Repository: ropenscilabs/r-docker-tutorial Branch: gh-pages Commit: c4428c6af0fe Files: 25 Total size: 6.2 MB Directory structure: gitextract_zmrekp_n/ ├── .gitattributes ├── .gitignore ├── 01-what-and-why.Rmd ├── 01-what-and-why.html ├── 02-Launching-Docker.Rmd ├── 02-Launching-Docker.html ├── 03-install-packages.Rmd ├── 03-install-packages.html ├── 04-Dockerhub.Rmd ├── 04-Dockerhub.html ├── 05-dockerfiles.Rmd ├── 05-dockerfiles.html ├── 06-Sharing-all-your-analysis.Rmd ├── 06-Sharing-all-your-analysis.html ├── Makefile ├── README.md ├── data/ │ └── gapminder-FiveYearData.csv ├── index.html ├── instructors.md ├── javascripts/ │ └── scale.fix.js ├── params.json ├── r-docker-tutorial.Rmd ├── stylesheets/ │ ├── github-light.css │ └── styles.css └── supplemental.md ================================================ FILE CONTENTS ================================================ ================================================ FILE: .gitattributes ================================================ *.html linguist-vendored stylesheets/*.css linguist-vendored javascripts/*.js linguist-vendored *.Rmd linguist-language=R ================================================ FILE: .gitignore ================================================ .Rhistory *_cache ================================================ FILE: 01-what-and-why.Rmd ================================================ --- title: "What is Docker and Why should I use it?" output: dcTemplate::dc_lesson_template: fig_width: 6 fig_height: 6 highlight: pygments --- ```{r knitr_init, echo = FALSE, cache = FALSE} library(knitr) ## Global options options(max.print = "75") opts_chunk$set(cache = TRUE, prompt = FALSE, tidy = TRUE, comment = "> #", message = FALSE, warning = FALSE) opts_knit$set(width = 75) ``` ## Lesson Objectives - Understanding the basic idea of Docker - Seeing the point of why Docker is useful ## Why would I want to use Docker? Imagine you are working on an analysis in R and you send your code to a friend. Your friend runs exactly this code on exactly the same data set but gets a slightly different result. This can have various reasons such as a different operating system, a different version of an R package, et cetera. Docker is trying to solve problems like that. **A Docker container can be seen as a computer inside your computer**. The cool thing about this virtual computer is that you can send it to your friends; And when they start this computer and run your code they will get exactly the same results as you did. ![Computerception](files/computer.jpg) In short, you should use Docker because - it allows you to **wrangle dependencies** starting from the operating system up to details such as R and Latex package versions - it makes sure that your analyses are **reproducible**. There are a couple of other points what Docker helps with: - Portability: Since a Docker container can easily be sent to another machine, you can set up everything on your own computer and then run the analyses on e.g. a more powerful machine. - Sharability: You can send the Docker container to anyone (who knows how to work with Docker). ## Basic vocabulary The words *image* and *container* will come up a lot in the following. An instance of an image is called container. An image is the setup of the virtual computer. If you run this image, you will have an instance of it, which we call container. You can have many running containers of the same image. Next: Go to [Lesson 02 Launching Docker](02-Launching-Docker.html) or back to the [main page](http://jsta.github.io/r-docker-tutorial/). ================================================ FILE: 01-what-and-why.html ================================================ What is Docker and Why should I use it?

Lesson Objectives

  • Understanding the basic idea of Docker
  • Seeing the point of why Docker is useful

Why would I want to use Docker?

Imagine you are working on an analysis in R and you send your code to a friend. Your friend runs exactly this code on exactly the same data set but gets a slightly different result. This can have various reasons such as a different operating system, a different version of an R package, et cetera. Docker is trying to solve problems like that.

A Docker container can be seen as a computer inside your computer. The cool thing about this virtual computer is that you can send it to your friends; And when they start this computer and run your code they will get exactly the same results as you did.

Computerception

In short, you should use Docker because

  • it allows you to wrangle dependencies starting from the operating system up to details such as R and Latex package versions
  • it makes sure that your analyses are reproducible.

There are a couple of other points what Docker helps with:

  • Portability: Since a Docker container can easily be sent to another machine, you can set up everything on your own computer and then run the analyses on e.g. a more powerful machine.
  • Sharability: You can send the Docker container to anyone (who knows how to work with Docker).

Basic vocabulary

The words image and container will come up a lot in the following. An instance of an image is called container. An image is the setup of the virtual computer. If you run this image, you will have an instance of it, which we call container. You can have many running containers of the same image.

Next: Go to Lesson 02 Launching Docker or back to the main page.

