New_Visitor,TRUE,TRUE
3,33,2,84.5,4,46.5,0,0.010666667,0,0,Mar,2,2,5,8,New_Visitor,FALSE,FALSE
3,152.5,5,243.5,43,3065.945238,0,0.011666667,3.31108,0,Mar,1,2,1,1,Returning_Visitor,TRUE,TRUE
11,828.0526316,6,389.3666667,57,2099.930554,0.003333333,0.009142857,3.29868,0,Mar,2,2,1,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,30,0,0.05,0,0,Mar,3,2,1,9,Returning_Visitor,TRUE,FALSE
0,0,0,0,3,52,0,0.066666667,0,0,Mar,2,5,8,3,Returning_Visitor,TRUE,FALSE
4,162,3,75.5,4,158.5,0,0.016666667,0,0,Mar,2,4,1,10,Returning_Visitor,FALSE,FALSE
4,539.5,0,0,1,0,0,0.05,0,0,Mar,3,2,8,8,New_Visitor,FALSE,FALSE
0,0,0,0,9,250.5,0,0.044444444,0,0,Mar,3,2,7,1,Returning_Visitor,TRUE,FALSE
4,120.5,0,0,66,3960.646154,0.002941176,0.013663064,0,0,Mar,2,4,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,9,280,0,0.022222222,0,0,Mar,2,2,1,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,13,281.547619,0.003846154,0.017307692,0,0,Mar,1,1,2,2,Returning_Visitor,TRUE,FALSE
1,12,0,0,13,2004.5,0.028571429,0.04047619,0,0,Mar,1,1,6,2,Returning_Visitor,TRUE,FALSE
12,285.0119048,0,0,53,967.210697,0.000892857,0.033208874,0,0,Mar,2,2,3,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,6,100,0,0.033333333,0,0,Mar,2,2,4,6,Returning_Visitor,TRUE,FALSE
10,198.5,2,158,6,73.21428571,0,0.02,0,0,Mar,1,1,1,2,Returning_Visitor,FALSE,FALSE
4,224,1,32,20,789.35,0,0.002721088,0,0,Mar,1,2,4,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,30,1281,0.006666667,0.02,0,0,Mar,2,4,2,1,Returning_Visitor,FALSE,FALSE
4,162.5,2,44.5,20,1115.266667,0,0.020661157,0,0,Mar,1,2,3,10,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,3,2,2,1,Returning_Visitor,FALSE,FALSE
2,77.5,3,92,18,341.2916667,0,0.009090909,0,0,Mar,1,1,1,2,New_Visitor,TRUE,FALSE
6,192.5,0,0,113,3000.666667,0.003478261,0.005217391,0,0,Mar,2,2,3,2,Returning_Visitor,FALSE,FALSE
6,148.8,4,81.33333333,29,1715.687897,0.010909091,0.027138047,0,0,Mar,2,2,9,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,8,607,0.0375,0.0625,0,0,Mar,1,1,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,31,0,0.05,0,0,Mar,2,2,7,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,16,1027.657143,0.0125,0.01875,0,0,Mar,1,1,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,2,2,7,10,Returning_Visitor,FALSE,FALSE
0,0,0,0,8,196.5,0,0.025,0,0,Mar,2,2,1,10,Returning_Visitor,FALSE,FALSE
4,1521,2,64,30,2284.687302,0.019354839,0.042741935,2.304322581,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
13,112.2666667,0,0,49,1503.490909,0,0.003508772,0,0,Mar,2,2,2,2,New_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,2,2,1,10,Returning_Visitor,FALSE,FALSE
3,150,0,0,12,271.3333333,0,0.014285714,0,0,Mar,1,1,4,2,New_Visitor,FALSE,FALSE
0,0,0,0,6,97.33333333,0,0.041666667,0,0,Mar,1,2,1,2,Returning_Visitor,TRUE,FALSE
0,0,0,0,5,161.3333333,0,0.05,0,0,Mar,1,1,1,3,Returning_Visitor,FALSE,FALSE
0,0,4,32.5,7,67,0,0.022222222,0,0,Mar,2,2,1,8,New_Visitor,FALSE,FALSE
0,0,0,0,34,1006.257576,0,0.015196078,0,0,Mar,2,2,7,3,Returning_Visitor,FALSE,FALSE
4,167.5,0,0,22,869.9,0,0.026388889,33.53327578,0,Mar,2,6,4,10,Returning_Visitor,FALSE,TRUE
4,57,1,0,19,479.8666667,0,0.018181818,0,0,Mar,4,2,1,2,Returning_Visitor,FALSE,FALSE
5,345,0,0,7,229.5,0.03,0.026666667,0,0,Mar,3,2,4,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,1,1,7,2,Returning_Visitor,TRUE,FALSE
0,0,0,0,20,606,0,0.011111111,0,0,Mar,2,2,6,1,Returning_Visitor,FALSE,FALSE
11,267.1666667,0,0,39,881.4416667,0.004166667,0.011458333,20.11751289,0,Mar,2,2,3,1,New_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,3,2,3,9,Returning_Visitor,TRUE,FALSE
3,123,0,0,8,371.6666667,0,0.011111111,0,0,Mar,3,2,4,2,New_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
3,1373.5,0,0,43,2798.07381,0,0.010971006,2.915511628,0,Mar,2,6,2,3,Returning_Visitor,FALSE,FALSE
5,29,0,0,4,12,0,0.033333333,0,0,Mar,4,1,1,8,New_Visitor,TRUE,FALSE
0,0,0,0,42,1185.666667,0,0.004761905,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,60,0,0.05,0,0,Mar,3,2,3,1,Returning_Visitor,FALSE,FALSE
8,29.5,0,0,89,6770.274267,0.006315789,0.030125313,0,0,Mar,2,2,3,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,5,337.25,0,0.02,0,0,Mar,2,2,2,10,Returning_Visitor,FALSE,FALSE
0,0,0,0,13,323.9166667,0,0.008333333,35.8370931,0,Mar,1,1,4,10,Returning_Visitor,FALSE,TRUE
5,79.33333333,3,242.0555556,17,1142.816919,0.006818182,0.018519814,62.16886364,0,Mar,3,2,6,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,3,2,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,148.5,0.05,0.083333333,0,0,Mar,1,1,1,1,Returning_Visitor,TRUE,FALSE
3,16,0,0,11,207,0,0.015384615,0,0,Mar,2,2,2,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,11,0,0.1,0,0,Mar,4,2,2,10,Returning_Visitor,FALSE,FALSE