================================================ FILE: 02-Launching-Docker.Rmd ================================================ --- title: "Launching RStudio in Docker" output: dcTemplate::dc_lesson_template: fig_width: 6 fig_height: 6 highlight: pygments --- ```{r knitr_init, echo = FALSE, cache = FALSE} library(knitr) ## Global options options(max.print = "75") opts_chunk$set(cache = TRUE, prompt = FALSE, tidy = TRUE, comment = "> #", message = FALSE, warning = FALSE) opts_knit$set(width = 75) ``` ## Lesson Objectives - Launch RStudio inside of a Docker container - Linking a volume to a Docker container - Load into the container plotting it ## Installation First things first: [install Docker](https://docs.docker.com/engine/getstarted/step_one/). The install guide links to a bunch of introductory material after installation is complete; it's not necessary to complete those tutorials for this lesson, but they are an excellent introduction to basic Docker usage. ## Launching RStudio in Docker The first thing we need to do to launch Docker is to open a Unix Shell. If you're on Mac or Windows, in the last step you installed something called the *Docker Quickstart Terminal*; open that up now - it should look like a plain shell prompt (`~$`), but really it's pointing at a linux virtual machine that Docker likes to run in, and this is where you should do everything for the rest of this tutorial unless otherwise noted. If you're on a linux machine, then you can use a plain old terminal prompt. On a Mac you can also go to your terminal of choice and configure it for Docker usage. Especially if you get the error *Cannot connect to the Docker daemon. Is the docker daemon running on this host?* at some point in the tutorial, running the following command might fix your problem: ~~~ eval "$(docker-machine env default)" ~~~ Next, we will ask Docker to run an image that already exists, we will use the *verse* Docker image from [Rocker](https://github.com/rocker-org/rocker/wiki) which will allow us to run RStudio inside the container and has many useful R packages already installed. You need to set a password for RStudio using the -e environment flag. You will be asked to enter this when the container launches. ~~~ docker run --rm -p 8787:8787 -e PASSWORD=YOURNEWPASSWORD rocker/verse ~~~ Optional: *`p` and `--rm` are flags that allow you to customize how you run the container. `p` tells Docker that you will be using a port to see RStudio in your web browser (at a location which we specify afterwards as port `8787:8787`). Finally, --rm ensures that when we quit the container, the container is deleted. If we did not do this, everytime we run a container, a version of it will be saved to our local computer. This can lead to the eventual wastage of a lot of disk space until we manually remove these containers. Later we will show you how to save your container if you want to do so. If you try to run a Docker container which you have not installed locally then Docker will automatically search for the container on Docker Hub (an online repository for docker images) and download it if it exists.* The command above will lead RStudio-Server to launch invisibly. To connect to it, open a browser and enter `http://`, followed by your ip address, followed by `:8787`. If you are running a Mac or Windows machine, you will find the ip address on the first line of text that appeared in your terminal when you launched the Docker Quickstart Terminal. For example, you should see: ~~~ ## . ## ## ## == ## ## ## ## ## === /"""""""""""""""""\___/ === ~~~ {~~ ~~~~ ~~~ ~~~~ ~~~ ~ / ===- ~~~ \______ o __/ \ \ __/ \____\_______/ docker is configured to use the default machine with IP 192.168.99.100 For help getting started, check out the docs at https://docs.docker.com ~~~ Thus, you would enter `http://192.168.99.100:8787` in your browser as the url. If you are running a Mac or Linux machine, you can use `localhost` as the ip address. For example: `http://localhost:8787` This should lead to you being greeted by the RStudio welcome screen. Log in using: username: rstudio password: YOURNEWPASSWORD Now you should be able to work with RStudio in your browser in much the same way as you would on your desktop. The password you should use is the one you created when you used `docker run` above. The image below shows RStudio server running within a docker image. You should see something similar on your machine. ![install-pkgs](files/install-pkgs.png) Try to now look at your files of your virtual computer (docker container). Go to file -> open file. You will see that there are actually no files. The reason for this is that this image came with no files. Next, open a new R Script, e.g. by going to file -> New file -> R Script. Enter the following code in the script, run it and save it. ~~~ # make x the numbers from 1 to 5, and y the numbers from 6-10 x <- 1:5 y <- 6:10 # plot x against y plot(x, y) ~~~ If you look at your files again now, you will see the script file. Now, given that we used the `--rm` flag when we launched the Docker container, anything we create on the machine will be gone. Let's verify this. First, close the browser tab where you have RStudio open, and then go to your terminal window from where you launched the Docker container and type Contol+C. This shuts down the Docker container. Now relaunch your a Docker container using the RStudio image as you did previously, e.g., `docker run --rm -p 8787:8787 rocker/verse` in the terminal and typing `http://192.168.99.100:8787` in your browser window and see if the rscript and plot you saved is still there. ## Linking a volume to a Docker container to access data and save files That leads us to the question of, how can we save our work if the container is deleted when we exit the container? One solution is to link a volume (for example your local hard drive) to the container so that you can access the data there as well as being able to save things there. This time when we launch our container we will use the `-v` flag along with the path to our project's root directory. Your launch command should look something like this, although the path will differ depending on where you saved the data to on your computer. On the left hand side of the `:` is the path on your own computer, which you can get by doing `pwd` at the bash prompt from your project's root directory. On the right hand side is the path on the container; this should almost always start with `/home/rstudio/`. ~~~ docker run --rm -p 8787:8787 -v /Users/tiffanytimbers/Documents/DC/r-docker-tutorial:/home/rstudio/r-docker-tutorial rocker/verse ~~~ Again, you will have to enter something like `http://192.168.99.100:8787` in your browser as the url to get RStudio to run. This time when you launch RStudio in a Docker container and you try to open a file you should be able to see some files and directories. Now set the working directory to the directory called `r-docker-tutorial` and load the `gapminder-FiveYearData.csv` into R via `read.table`. ~~~ # load gapminder data from a csv on your computer gap5yr <- read.csv(file = 'data/gapminder-FiveYearData.csv') ~~~ Now lets plot GDP per capita against life expectancy. ~~~ # load ggplot library library(ggplot2) # plot GDP against life expectancy qplot(gap5yr$lifeExp, gap5yr$gdpPercap) # save the plot ggsave(filename = 'data/GDP_LifeExp.pdf') ~~~ Let's also save the script as `plot_GDP_LifeExp.R` in the `r-docker-tutorial` directory. Now close the RStudio browser and exit your Docker container via the terminal using Control+C. Then look inside the `r-docker-tutorial` and `r-docker-tutorial/data` directories on your laptop to see if you can see the two files you created. ## Summary In this lesson we learned how to launch a Docker container that allows us to run RStudio in a browser. We learned that using the `--rm` flag when we run Docker makes the container ephemeral; meaning that it is automatically deleted after we close the container. We do this as to not build up a large collection of containers on our machine and waste space. We also learned that we can link a volume of our laptop to the Docker container if we want to be able to access and save data, scripts and any other files. The container we used already had R, RStudio and several useful R packages installed. In later lessons we will learn how to modify this container to install new packages, and where we can find other Docker containers that might be useful for our work. ## Challenge Questions Open R or RStudio on your local machine and check which packages you have installed by typing `installed.packages()`. Compare with your neighbour if they match. Do the same in RStudio in your browser. Next: Go to [Lesson 03 Install packages](03-install-packages.html) or back to the [main page](http://jsta.github.io/r-docker-tutorial/). ================================================ FILE: 02-Launching-Docker.html ================================================ Launching RStudio in Docker 
## Warning: package 'knitr' was built under R version 4.1.2

Lesson Objectives

  • Launch RStudio inside of a Docker container
  • Linking a volume to a Docker container
  • Load into the container plotting it

Installation

First things first: install Docker. The install guide links to a bunch of introductory material after installation is complete; it’s not necessary to complete those tutorials for this lesson, but they are an excellent introduction to basic Docker usage.