0,0,0,0,6,53,0,0.06,0,0,Mar,2,2,7,3,Returning_Visitor,TRUE,FALSE
2,33,0,0,9,354,0,0.02,0,0,Mar,3,2,1,3,New_Visitor,FALSE,FALSE
3,139,0,0,10,277.1428571,0,0.007692308,0,0,Mar,3,2,1,2,Returning_Visitor,TRUE,FALSE
2,47,0,0,17,411.625,0,0.023529412,0,0,Mar,2,2,4,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,16,392.1428571,0.00625,0.027205882,0,0,Mar,3,2,1,2,Returning_Visitor,FALSE,FALSE
1,54.5,0,0,68,3135.517677,0.003361345,0.01146836,4.095288919,0,Mar,1,1,2,1,Returning_Visitor,FALSE,FALSE
14,272.5,2,52.25,55,1127.288305,0.003125,0.014499164,0,0,Mar,3,2,7,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,25,954.4702381,0,0.012742857,0,0,Mar,3,2,1,1,Returning_Visitor,TRUE,FALSE
0,0,0,0,33,3506.166667,0,0.025,0,0,Mar,1,1,1,1,Returning_Visitor,TRUE,FALSE
0,0,0,0,19,370.3809524,0,0.007894737,0,0,Mar,1,1,1,2,Returning_Visitor,FALSE,FALSE
5,169,0,0,3,50,0,0.033333333,0,0,Mar,1,1,1,9,New_Visitor,FALSE,FALSE
4,59.25,0,0,9,139.25,0.015384615,0.031538462,0,0,Mar,3,2,1,2,Returning_Visitor,FALSE,FALSE
4,175,0,0,15,270.5,0,0.006666667,0,0,Mar,1,1,7,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,9,321,0.033333333,0.085185185,0,0,Mar,2,5,5,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
4,159,0,0,3,64.75,0,0.014285714,0,0,Mar,1,1,1,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,26.5,0,0.05,0,0,Mar,2,2,9,2,Returning_Visitor,TRUE,FALSE
0,0,0,0,14,927.2777778,0,0.014285714,0,0,Mar,2,2,1,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,7,141.1666667,0,0.007142857,0,0,Mar,3,2,3,1,Returning_Visitor,FALSE,FALSE
11,247.3333333,2,369,90,7221,0.001030928,0.003917526,13.46406308,0,Mar,2,2,3,8,Returning_Visitor,FALSE,TRUE
0,0,0,0,12,218.5,0,0.045833333,0,0,Mar,1,1,4,2,Returning_Visitor,FALSE,FALSE
2,78.33333333,0,0,12,262.5,0.028571429,0.033333333,0,0,Mar,1,1,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,17,469.4166667,0,0.011764706,0,0,Mar,1,1,2,2,Returning_Visitor,FALSE,FALSE
1,16,0,0,27,1240.916667,0,0.009259259,28.39335492,0,Mar,2,2,3,1,Returning_Visitor,FALSE,TRUE
1,8,0,0,5,143.5,0,0.011111111,0,0,Mar,3,2,2,3,New_Visitor,TRUE,FALSE
0,0,0,0,7,101,0.028571429,0.057142857,0,0,Mar,2,5,1,3,Returning_Visitor,FALSE,FALSE
5,267.5,0,0,5,62.5,0.022222222,0.044444444,0,0,Mar,2,2,2,3,New_Visitor,TRUE,FALSE
1,14,0,0,6,156,0,0.04,0,0,Mar,1,1,3,1,Returning_Visitor,TRUE,FALSE
0,0,0,0,6,104,0,0.033333333,0,0,Mar,3,2,7,6,Returning_Visitor,FALSE,FALSE
2,17,0,0,15,1349,0,0.005882353,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
1,12,0,0,11,331.25,0.016666667,0.033333333,0,0,Mar,2,2,2,2,Returning_Visitor,TRUE,FALSE
5,114.75,0,0,8,301.5,0,0.018181818,0,0,Mar,2,4,4,2,Returning_Visitor,TRUE,FALSE
0,0,0,0,8,157.5714286,0,0.025,0,0,Mar,3,2,2,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,1,1,4,9,Returning_Visitor,TRUE,FALSE
0,0,0,0,19,224.9583333,0,0.010526316,0,0,Mar,1,1,1,2,Returning_Visitor,FALSE,FALSE
1,10,0,0,39,1152.5,0.011965812,0.017802198,0,0,Mar,3,2,1,3,Returning_Visitor,FALSE,FALSE
10,164.5,1,3,61,2292.679762,0,0.009552239,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,9,329,0.022222222,0.044444444,0,0,Mar,2,2,3,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,8,111.6666667,0,0.025,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,15,1074.428571,0.015384615,0.021538462,0,0,Mar,3,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,32,1080.047619,0,0.01015625,0,0,Mar,2,2,7,2,Returning_Visitor,FALSE,FALSE
4,387.5,0,0,23,666.9464286,0.007692308,0.026089744,0,0,Mar,1,1,6,10,Returning_Visitor,FALSE,FALSE
2,123,0,0,14,239,0,0.0125,0,0,Mar,2,2,1,2,New_Visitor,TRUE,FALSE
4,272.5,0,0,14,279.9,0,0.028571429,0,0,Mar,1,1,3,10,New_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,2,2,7,11,Returning_Visitor,FALSE,FALSE
0,0,0,0,15,1674,0,0.04,0,0,Mar,2,2,4,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,15,0,0.066666667,0,0,Mar,2,4,3,1,Returning_Visitor,TRUE,FALSE
0,0,0,0,22,480.9666667,0.004848485,0.026652893,0,0,Mar,2,2,4,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,62,0,0.066666667,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
4,320.5,0,0,23,1841.171429,0,0.003913043,0,0,Mar,1,1,1,2,New_Visitor,TRUE,FALSE
0,0,0,0,2,37.5,0,0.033333333,0,0,Mar,3,2,4,3,Returning_Visitor,TRUE,FALSE
2,35,0,0,11,131.3,0,0.015384615,0,0,Mar,2,2,1,2,New_Visitor,FALSE,FALSE
0,0,0,0,2,92,0,0.1,0,0,Mar,2,2,8,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,78.33333333,0,0.022222222,0,0,Mar,2,2,7,11,Returning_Visitor,FALSE,FALSE
0,0,0,0,7,114.6,0.028571429,0.033333333,0,0,Mar,3,2,1,10,Returning_Visitor,FALSE,FALSE
2,34,0,0,18,671,0,0.010526316,0,0,Mar,3,2,3,11,New_Visitor,TRUE,FALSE
2,47,0,0,11,624,0,0.020512821,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