Launching RStudio in Docker

The first thing we need to do to launch Docker is to open a Unix Shell. If you’re on Mac or Windows, in the last step you installed something called the Docker Quickstart Terminal; open that up now - it should look like a plain shell prompt (~$), but really it’s pointing at a linux virtual machine that Docker likes to run in, and this is where you should do everything for the rest of this tutorial unless otherwise noted. If you’re on a linux machine, then you can use a plain old terminal prompt.

On a Mac you can also go to your terminal of choice and configure it for Docker usage. Especially if you get the error Cannot connect to the Docker daemon. Is the docker daemon running on this host? at some point in the tutorial, running the following command might fix your problem:

eval "$(docker-machine env default)"

Next, we will ask Docker to run an image that already exists, we will use the verse Docker image from Rocker which will allow us to run RStudio inside the container and has many useful R packages already installed. You need to set a password for RStudio using the -e environment flag. You will be asked to enter this when the container launches.

docker run --rm -p 8787:8787 -e PASSWORD=YOURNEWPASSWORD rocker/verse

Optional: *p and --rm are flags that allow you to customize how you run the container. p tells Docker that you will be using a port to see RStudio in your web browser (at a location which we specify afterwards as port 8787:8787). Finally, –rm ensures that when we quit the container, the container is deleted. If we did not do this, everytime we run a container, a version of it will be saved to our local computer. This can lead to the eventual wastage of a lot of disk space until we manually remove these containers. Later we will show you how to save your container if you want to do so.

If you try to run a Docker container which you have not installed locally then Docker will automatically search for the container on Docker Hub (an online repository for docker images) and download it if it exists.*

The command above will lead RStudio-Server to launch invisibly. To connect to it, open a browser and enter http://, followed by your ip address, followed by :8787. If you are running a Mac or Windows machine, you will find the ip address on the first line of text that appeared in your terminal when you launched the Docker Quickstart Terminal. For example, you should see:


                        ##         .
                  ## ## ##        ==
               ## ## ## ## ##    ===
           /"""""""""""""""""\___/ ===
      ~~~ {~~ ~~~~ ~~~ ~~~~ ~~~ ~ /  ===- ~~~
           \______ o           __/
             \    \         __/
              \____\_______/


docker is configured to use the default machine with IP 192.168.99.100
For help getting started, check out the docs at https://docs.docker.com

Thus, you would enter http://192.168.99.100:8787 in your browser as the url.

If you are running a Mac or Linux machine, you can use localhost as the ip address. For example: http://localhost:8787

This should lead to you being greeted by the RStudio welcome screen. Log in using:

username: rstudio password: YOURNEWPASSWORD

Now you should be able to work with RStudio in your browser in much the same way as you would on your desktop. The password you should use is the one you created when you used docker run above.

The image below shows RStudio server running within a docker image. You should see something similar on your machine.

install-pkgs

Try to now look at your files of your virtual computer (docker container). Go to file -> open file. You will see that there are actually no files. The reason for this is that this image came with no files. Next, open a new R Script, e.g. by going to file -> New file -> R Script. Enter the following code in the script, run it and save it.

# make x the numbers from 1 to 5, and y the numbers from 6-10
x <- 1:5
y <- 6:10

# plot x against y
plot(x, y)

If you look at your files again now, you will see the script file.

Now, given that we used the --rm flag when we launched the Docker container, anything we create on the machine will be gone. Let’s verify this. First, close the browser tab where you have RStudio open, and then go to your terminal window from where you launched the Docker container and type Contol+C. This shuts down the Docker container.

Now relaunch your a Docker container using the RStudio image as you did previously, e.g., docker run --rm -p 8787:8787 rocker/verse in the terminal and typing http://192.168.99.100:8787 in your browser window and see if the rscript and plot you saved is still there.

Linking a volume to a Docker container to access data and save files

That leads us to the question of, how can we save our work if the container is deleted when we exit the container? One solution is to link a volume (for example your local hard drive) to the container so that you can access the data there as well as being able to save things there.

This time when we launch our container we will use the -v flag along with the path to our project’s root directory. Your launch command should look something like this, although the path will differ depending on where you saved the data to on your computer. On the left hand side of the : is the path on your own computer, which you can get by doing pwd at the bash prompt from your project’s root directory. On the right hand side is the path on the container; this should almost always start with /home/rstudio/.

docker run --rm -p 8787:8787 -v /Users/tiffanytimbers/Documents/DC/r-docker-tutorial:/home/rstudio/r-docker-tutorial rocker/verse

Again, you will have to enter something like http://192.168.99.100:8787 in your browser as the url to get RStudio to run.

This time when you launch RStudio in a Docker container and you try to open a file you should be able to see some files and directories. Now set the working directory to the directory called r-docker-tutorial and load the gapminder-FiveYearData.csv into R via read.table.

# load gapminder data from a csv on your computer
gap5yr <- read.csv(file = 'data/gapminder-FiveYearData.csv')

Now lets plot GDP per capita against life expectancy.

# load ggplot library
library(ggplot2)

# plot GDP against  life expectancy
qplot(gap5yr$lifeExp, gap5yr$gdpPercap)

# save the plot
ggsave(filename = 'data/GDP_LifeExp.pdf')

Let’s also save the script as plot_GDP_LifeExp.R in the r-docker-tutorial directory. Now close the RStudio browser and exit your Docker container via the terminal using Control+C. Then look inside the r-docker-tutorial and r-docker-tutorial/data directories on your laptop to see if you can see the two files you created.

Summary

In this lesson we learned how to launch a Docker container that allows us to run RStudio in a browser. We learned that using the --rm flag when we run Docker makes the container ephemeral; meaning that it is automatically deleted after we close the container. We do this as to not build up a large collection of containers on our machine and waste space. We also learned that we can link a volume of our laptop to the Docker container if we want to be able to access and save data, scripts and any other files.

The container we used already had R, RStudio and several useful R packages installed. In later lessons we will learn how to modify this container to install new packages, and where we can find other Docker containers that might be useful for our work.

Challenge Questions

Open R or RStudio on your local machine and check which packages you have installed by typing installed.packages(). Compare with your neighbour if they match. Do the same in RStudio in your browser.

Next: Go to Lesson 03 Install packages or back to the main page.

================================================ FILE: 03-install-packages.Rmd ================================================ --- title: "Installing R Packages" output: dcTemplate::dc_lesson_template: fig_width: 6 fig_height: 6 highlight: pygments --- ```{r knitr_init, echo = FALSE, cache = FALSE} library(knitr) ## Global options options(max.print = "75") opts_chunk$set(cache = TRUE, prompt = FALSE, tidy = TRUE, comment = "> #", message = FALSE, warning = FALSE) opts_knit$set(width = 75) ``` ## Installing R Packages within RStudio You can install R packages with RStudio in the browser, like you would on a desktop-RStudio-session, by using `install.packages`. Let's launch a *verse* Docker container to run RStudio as we did previously, and try to install the gapminder package, and load it and peek at the data. ~~~ # install package install.packages('gapminder') # load library library(gapminder) # peek at data head(gapminder) ~~~ Great! Now we have the Gapminder package installed so we can work with the whole dataset. But wait, what is going to happen when we exit the container? It will be deleted and since we didn't save this version of the Docker image, when we open another instance of the container we will have to install the Gapminder package again if we want to use it. To avoid this, lets save the image by running `Docker commit` and then the next time we run a Docker container we can run an instance of this image which includes the Gapminder package. To do this we need to open another terminal window **before** we close our Docker container. To save this specific version of the image we need to find this containers specific hash. We can see this by typing the following command in the new terminal window, and it will list all running Docker containers: ~~~ docker ps ~~~ The output should look something like what is shown below, and the specific hash for this container is the alphanumeric text in the first column. ~~~ 4a6a528b35da rocker/verse "/init" 2 minutes ago Up 2 minutes 0.0.0.0:8787->8787/tcp silly_meninsky ~~~ Now to save this version of the image, in the new terminal window type: ~~~ docker commit -m "verse + gapminder" 4a6a528b35da verse_gapminder ~~~ To save this Docker image we have to provide a commit message to describe the change that we have made to the image. We do this by passing the `-m` flag followed by the message in quotes. We also need to provide the specific hash for this version of the container (here 4a6a528b35da). Finally, we also provide a new name for the new image. We called this new image `verse_gapminder`. We can see that we now have two Docker images saved on our laptops by typing: ~~~ docker images ~~~ ~~~ REPOSITORY TAG IMAGE ID CREATED SIZE verse_gapminder latest bb38976d03cf 57 seconds ago 1.955 GB rocker/verse latest 0168d115f220 3 days ago 1.954 GB ~~~ You can test that this worked by running a Docker container from each image. You will find that the Gapminder package is only installed on the verse_gapminder image and not on the rocker/verse image. ### Installing Dependencies external to the R system Many R packages have dependencies external to R, for example GSL, GDAL, JAGS and so on. To install these on a running rocker container you need to go to the docker command line (in a new terminal window) and type the following: ```{r external-dependencies, eval=FALSE} docker ps # find the ID of the running container you want to add a package to docker exec -it bash # a docker command to start a bash shell in your container apt-get install libgsl0-dev # install the package, in this case GSL ``` If you get an error message when running `apt-get install libgsl0-dev` try running `apt-get update` first. To save these changes go to yet another terminal window and save as above using `docker commit`, e.g. ``` docker commit -m "verse + gapminder + GSL" verse_gapminder_gsl ``` Now you can go to the terminal window in which you typed the `docker exec` command and close the docker container by typing `exit`. ## Challenge Questions You or someone else will probably want to check at some point later, what the docker image contains. Write a README file which documents the details of the `verse_gapminder_gsl` image. For the R packages you can use the output of `installed.packages()`. Next: Go to [Lesson 04 Dockerhub](04-Dockerhub.html) or back to the [main page](http://jsta.github.io/r-docker-tutorial/). ================================================ FILE: 03-install-packages.html ================================================ Installing R Packages

Installing R Packages within RStudio

You can install R packages with RStudio in the browser, like you would on a desktop-RStudio-session, by using install.packages. Let’s launch a verse Docker container to run RStudio as we did previously, and try to install the gapminder package, and load it and peek at the data.

# install package
install.packages('gapminder')

# load library
library(gapminder)

# peek at data
head(gapminder)

Great! Now we have the Gapminder package installed so we can work with the whole dataset. But wait, what is going to happen when we exit the container? It will be deleted and since we didn’t save this version of the Docker image, when we open another instance of the container we will have to install the Gapminder package again if we want to use it.

To avoid this, lets save the image by running Docker commit and then the next time we run a Docker container we can run an instance of this image which includes the Gapminder package. To do this we need to open another terminal window before we close our Docker container.

To save this specific version of the image we need to find this containers specific hash. We can see this by typing the following command in the new terminal window, and it will list all running Docker containers:

docker ps

The output should look something like what is shown below, and the specific hash for this container is the alphanumeric text in the first column.

4a6a528b35da        rocker/verse        "/init"             2 minutes ago       Up 2 minutes        0.0.0.0:8787->8787/tcp   silly_meninsky

Now to save this version of the image, in the new terminal window type:

docker commit -m "verse + gapminder" 4a6a528b35da verse_gapminder

To save this Docker image we have to provide a commit message to describe the change that we have made to the image. We do this by passing the -m flag followed by the message in quotes. We also need to provide the specific hash for this version of the container (here 4a6a528b35da). Finally, we also provide a new name for the new image. We called this new image verse_gapminder.