2,11,3,123.3333333,34,448.75,0.021621622,0.048648649,0,0,Mar,2,10,6,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,35,0,0.05,0,0,Mar,2,2,9,3,Returning_Visitor,FALSE,FALSE
3,13,0,0,7,79.5,0,0.02,0,0,Mar,2,2,1,8,New_Visitor,TRUE,FALSE
0,0,0,0,10,189.5,0,0.036666667,0,0,Mar,3,2,3,3,Returning_Visitor,FALSE,FALSE
2,36,0,0,15,2190.666667,0,0.004444444,0,0,Mar,2,2,3,8,Returning_Visitor,FALSE,FALSE
0,0,0,0,2,0,0.2,0.2,0,0,Mar,2,2,3,3,Returning_Visitor,TRUE,FALSE
0,0,0,0,2,0,0.2,0.2,0,0,Mar,1,1,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,5,672.5,0,0.04,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
3,33,0,0,67,2502.816667,0.006060606,0.011147186,0,0,Mar,4,1,1,10,Returning_Visitor,FALSE,FALSE
7,97,6,281.5,83,1778.125214,0.007967033,0.019990486,6.626647741,0,Mar,2,2,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,49.5,0.05,0.075,0,0,Mar,3,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,12,261,0.033333333,0.083333333,0,0,Mar,2,2,7,1,Returning_Visitor,FALSE,FALSE
1,37,0,0,12,663.5,0,0.016666667,10.83431037,0,Mar,3,2,6,8,New_Visitor,FALSE,TRUE
4,55,0,0,16,284.9,0.003333333,0.033333333,18.8649,0,Mar,1,1,2,10,Returning_Visitor,FALSE,FALSE
0,0,0,0,7,236,0.057142857,0.085714286,0,0,Mar,2,2,3,2,Returning_Visitor,FALSE,FALSE
3,26,0,0,19,576.0833333,0.009090909,0.018181818,30.65045455,0,Mar,2,2,2,1,Returning_Visitor,TRUE,TRUE
0,0,0,0,3,77,0,0.066666667,0,0,Mar,3,6,1,9,Returning_Visitor,TRUE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,79,0.066666667,0.166666667,0,0,Mar,1,1,3,3,Returning_Visitor,FALSE,FALSE
2,24.5,1,710,66,4566.952839,0.006470588,0.018141923,0,0,Mar,3,2,2,2,Returning_Visitor,FALSE,FALSE
1,24,3,125.5,65,8646,0,0.011764706,0,0,Mar,2,2,1,13,Returning_Visitor,TRUE,FALSE
0,0,0,0,17,600.5,0,0.005882353,0,0,Mar,2,2,7,10,Returning_Visitor,FALSE,FALSE
0,0,0,0,21,434.5,0,0.023809524,0,0,Mar,2,2,7,1,Returning_Visitor,FALSE,FALSE
1,0,0,0,35,499.4,0.011764706,0.028151261,0,0,Mar,2,2,3,1,Returning_Visitor,TRUE,FALSE
9,122,1,87,50,1694.797619,0.008928571,0.018154762,0,0,Mar,1,1,1,3,Returning_Visitor,TRUE,FALSE
1,123,0,0,7,181.5,0,0.025,64.7325,0,Mar,2,2,1,2,New_Visitor,TRUE,TRUE
3,308,0,0,54,1306.151974,0.003508772,0.012962963,0,0,Mar,2,2,4,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,6,75,0,0.016666667,0,0,Mar,1,1,1,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,6,61,0,0.066666667,0,0,Mar,2,4,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,12,1165.333333,0.004166667,0.043055556,0,0,Mar,2,2,3,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,3,2,5,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,6,70.83333333,0,0.016666667,0,0,Mar,2,2,8,2,Returning_Visitor,FALSE,FALSE
5,72.5,0,0,31,649.3071429,0,0.001041667,35.10378279,0,Mar,2,7,2,2,Returning_Visitor,TRUE,TRUE
1,21,1,61,49,1647.152381,0,0.0008,144.3934888,0,Mar,2,2,7,2,Returning_Visitor,TRUE,TRUE
6,233.0833333,2,63,60,3135.442572,0.001666667,0.009358814,0,0,Mar,3,2,1,10,Returning_Visitor,FALSE,FALSE
0,0,0,0,9,181.3333333,0.02962963,0.055026455,0,0,Mar,2,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,9,159,0,0.022222222,0,0,Mar,2,2,1,2,Returning_Visitor,TRUE,FALSE
4,315,0,0,8,465.8333333,0,0.024242424,0,0,Mar,3,2,3,3,Returning_Visitor,TRUE,FALSE
0,0,0,0,3,112,0.066666667,0.133333333,0,0,Mar,2,2,7,10,Returning_Visitor,FALSE,FALSE
0,0,0,0,40,952.9666667,0.001666667,0.016666667,0,0,Mar,1,1,2,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,8,372.8333333,0,0.0125,0,0,Mar,1,1,1,1,Returning_Visitor,FALSE,FALSE
6,192.5,0,0,14,327,0,0.00625,0,0,Mar,1,1,1,9,Returning_Visitor,TRUE,FALSE
0,0,0,0,1,0,0.2,0.2,0,0,Mar,2,2,2,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,6,1057,0,0.033333333,0,0,Mar,2,4,4,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,12,0,0.066666667,0,0,Mar,2,2,1,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,1,36,0,0.066666667,0,0,Mar,3,2,6,2,Returning_Visitor,TRUE,FALSE
3,43.5,0,0,30,2264.333333,0,0.010416667,0,0,Mar,2,2,1,3,Returning_Visitor,TRUE,FALSE
4,76,0,0,28,866,0,0.02183908,0,0,Mar,2,2,4,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,97,0,0.05,0,0,Mar,2,2,2,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,17,701.5424242,0.013333333,0.026666667,0,0,Mar,2,2,6,2,Returning_Visitor,FALSE,FALSE
2,35,0,0,20,979.0833333,0,0.00952381,60.04549665,0,Mar,2,2,3,2,Returning_Visitor,FALSE,TRUE
3,13,0,0,28,324.7692308,0,0.001724138,0,0,Mar,2,2,1,6,Returning_Visitor,FALSE,FALSE
6,160.0952381,3,94.5,47,1682.870247,0.001333333,0.007891429,5.698642857,0,Mar,3,2,6,10,Returning_Visitor,FALSE,TRUE
0,0,0,0,9,210,0.044444444,0.055555556,0,0,Mar,1,1,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,20,332,0.03,0.06,0,0,Mar,4,1,3,1,Returning_Visitor,FALSE,FALSE
1,45,0,0,13,1610.916667,0,0.007142857,0,0,Mar,1,1,1,3,New_Visitor,TRUE,FALSE
4,177.1666667,0,0,50,1188.566667,0.007843137,0.018300654,0,0,Mar,2,2,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,98,0,0.066666667,0,0,Mar,2,6,7,1,Returning_Visitor,FALSE,FALSE
0,0,1,36.33333333,38,1663.683333,0.005405405,0.022972973,0,0,Mar,2,2,4,1,Returning_Visitor,FALSE,FALSE
4,43.5,0,0,39,930.3,0.001190476,0.010997732,0,0,Mar,4,5,1,3,Returning_Visitor,TRUE,FALSE
0,0,0,0,21,1003,0,0.008333333,0,0,Mar,2,4,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,69,0,0.066666667,0,0,Mar,2,2,2,6,Returning_Visitor,FALSE,FALSE
0,0,0,0,27,1199.725758,0.007407407,0.01691358,9.028406684,0,Mar,1,1,2,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,34,1524.058333,0.019393939,0.025282904,11.77367361,0,Mar,3,2,3,1,Returning_Visitor,FALSE,FALSE
0,0,2,45,11,624,0.015384615,0.046153846,0,0,Mar,2,2,4,10,Returning_Visitor,FALSE,FALSE
0,0,0,0,37,1229.766667,0.005405405,0.014414414,0,0,Mar,2,2,1,3,Returning_Visitor,TRUE,FALSE
0,0,0,0,13,972.6,0,0.007692308,0,0,Mar,2,2,3,10,Returning_Visitor,FALSE,FALSE
5,159,0,0,17,438.4333333,0.003030303,0.027272727,0,0,Mar,1,1,3,3,Returning_Visitor,FALSE,FALSE
0,0,0,0,10,270,0,0.004,0,0,Mar,2,2,1,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,3,333,0,0.066666667,0,0,Mar,2,2,2,1,Returning_Visitor,TRUE,FALSE
0,0,0,0,20,504.2333333,0.01,0.021666667,0,0,Mar,3,2,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,27,845.5,0,0.007407407,0,0,Mar,4,1,1,11,Returning_Visitor,TRUE,FALSE
1,54,1,237,16,744.5,0.013333333,0.033777778,0,0,Mar,2,2,6,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,21,1129,0.00952381,0.038095238,0,0,Mar,2,5,5,1,Returning_Visitor,FALSE,FALSE
2,34,0,0,8,358,0,0.02,0,0,Mar,2,2,1,2,Returning_Visitor,FALSE,FALSE
0,0,0,0,24,832,0,0.020289855,21.92521348,0,Mar,2,6,6,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,4,36.5,0,0.05,0,0,Mar,2,2,7,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,7,157,0,0.014285714,0,0,Mar,3,2,1,2,Returning_Visitor,FALSE,FALSE
3,36,0,0,9,71.33333333,0,0.02,0,0,Mar,2,2,1,11,New_Visitor,FALSE,FALSE
7,196,3,138.5,11,227.5,0,0.006666667,0,0,Mar,3,2,5,8,New_Visitor,TRUE,FALSE
1,0,2,56,22,1054.309524,0.004761905,0.023809524,0,0,Mar,1,1,1,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,6,308.1666667,0.083333333,0.095,0,0,Mar,1,1,6,1,Returning_Visitor,FALSE,FALSE
0,0,0,0,10,229.25,0,0.06,0,0,Mar,1,1,6,2,Returning_Visitor,FALSE,FALSE
0,0,1,29,9,225.8333333,0,0.02,0,0,Mar,2,2,1,3,Returning_Visitor,TRUE,FALSE
2,21,1,26,22,326.5833333,0.018181818,0.066666667,0,0,Mar,3,2,4
gitextract_o39wik8g/
├── .gitignore
├── README.md
├── week0/
│ ├── degrees/
│ │ ├── degrees.py
│ │ ├── small/
│ │ │ ├── movies.csv
│ │ │ ├── people.csv
│ │ │ └── stars.csv
│ │ └── util.py
│ └── tictactoe/
│ ├── requirements.txt
│ ├── runner.py
│ └── tictactoe.py
├── week1/
│ ├── knights/
│ │ ├── logic.py
│ │ └── puzzle.py
│ └── minesweeper/
│ ├── minesweeper.py
│ ├── requirements.txt
│ └── runner.py
├── week2/
│ ├── heredity/
│ │ └── heredity.py
│ └── pagerank/
│ └── pagerank.py
├── week3/
│ └── crossword/
│ ├── crossword.py
│ ├── data/
│ │ ├── structure0.txt
│ │ ├── structure1.txt
│ │ ├── structure2.txt
│ │ ├── words0.txt
│ │ ├── words1.txt
│ │ └── words2.txt
│ └── generate.py
├── week4/
│ ├── nim/
│ │ ├── nim.py
│ │ └── play.py
│ └── shopping/
│ ├── shopping.csv
│ └── shopping.py
├── week5/
│ └── traffic/
│ └── traffic.py
└── week6/
├── parser/
│ ├── parser.py
│ └── sentences/
│ ├── 1.txt
│ ├── 10.txt
│ ├── 2.txt
│ ├── 3.txt
│ ├── 4.txt
│ ├── 5.txt
│ ├── 6.txt
│ ├── 7.txt
│ ├── 8.txt
│ ├── 9.txt
│ └── test.txt
└── questions/
├── corpus/
│ ├── artificial_intelligence.txt
│ ├── machine_learning.txt
│ ├── natural_language_processing.txt
│ ├── neural_network.txt
│ ├── probability.txt
│ └── python.txt
└── questions.py
SYMBOL INDEX (170 symbols across 15 files)
FILE: week0/degrees/degrees.py
function load_data (line 16) | def load_data(directory):
function main (line 56) | def main():
function shortest_path (line 88) | def shortest_path(source, target):
function person_id_for_name (line 140) | def person_id_for_name(name):
function neighbors_for_person (line 166) | def neighbors_for_person(person_id):
FILE: week0/degrees/util.py
class Node (line 1) | class Node():
method __init__ (line 2) | def __init__(self, state, parent, action):
class StackFrontier (line 8) | class StackFrontier():
method __init__ (line 9) | def __init__(self):
method add (line 12) | def add(self, node):
method contains_state (line 15) | def contains_state(self, state):
method empty (line 18) | def empty(self):
method remove (line 21) | def remove(self):
class QueueFrontier (line 30) | class QueueFrontier(StackFrontier):