We can see that we now have two Docker images saved on our laptops by typing:

docker images 
REPOSITORY                           TAG                 IMAGE ID            CREATED             SIZE
verse_gapminder                      latest              bb38976d03cf        57 seconds ago      1.955 GB
rocker/verse                         latest              0168d115f220        3 days ago          1.954 GB

You can test that this worked by running a Docker container from each image. You will find that the Gapminder package is only installed on the verse_gapminder image and not on the rocker/verse image.

Installing Dependencies external to the R system

Many R packages have dependencies external to R, for example GSL, GDAL, JAGS and so on. To install these on a running rocker container you need to go to the docker command line (in a new terminal window) and type the following:

docker ps # find the ID of the running container you want to add a package to
docker exec -it <container-id> bash # a docker command to start a bash shell in your container
apt-get install libgsl0-dev # install the package, in this case GSL

If you get an error message when running apt-get install libgsl0-dev try running apt-get update first.

To save these changes go to yet another terminal window and save as above using docker commit, e.g.

docker commit -m "verse + gapminder + GSL" <container id>  verse_gapminder_gsl

Now you can go to the terminal window in which you typed the docker exec command and close the docker container by typing exit.

Challenge Questions

You or someone else will probably want to check at some point later, what the docker image contains. Write a README file which documents the details of the verse_gapminder_gsl image. For the R packages you can use the output of installed.packages().

Next: Go to Lesson 04 Dockerhub or back to the main page.

================================================ FILE: 04-Dockerhub.Rmd ================================================ --- title: "Pushing and Pulling to and from Docker Hub" output: dcTemplate::dc_lesson_template: fig_width: 6 fig_height: 6 highlight: pygments --- ```{r knitr_init, echo = FALSE, cache = FALSE} library(knitr) ## Global options options(max.print = "75") opts_chunk$set(cache = TRUE, prompt = FALSE, tidy = TRUE, comment = "> #", message = FALSE, warning = FALSE) opts_knit$set(width = 75) ``` ## Lesson Objectives - Understanding where images come from - Pulling a Docker image from Docker Hub - Pushing a Docker image to Docker Hub ## Getting an image from Docker Hub [Docker Hub](https://hub.docker.com/) is the place where open Docker images are stored. When we ran our first image by typing ```{} docker run --rm -p 8787:8787 rocker/verse ``` the software first checked if this image is available on your computer and since it wasn't it downloaded the image from Docker Hub. So getting an image from Docker Hub works sort of automatically. If you just want to pull the image but not run it, you can also do ```{} docker pull rocker/verse ``` ## Getting an image to Docker Hub Imagine you made your own Docker image and would like to share it with the world you can sign up for an account on https://hub.docker.com/. After verifying your email you are ready to go and upload your first docker image. 1. Log in on https://hub.docker.com/ 2. Click on *Create Repository*. 3. Choose a name (e.g. verse_gapminder) and a description for your repository and click *Create*. 4. Log into the Docker Hub from the command line ```{} docker login --username=yourhubusername --email=youremail@company.com ``` just with your own user name and email that you used for the account. Enter your password when prompted. If everything worked you will get a message similar to ```{} WARNING: login credentials saved in /home/username/.docker/config.json Login Succeeded ``` 5. Check the image ID using ```{} docker images ``` and what you will see will be similar to ```{} REPOSITORY TAG IMAGE ID CREATED SIZE verse_gapminder_gsl latest 023ab91c6291 3 minutes ago 1.975 GB verse_gapminder latest bb38976d03cf 13 minutes ago 1.955 GB rocker/verse latest 0168d115f220 3 days ago 1.954 GB ``` and tag your image ```{} docker tag bb38976d03cf yourhubusername/verse_gapminder:firsttry ``` The number must match the image ID and `:firsttry` is the tag. In general, a good choice for a tag is something that will help you understand what this container should be used in conjunction with, or what it represents. If this container contains the analysis for a paper, consider using that paper's DOI or journal-issued serial number; if it's meant for use with a particular version of a code or data version control repo, that's a good choice too - whatever will help you understand what this particular image is intended for. 6. Push your image to the repository you created ```{} docker push yourhubusername/verse_gapminder ``` Your image is now available for everyone to use. ## Saving and loading images Pushing to Docker Hub is great, but it does have some disadvantages: 1. Bandwidth - many ISPs have much lower upload bandwidth than download bandwidth. 2. Unless you're paying extra for the private repositories, pushing equals publishing. 3. When working on some clusters, each time you launch a job that uses a Docker container it pulls the container from Docker Hub, and if you are running many jobs, this can be really slow. Solutions to these problems can be to save the Docker container locally as a a tar archive, and then you can easily load that to an image when needed. To save a Docker image after you have pulled, committed or built it you use the `docker save` command. For example, lets save a local copy of the `verse_gapminder` docker image we made: ~~~ docker save verse_gapminder > verse_gapminder.tar ~~~ If we want to load that Docker container from the archived tar file in the future, we can use the docker load command: ~~~ docker load --input verse_gapminder.tar ~~~ ## Challenge Questions - Download your partner's image. How did that compare speed-wise to downloading the verse image the first time? - Browse Docker Hub for interesting images. What could be useful to you? - Discuss the pros and cons of using Docker images from someone you don't know with your neighbour. Next: Go to [Lesson 05 Dockerfiles](05-dockerfiles.html) or back to the [main page](http://jsta.github.io/r-docker-tutorial/). ================================================ FILE: 04-Dockerhub.html ================================================ Pushing and Pulling to and from Docker Hub

Lesson Objectives

  • Understanding where images come from
  • Pulling a Docker image from Docker Hub
  • Pushing a Docker image to Docker Hub

Getting an image from Docker Hub

Docker Hub is the place where open Docker images are stored. When we ran our first image by typing

docker run --rm -p 8787:8787 rocker/verse

the software first checked if this image is available on your computer and since it wasn’t it downloaded the image from Docker Hub. So getting an image from Docker Hub works sort of automatically. If you just want to pull the image but not run it, you can also do

docker pull rocker/verse

Getting an image to Docker Hub

Imagine you made your own Docker image and would like to share it with the world you can sign up for an account on https://hub.docker.com/. After verifying your email you are ready to go and upload your first docker image.

  1. Log in on https://hub.docker.com/
  2. Click on Create Repository.
  3. Choose a name (e.g. verse_gapminder) and a description for your repository and click Create.
  4. Log into the Docker Hub from the command line
docker login --username=yourhubusername --email=youremail@company.com

just with your own user name and email that you used for the account. Enter your password when prompted. If everything worked you will get a message similar to

WARNING: login credentials saved in /home/username/.docker/config.json
Login Succeeded
  1. Check the image ID using
docker images

and what you will see will be similar to

REPOSITORY              TAG       IMAGE ID         CREATED           SIZE
verse_gapminder_gsl     latest    023ab91c6291     3 minutes ago     1.975 GB
verse_gapminder         latest    bb38976d03cf     13 minutes ago    1.955 GB
rocker/verse            latest    0168d115f220     3 days ago        1.954 GB

and tag your image

docker tag bb38976d03cf yourhubusername/verse_gapminder:firsttry

The number must match the image ID and :firsttry is the tag. In general, a good choice for a tag is something that will help you understand what this container should be used in conjunction with, or what it represents. If this container contains the analysis for a paper, consider using that paper’s DOI or journal-issued serial number; if it’s meant for use with a particular version of a code or data version control repo, that’s a good choice too - whatever will help you understand what this particular image is intended for.

  1. Push your image to the repository you created
docker push yourhubusername/verse_gapminder

Your image is now available for everyone to use.

Saving and loading images

Pushing to Docker Hub is great, but it does have some disadvantages:

  1. Bandwidth - many ISPs have much lower upload bandwidth than download bandwidth.
  2. Unless you’re paying extra for the private repositories, pushing equals publishing.
  3. When working on some clusters, each time you launch a job that uses a Docker container it pulls the container from Docker Hub, and if you are running many jobs, this can be really slow.

Solutions to these problems can be to save the Docker container locally as a a tar archive, and then you can easily load that to an image when needed.

To save a Docker image after you have pulled, committed or built it you use the docker save command. For example, lets save a local copy of the verse_gapminder docker image we made:

docker save verse_gapminder > verse_gapminder.tar

If we want to load that Docker container from the archived tar file in the future, we can use the docker load command:

docker load --input verse_gapminder.tar

Challenge Questions

  • Download your partner’s image. How did that compare speed-wise to downloading the verse image the first time?
  • Browse Docker Hub for interesting images. What could be useful to you?
  • Discuss the pros and cons of using Docker images from someone you don’t know with your neighbour.

Next: Go to Lesson 05 Dockerfiles or back to the main page.

================================================ FILE: 05-dockerfiles.Rmd ================================================ --- title: "Dockerfiles" output: dcTemplate::dc_lesson_template: fig_width: 6 fig_height: 6 highlight: pygments --- Earlier, we got started with a base image that let us run RStudio from within Docker, and learned to modify the contents of that image using `docker commit`. This is an excellent technique for capturing what we've done so we can reproduce it later, but what if we want to be able to easily change the collection of things in our image, and have a clear record of just what went into it? This is useful when maintaining running environments that may change and evolve over a project, and is facilitated by Dockerfiles. Dockerfiles are a set of instructions on how to add things to a base image. They build custom images up in a series of *layers*. In a new file called `Dockerfile`, put the following: ``` FROM rocker/verse:latest ``` This tells Docker to start with the `rocker/verse` base image - that's what we've been using so far. The `FROM` command must always be the first thing in your Dockerfile; this is the bottom crust of the pie we are baking. Next, let's add another layer on top of our base, in order to have `gapminder` pre-installed and ready to go: ``` RUN R -e "install.packages('gapminder', repos = 'http://cran.us.r-project.org')" ``` `RUN` commands in your Dockerfile execute shell commands to build up your image, like putting the filling in our pie. In this example, we install `gapminder` from the command line using `install.packages`, which does the same thing as if we had done `install.packages('gapminder')` from within RStudio. Save your Dockerfile, and return to your docker terminal; we can now build our image by doing: ``` docker build -t my-r-image . ``` `-t my-r-image` gives our image a name (note image names are always all lower case), and the `.` says all the resources we need to build this image are in our current directory. List your images via: ``` docker images ``` and you should see `my-r-image` in the list. Launch your new image similarly to how we launched the base image: ``` docker run --rm -p 8787:8787 my-r-image ``` Then in the RStudio terminal, try gapminder again: ``` library('gapminder') gapminder ``` And there it is - gapminder is pre-installed and ready to go in your new docker image. Our pie is almost complete! All we need to finish it is the topping. In addition to R packages like gapminder, we may also want some some static files inside our Docker image - such as data. We can do this using the `ADD` command in your Dockerfile: ``` ADD data/gapminder-FiveYearData.csv /home/rstudio/ ``` Rebuild your Docker image: ``` docker build -t my-r-image . ``` And launch it again: ``` docker run --rm -p 8787:8787 my-r-image ``` Go back to RStudio in the browser, and there `gapminder-FiveYearData.csv` will be, present in the files visible to RStudio. In this way, we can capture files as part of our Docker image, so they're always available along with the rest of our image in the exact same state. #### Protip: Cached Layers While building and rebuilding your Docker image in this tutorial, you may have noticed lines like this: ``` Step 2 : RUN R -e "install.packages('gapminder', repos = 'http://cran.us.r-project.org')" ---> Using cache ---> fa9be67b52d1 ``` Noting that a cached version of the commands was being used. When you rebuild an image, Docker checks the previous version(s) of that image to see if the same commands were executed previously; each of those steps is preserved as a separate layer, and Docker is smart enough to re-use those layers if they are unchanged and *in the same order* as previously. Therefore, once you've got part of your setup process figured out (particularly if it's a slow part), leave it near the top of your Dockerfile and don't put anything above or between those lines, particularly things that change frequently; this can substantially speed up your build process. ## Summary In this lesson, we learned how to compose a Dockerfile so that we can re-create our images at will. We learned three main commands: - `FROM` is always at the top of a Dockerfile, and specifies the image we want to start from. - `RUN` runs shell commands on top of our base image, and is used for doing things like downloads and installations. - `ADD` adds files from our computer to our new Docker image. The image is built by running `docker build -t my-r-image .` in the same directory as our Dockerfile and any files we want to include with an `ADD` command. ## Challenge Questions - Write a Dockerfile that makes an image like the one you made at the end of Section 3: built on `rocker/verse`, with `gapminder` and `gsl` installed. Also add a readme to your image describing what it contains. Find the Dockerfile of the `rocker/verse` image through Docker Hub. - How does having a Dockerfile compare to a README file (like the one we prepared in lesson 3)? - Docker Hub can automatically build images when you store the file on Github or Bitbucket. What do you think are the benefits of doing this instead of commiting the image directly? Could it be negative? - Find the build details of the `rocker/verse` image. What do they tell us? Go to [Lesson 06 Share all your analysis](06-Sharing-all-your-analysis.html) or back to the [main page](http://jsta.github.io/r-docker-tutorial/). ================================================ FILE: 05-dockerfiles.html ================================================ Dockerfiles