method remove (line 32) | def remove(self):
FILE: week0/tictactoe/tictactoe.py
function initial_state (line 13) | def initial_state():
function player (line 22) | def player(board):
function actions (line 39) | def actions(board):
function result (line 54) | def result(board, action):
function winner (line 71) | def winner(board):
function terminal (line 96) | def terminal(board):
function utility (line 113) | def utility(board):
function minimax (line 128) | def minimax(board):
FILE: week1/knights/logic.py
class Sentence (line 4) | class Sentence():
method evaluate (line 6) | def evaluate(self, model):
method formula (line 10) | def formula(self):
method symbols (line 14) | def symbols(self):
method validate (line 19) | def validate(cls, sentence):
method parenthesize (line 24) | def parenthesize(cls, s):
class Symbol (line 45) | class Symbol(Sentence):
method __init__ (line 47) | def __init__(self, name):
method __eq__ (line 50) | def __eq__(self, other):
method __hash__ (line 53) | def __hash__(self):
method __repr__ (line 56) | def __repr__(self):
method evaluate (line 59) | def evaluate(self, model):
method formula (line 65) | def formula(self):
method symbols (line 68) | def symbols(self):
class Not (line 72) | class Not(Sentence):
method __init__ (line 73) | def __init__(self, operand):
method __eq__ (line 77) | def __eq__(self, other):
method __hash__ (line 80) | def __hash__(self):
method __repr__ (line 83) | def __repr__(self):
method evaluate (line 86) | def evaluate(self, model):
method formula (line 89) | def formula(self):
method symbols (line 92) | def symbols(self):
class And (line 96) | class And(Sentence):
method __init__ (line 97) | def __init__(self, *conjuncts):
method __eq__ (line 102) | def __eq__(self, other):
method __hash__ (line 105) | def __hash__(self):
method __repr__ (line 110) | def __repr__(self):
method add (line 116) | def add(self, conjunct):
method evaluate (line 120) | def evaluate(self, model):
method formula (line 123) | def formula(self):
method symbols (line 129) | def symbols(self):
class Or (line 133) | class Or(Sentence):
method __init__ (line 134) | def __init__(self, *disjuncts):
method __eq__ (line 139) | def __eq__(self, other):
method __hash__ (line 142) | def __hash__(self):
method __repr__ (line 147) | def __repr__(self):
method evaluate (line 151) | def evaluate(self, model):
method formula (line 154) | def formula(self):
method symbols (line 160) | def symbols(self):
class Implication (line 164) | class Implication(Sentence):
method __init__ (line 165) | def __init__(self, antecedent, consequent):
method __eq__ (line 171) | def __eq__(self, other):
method __hash__ (line 176) | def __hash__(self):
method __repr__ (line 179) | def __repr__(self):
method evaluate (line 182) | def evaluate(self, model):
method formula (line 186) | def formula(self):
method symbols (line 191) | def symbols(self):
class Biconditional (line 195) | class Biconditional(Sentence):
method __init__ (line 196) | def __init__(self, left, right):
method __eq__ (line 202) | def __eq__(self, other):
method __hash__ (line 207) | def __hash__(self):
method __repr__ (line 210) | def __repr__(self):
method evaluate (line 213) | def evaluate(self, model):
method formula (line 219) | def formula(self):
method symbols (line 224) | def symbols(self):
function model_check (line 228) | def model_check(knowledge, query):
FILE: week1/knights/puzzle.py
function main (line 122) | def main():
FILE: week1/minesweeper/minesweeper.py
class Minesweeper (line 6) | class Minesweeper():
method __init__ (line 11) | def __init__(self, height=8, width=8, mines=8):
method print (line 37) | def print(self):
method is_mine (line 52) | def is_mine(self, cell):
method nearby_mines (line 56) | def nearby_mines(self, cell):
method won (line 81) | def won(self):
class Sentence (line 88) | class Sentence():
method __init__ (line 95) | def __init__(self, cells, count):
method __eq__ (line 99) | def __eq__(self, other):
method __str__ (line 102) | def __str__(self):
method known_mines (line 105) | def known_mines(self):
method known_safes (line 112) | def known_safes(self):
method mark_mine (line 119) | def mark_mine(self, cell):
method mark_safe (line 130) | def mark_safe(self, cell):
class MinesweeperAI (line 141) | class MinesweeperAI():
method __init__ (line 146) | def __init__(self, height=8, width=8):
method mark_mine (line 162) | def mark_mine(self, cell):
method mark_safe (line 171) | def mark_safe(self, cell):
method add_knowledge (line 180) | def add_knowledge(self, cell, count):
method return_close_cells (line 230) | def return_close_cells(self, cell):
method check_knowledge (line 242) | def check_knowledge(self):