Earlier, we got started with a base image that let us run RStudio from within Docker, and learned to modify the contents of that image using docker commit. This is an excellent technique for capturing what we’ve done so we can reproduce it later, but what if we want to be able to easily change the collection of things in our image, and have a clear record of just what went into it? This is useful when maintaining running environments that may change and evolve over a project, and is facilitated by Dockerfiles.

Dockerfiles are a set of instructions on how to add things to a base image. They build custom images up in a series of layers. In a new file called Dockerfile, put the following:

FROM rocker/verse:latest

This tells Docker to start with the rocker/verse base image - that’s what we’ve been using so far. The FROM command must always be the first thing in your Dockerfile; this is the bottom crust of the pie we are baking.

Next, let’s add another layer on top of our base, in order to have gapminder pre-installed and ready to go:

RUN R -e "install.packages('gapminder', repos = 'http://cran.us.r-project.org')"

RUN commands in your Dockerfile execute shell commands to build up your image, like putting the filling in our pie. In this example, we install gapminder from the command line using install.packages, which does the same thing as if we had done install.packages('gapminder') from within RStudio. Save your Dockerfile, and return to your docker terminal; we can now build our image by doing:

docker build -t my-r-image .

-t my-r-image gives our image a name (note image names are always all lower case), and the . says all the resources we need to build this image are in our current directory. List your images via:

docker images

and you should see my-r-image in the list. Launch your new image similarly to how we launched the base image:

docker run --rm -p 8787:8787 my-r-image

Then in the RStudio terminal, try gapminder again:

library('gapminder')
gapminder

And there it is - gapminder is pre-installed and ready to go in your new docker image.

Our pie is almost complete! All we need to finish it is the topping. In addition to R packages like gapminder, we may also want some some static files inside our Docker image - such as data. We can do this using the ADD command in your Dockerfile:

ADD data/gapminder-FiveYearData.csv /home/rstudio/

Rebuild your Docker image:

docker build -t my-r-image .

And launch it again:

docker run --rm -p 8787:8787 my-r-image

Go back to RStudio in the browser, and there gapminder-FiveYearData.csv will be, present in the files visible to RStudio. In this way, we can capture files as part of our Docker image, so they’re always available along with the rest of our image in the exact same state.

Protip: Cached Layers

While building and rebuilding your Docker image in this tutorial, you may have noticed lines like this:

Step 2 : RUN R -e "install.packages('gapminder', repos = 'http://cran.us.r-project.org')"
 ---> Using cache
 ---> fa9be67b52d1

Noting that a cached version of the commands was being used. When you rebuild an image, Docker checks the previous version(s) of that image to see if the same commands were executed previously; each of those steps is preserved as a separate layer, and Docker is smart enough to re-use those layers if they are unchanged and in the same order as previously. Therefore, once you’ve got part of your setup process figured out (particularly if it’s a slow part), leave it near the top of your Dockerfile and don’t put anything above or between those lines, particularly things that change frequently; this can substantially speed up your build process.

Summary

In this lesson, we learned how to compose a Dockerfile so that we can re-create our images at will. We learned three main commands:

  • FROM is always at the top of a Dockerfile, and specifies the image we want to start from.
  • RUN runs shell commands on top of our base image, and is used for doing things like downloads and installations.
  • ADD adds files from our computer to our new Docker image.

The image is built by running docker build -t my-r-image . in the same directory as our Dockerfile and any files we want to include with an ADD command.

Challenge Questions

  • Write a Dockerfile that makes an image like the one you made at the end of Section 3: built on rocker/verse, with gapminder and gsl installed. Also add a readme to your image describing what it contains.

Find the Dockerfile of the rocker/verse image through Docker Hub.

  • How does having a Dockerfile compare to a README file (like the one we prepared in lesson 3)?
  • Docker Hub can automatically build images when you store the file on Github or Bitbucket. What do you think are the benefits of doing this instead of commiting the image directly? Could it be negative?
  • Find the build details of the rocker/verse image. What do they tell us?

Go to Lesson 06 Share all your analysis or back to the
main page.