method extra_inference (line 272) | def extra_inference(self):
method make_safe_move (line 302) | def make_safe_move(self):
method make_random_move (line 318) | def make_random_move(self):
FILE: week2/heredity/heredity.py
function main (line 40) | def main():
function load_data (line 97) | def load_data(filename):
function powerset (line 119) | def powerset(s):
function joint_probability (line 131) | def joint_probability(people, one_gene, two_genes, have_trait):
function update (line 180) | def update(probabilities, one_gene, two_genes, have_trait, p):
function normalize (line 193) | def normalize(probabilities):
FILE: week2/pagerank/pagerank.py
function main (line 10) | def main():
function crawl (line 24) | def crawl(directory):
function transition_model (line 51) | def transition_model(corpus, page, damping_factor):
function sample_pagerank (line 86) | def sample_pagerank(corpus, damping_factor, n):
function iterate_pagerank (line 124) | def iterate_pagerank(corpus, damping_factor):
FILE: week3/crossword/crossword.py
class Variable (line 1) | class Variable():
method __init__ (line 6) | def __init__(self, i, j, direction, length):
method __hash__ (line 19) | def __hash__(self):
method __eq__ (line 22) | def __eq__(self, other):
method __str__ (line 30) | def __str__(self):
method __repr__ (line 33) | def __repr__(self):
class Crossword (line 38) | class Crossword():
method __init__ (line 40) | def __init__(self, structure_file, words_file):
method neighbors (line 128) | def neighbors(self, var):
FILE: week3/crossword/generate.py
class CrosswordCreator (line 7) | class CrosswordCreator():
method __init__ (line 9) | def __init__(self, crossword):
method letter_grid (line 19) | def letter_grid(self, assignment):
method print (line 35) | def print(self, assignment):
method save (line 48) | def save(self, assignment, filename):
method solve (line 89) | def solve(self):
method enforce_node_consistency (line 97) | def enforce_node_consistency(self):
method revise (line 117) | def revise(self, x, y):
method ac3 (line 155) | def ac3(self, arcs=None):
method assignment_complete (line 183) | def assignment_complete(self, assignment):
method consistent (line 193) | def consistent(self, assignment):
method order_domain_values (line 222) | def order_domain_values(self, var, assignment):
method select_unassigned_variable (line 257) | def select_unassigned_variable(self, assignment):
method backtrack (line 281) | def backtrack(self, assignment):
function main (line 310) | def main():
FILE: week4/nim/nim.py
class Nim (line 6) | class Nim():
method __init__ (line 8) | def __init__(self, initial=[1, 3, 5, 7]):
method available_actions (line 21) | def available_actions(cls, piles):
method other_player (line 36) | def other_player(cls, player):
method switch_player (line 43) | def switch_player(self):
method move (line 49) | def move(self, action):
class NimAI (line 73) | class NimAI():
method __init__ (line 75) | def __init__(self, alpha=0.5, epsilon=0.1):
method update (line 89) | def update(self, old_state, action, new_state, reward):
method get_q_value (line 99) | def get_q_value(self, state, action):
method update_q_value (line 109) | def update_q_value(self, state, action, old_q, reward, future_rewards):
method best_future_reward (line 127) | def best_future_reward(self, state):
method choose_action (line 145) | def choose_action(self, state, epsilon=True):
function train (line 188) | def train(n):
function play (line 247) | def play(ai, human_player=None):
FILE: week4/shopping/shopping.py
function main (line 12) | def main():
function load_data (line 36) | def load_data(filename):
function train_model (line 105) | def train_model(evidence, labels):
function evaluate (line 116) | def evaluate(labels, predictions):
FILE: week5/traffic/traffic.py
function main (line 16) | def main():
function load_data (line 49) | def load_data(data_dir):
function get_model (line 80) | def get_model():
FILE: week6/parser/parser.py
function main (line 30) | def main():
function preprocess (line 63) | def preprocess(sentence):
function np_chunk (line 75) | def np_chunk(tree):
FILE: week6/questions/questions.py
function main (line 11) | def main():
function load_files (line 49) | def load_files(directory):
function tokenize (line 63) | def tokenize(document):
function compute_idfs (line 79) | def compute_idfs(documents):
function top_files (line 103) | def top_files(query, files, idfs, n):
function top_sentences (line 123) | def top_sentences(query, sentences, idfs, n):
Condensed preview — 49 files, each showing path, character count, and a content snippet. Download the .json file or copy for the full structured content (1,471K chars).
[
{
"path": ".gitignore",
"chars": 63,
"preview": "*.zip\n*.pyc\n\n__pycache__/\n.venv/\nvenv/\n.idea/\n\n*/degrees/large/"
},
{
"path": "README.md",
"chars": 490,
"preview": "# CS50 AI \nMine solutions for CS50's Introduction to Artificial Intelligence with Python course\n\n*Warning : before visit"
},
{
"path": "week0/degrees/degrees.py",
"chars": 5030,
"preview": "import csv\nimport sys\n\nfrom util import Node, StackFrontier, QueueFrontier\n\n# Maps names to a set of corresponding perso"
},
{
"path": "week0/degrees/small/movies.csv",
"chars": 148,
"preview": "id,title,year\n112384,\"Apollo 13\",1995\n104257,\"A Few Good Men\",1992\n109830,\"Forrest Gump\",1994\n93779,\"The Princess Bride\""
},
{
"path": "week0/degrees/small/people.csv",
"chars": 405,
"preview": "id,name,birth\n102,\"Kevin Bacon\",1958\n129,\"Tom Cruise\",1962\n144,\"Cary Elwes\",1962\n158,\"Tom Hanks\",1956\n1597,\"Mandy Patink"
},
{
"path": "week0/degrees/small/stars.csv",
"chars": 236,
"preview": "person_id,movie_id\n102,104257\n102,112384\n129,104257\n129,95953\n144,93779\n158,109830\n158,112384\n1597,93779\n163,95953\n1697,"
},
{
"path": "week0/degrees/util.py",
"chars": 916,
"preview": "class Node():\n def __init__(self, state, parent, action):\n self.state = state\n self.parent = parent\n "
},
{
"path": "week0/tictactoe/requirements.txt",
"chars": 7,
"preview": "pygame\n"
},
{
"path": "week0/tictactoe/runner.py",
"chars": 4709,
"preview": "import pygame\nimport sys\nimport time\n\nimport tictactoe as ttt\n\npygame.init()\nsize = width, height = 600, 400\n\n# Colors\nb"
},
{
"path": "week0/tictactoe/tictactoe.py",
"chars": 3620,
"preview": "\"\"\"\nTic Tac Toe Player\n\"\"\"\n\nimport math\nfrom copy import deepcopy\n\nX = \"X\"\nO = \"O\"\nEMPTY = None\n\n\ndef initial_state():\n "
},
{
"path": "week1/knights/logic.py",
"chars": 7897,
"preview": "import itertools\n\n\nclass Sentence():\n\n def evaluate(self, model):\n \"\"\"Evaluates the logical sentence.\"\"\"\n "
},
{
"path": "week1/knights/puzzle.py",
"chars": 4103,
"preview": "from logic import *\n\nAKnight = Symbol(\"A is a Knight\")\nAKnave = Symbol(\"A is a Knave\")\n\nBKnight = Symbol(\"B is a Knight\""
},
{
"path": "week1/minesweeper/minesweeper.py",
"chars": 10924,
"preview": "import itertools\nimport random\nimport copy\n\n\nclass Minesweeper():\n \"\"\"\n Minesweeper game representation\n \"\"\"\n\n "
},
{
"path": "week1/minesweeper/requirements.txt",
"chars": 7,
"preview": "pygame\n"
},
{
"path": "week1/minesweeper/runner.py",
"chars": 6910,
"preview": "import pygame\nimport sys\nimport time\n\nfrom minesweeper import Minesweeper, MinesweeperAI\n\nHEIGHT = 8\nWIDTH = 8\nMINES = 8"
},
{
"path": "week2/heredity/heredity.py",
"chars": 6588,
"preview": "import csv\nimport itertools\nimport sys\n\nPROBS = {\n\n # Unconditional probabilities for having gene\n \"gene\": {\n "
},
{
"path": "week2/pagerank/pagerank.py",
"chars": 5203,
"preview": "import os\nimport random\nimport re\nimport sys\n\nDAMPING = 0.85\nSAMPLES = 10000\n\n\ndef main():\n if len(sys.argv) != 2:\n "
},
{
"path": "week3/crossword/crossword.py",
"chars": 4613,
"preview": "class Variable():\n\n ACROSS = \"across\"\n DOWN = \"down\"\n\n def __init__(self, i, j, direction, length):\n \"\"\""
},
{
"path": "week3/crossword/data/structure0.txt",
"chars": 30,
"preview": "#___#\n#_##_\n#_##_\n#_##_\n#____\n"
},
{
"path": "week3/crossword/data/structure1.txt",
"chars": 135,
"preview": "##############\n#######_####_#\n#____________#\n#_#####_####_#\n#_##_____###_#\n#_#####_####_#\n#_###______#_#\n#######_####_#\n"
},
{
"path": "week3/crossword/data/structure2.txt",
"chars": 48,
"preview": "######_\n____##_\n_##____\n_##_##_\n_##_##_\n#___##_\n"
},
{
"path": "week3/crossword/data/words0.txt",
"chars": 49,
"preview": "one\ntwo\nthree\nfour\nfive\nsix\nseven\neight\nnine\nten\n"
},
{
"path": "week3/crossword/data/words1.txt",
"chars": 418,
"preview": "adversarial\nalpha\narc\nartificial\nbayes\nbeta\nbit\nbreadth\nbyte\nclassification\nclassify\ncondition\nconstraint\ncreate\ndepth\nd"
},
{
"path": "week3/crossword/data/words2.txt",
"chars": 22224,
"preview": "a\nabandon\nability\nable\nabortion\nabout\nabove\nabroad\nabsence\nabsolute\nabsolutely\nabsorb\nabuse\nacademic\naccept\naccess\naccid"
},
{
"path": "week3/crossword/generate.py",
"chars": 12551,
"preview": "import sys\nimport copy\n\nfrom crossword import *\n\n\nclass CrosswordCreator():\n\n def __init__(self, crossword):\n "
},
{
"path": "week4/nim/nim.py",
"chars": 9062,
"preview": "import math\nimport random\nimport time\n\n\nclass Nim():\n\n def __init__(self, initial=[1, 3, 5, 7]):\n \"\"\"\n "
},
{
"path": "week4/nim/play.py",
"chars": 56,
"preview": "from nim import train, play\n\nai = train(10000)\nplay(ai)\n"
},
{
"path": "week4/shopping/shopping.csv",
"chars": 1059732,
"preview": "Administrative,Administrative_Duration,Informational,Informational_Duration,ProductRelated,ProductRelated_Duration,Bounc"
},
{
"path": "week4/shopping/shopping.py",
"chars": 4401,
"preview": "import csv\nimport pandas\nimport sys\n\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.neighbors import "
},
{
"path": "week5/traffic/traffic.py",
"chars": 3713,
"preview": "import cv2\nimport numpy as np\nimport os\nimport sys\nimport tensorflow as tf\n\nfrom sklearn.model_selection import train_te"
},
{
"path": "week6/parser/parser.py",
"chars": 2393,
"preview": "import nltk\nimport sys\nimport string\n\nTERMINALS = \"\"\"\nAdj -> \"country\" | \"dreadful\" | \"enigmatical\" | \"little\" | \"moist\""
},
{
"path": "week6/parser/sentences/1.txt",
"chars": 12,
"preview": "Holmes sat.\n"
},
{
"path": "week6/parser/sentences/10.txt",
"chars": 55,
"preview": "I had a little moist red paint in the palm of my hand.\n"
},
{
"path": "week6/parser/sentences/2.txt",
"chars": 19,
"preview": "Holmes lit a pipe.\n"
},
{
"path": "week6/parser/sentences/3.txt",
"chars": 36,
"preview": "We arrived the day before Thursday.\n"
},
{
"path": "week6/parser/sentences/4.txt",
"chars": 48,
"preview": "Holmes sat in the red armchair and he chuckled.\n"
},
{
"path": "week6/parser/sentences/5.txt",
"chars": 42,
"preview": "My companion smiled an enigmatical smile. "
},
{
"path": "week6/parser/sentences/6.txt",
"chars": 28,
"preview": "Holmes chuckled to himself.\n"
},
{
"path": "week6/parser/sentences/7.txt",
"chars": 53,
"preview": "She never said a word until we were at the door here."
},
{
"path": "week6/parser/sentences/8.txt",
"chars": 34,
"preview": "Holmes sat down and lit his pipe.\n"
},
{
"path": "week6/parser/sentences/9.txt",
"chars": 67,
"preview": "I had a country walk on Thursday and came home in a dreadful mess.\n"
},
{
"path": "week6/parser/sentences/test.txt",
"chars": 0,
"preview": ""
},
{
"path": "week6/questions/corpus/artificial_intelligence.txt",
"chars": 100263,
"preview": "https://en.wikipedia.org/wiki/Artificial_intelligence\n\nIn computer science, artificial intelligence (AI), sometimes call"
},
{
"path": "week6/questions/corpus/machine_learning.txt",
"chars": 42327,
"preview": "https://en.wikipedia.org/wiki/Machine_learning\n\nMachine learning (ML) is the study of computer algorithms that improve a"
},
{
"path": "week6/questions/corpus/natural_language_processing.txt",
"chars": 20039,
"preview": "https://en.wikipedia.org/wiki/Natural_language_processing\n\nNatural language processing (NLP) is a subfield of linguistic"
},
{
"path": "week6/questions/corpus/neural_network.txt",
"chars": 35710,
"preview": "https://en.wikipedia.org/wiki/Neural_network\n\nArtificial neural networks (ANN) or connectionist systems are computing sy"
},
{
"path": "week6/questions/corpus/probability.txt",
"chars": 26573,
"preview": "https://en.wikipedia.org/wiki/Probability\n\nProbability is a numerical description of how likely an event is to occur or "
},
{
"path": "week6/questions/corpus/python.txt",
"chars": 38870,
"preview": "https://en.wikipedia.org/wiki/Python_(programming_language)\n\nevel, general-purpose programming language. Created by Guid"
},
{
"path": "week6/questions/questions.py",
"chars": 4409,
"preview": "import nltk\nimport sys\nimport os\nimport string\nimport math\n\nFILE_MATCHES = 1\nSENTENCE_MATCHES = 1\n\n\ndef main():\n\n # C"
}
]
About this extraction
This page contains the full source code of the wbsth/cs50ai GitHub repository, extracted and formatted as plain text for AI agents and large language models (LLMs). The extraction includes 49 files (1.4 MB), approximately 677.4k tokens, and a symbol index with 170 extracted functions, classes, methods, constants, and types. Use this with OpenClaw, Claude, ChatGPT, Cursor, Windsurf, or any other AI tool that accepts text input. You can copy the full output to your clipboard or download it as a .txt file.
Extracted by GitExtract — free GitHub repo to text converter for AI. Built by Nikandr Surkov.