================================================ FILE: 06-Sharing-all-your-analysis.Rmd ================================================ --- title: "06-Share all your analysis" output: dcTemplate::dc_lesson_template: fig_width: 6 fig_height: 6 highlight: pygments --- Now that we have learned how to work with a dockerfile, we can send all our analysis to a collaborator. We will share an image that contains all the dependencies that we need to run our analysis, the data and the analysis. We will build this image via a dockerfile. Let's start with the basic verse rocker image we used before. This time we want to have a specific R version (3.3.2), which the developers make possible by tagging the images with the version. See all available tags for the `rocker/verse` image [here](https://hub.docker.com/r/rocker/verse/tags/). The version tag is very useful when you want your analysis to be reproducible. ``` FROM rocker/verse:3.3.2 ``` As part of our analysis, we will use the gapminder data. We will need to install this package into our docker image. Let's modify our dockerfile to install this package. ``` RUN R -e "install.packages('gapminder', repos = 'http://cran.us.r-project.org')" ``` Now we just need to write our analysis and add it to our dockerfile. For this analysis, we will create a plot of life expectancy vs. gdp per capita. On a new R script let's write the following analysis. ```{r} library(ggplot2) library(gapminder) life_expentancy_plot <- ggplot(data = gapminder) + geom_point(aes(x = lifeExp, y = gdpPercap, colour = continent)) ``` We will save this r script as analysis.R and add it to our dockerfile. ``` ADD analysis.R /home/rstudio/ ``` Now we can build the image and check that we have everything we want to share with our collaborator. ``` docker build -t my-analysis . ``` Our analysis will appear on the list of images. ``` docker images ``` Launch your new image and check you have everything you want to include: ``` docker run -dp 8787:8787 my-analysis ``` Great! our analysis script is there and gapminder is installed. Now we can push our analysis to dockerhub. On dockerhub click on *Create Repository*. Choose a name (e.g. gapminder_my_analysis) and a description for your repository and click *Create*. Log into the Docker Hub from the command line ```{} docker login --username=yourhubusername ``` just with your own user name that you used for the account. Enter your password when prompted. Check the image ID using ```{} docker images ``` and what you will see will be similar to ```{} REPOSITORY TAG IMAGE ID CREATED SIZE my-analysis latest dc63d4790eaa 2 minutes ago 3.164 GB ``` and tag your image ```{} docker tag dc63d4790eaa yourhubusername/gapminder_my_analysis:firsttry ``` Push your image to the repository you created ```{} docker push yourhubusername/gapminder_my_analysis ``` Your image is now available for everyone to use. Now your collaborator can download your image. Your collaborator should write on their command line: ``` docker pull yourhubusername/gapminder_my_analysis:firsttry ``` They now have the image of your analysis. Click to go back to the [main page](http://jsta.github.io/r-docker-tutorial/). ================================================ FILE: 06-Sharing-all-your-analysis.html ================================================ 06-Share all your analysis

Now that we have learned how to work with a dockerfile, we can send all our analysis to a collaborator. We will share an image that contains all the dependencies that we need to run our analysis, the data and the analysis.

We will build this image via a dockerfile. Let’s start with the basic verse rocker image we used before. This time we want to have a specific R version (3.3.2), which the developers make possible by tagging the images with the version. See all available tags for the rocker/verse image here. The version tag is very useful when you want your analysis to be reproducible.

FROM rocker/verse:3.3.2

As part of our analysis, we will use the gapminder data. We will need to install this package into our docker image. Let’s modify our dockerfile to install this package.

RUN R -e "install.packages('gapminder', repos = 'http://cran.us.r-project.org')"

Now we just need to write our analysis and add it to our dockerfile.

For this analysis, we will create a plot of life expectancy vs. gdp per capita.

On a new R script let’s write the following analysis.

library(ggplot2)
library(gapminder)
## Warning: package 'gapminder' was built under R version 4.1.2
life_expentancy_plot <- ggplot(data = gapminder) +
  geom_point(aes(x = lifeExp, y = gdpPercap, colour = continent))

We will save this r script as analysis.R and add it to our dockerfile.

ADD analysis.R /home/rstudio/

Now we can build the image and check that we have everything we want to share with our collaborator.

docker build -t my-analysis .

Our analysis will appear on the list of images.

docker images

Launch your new image and check you have everything you want to include:

docker run -dp 8787:8787 my-analysis

Great! our analysis script is there and gapminder is installed.

Now we can push our analysis to dockerhub.

On dockerhub click on Create Repository. Choose a name (e.g. gapminder_my_analysis) and a description for your repository and click Create.

Log into the Docker Hub from the command line

docker login --username=yourhubusername

just with your own user name that you used for the account. Enter your password when prompted.

Check the image ID using

docker images

and what you will see will be similar to

REPOSITORY                         TAG                 IMAGE ID            CREATED             SIZE
my-analysis                      latest              dc63d4790eaa        2 minutes ago       3.164 GB

and tag your image

docker tag dc63d4790eaa yourhubusername/gapminder_my_analysis:firsttry

Push your image to the repository you created

docker push yourhubusername/gapminder_my_analysis

Your image is now available for everyone to use.

Now your collaborator can download your image.

Your collaborator should write on their command line:

docker pull yourhubusername/gapminder_my_analysis:firsttry

They now have the image of your analysis.

Click to go back to the main page.

================================================ FILE: Makefile ================================================ RMD := $(wildcard *.Rmd) KNIT_HTML := $(patsubst %.Rmd, %.html, $(RMD)) all: $(KNIT_HTML) test: echo $(RMD) echo $(KNIT_HTML) %.html: %.Rmd Rscript -e "rmarkdown::render('$<')" deps: Rscript -e 'devtools::install_github("karthik/dcTemplate")' Rscript -e 'install.packages("gapminder", repos = "https://cloud.r-project.org")' ================================================ FILE: README.md ================================================ # r-docker-tutorial A docker tutorial for reproducible research. This is an introduction to Docker designed for participants with knowledge about R and RStudio. The introduction is intended to be helping people who need Docker for a project. We first explain what Docker is and why it is useful. Then we go into the the details on how to use it for a reproducible transportable project. ## Lessons: 1. [Lesson 01 What and Why](01-what-and-why.html) 2. [Lesson 02 Launching Docker](02-Launching-Docker.html) 3. [Lesson 03 Install packages](03-install-packages.html) 4. [Lesson 04 Dockerhub](04-Dockerhub.html) 5. [Lesson 05 Dockerfiles](05-dockerfiles.html) 6. [Lesson 06 Sharing your analysis](06-Sharing-all-your-analysis.html) ## Links - [Website](http://jsta.github.io/r-docker-tutorial) - [For lesson developers](http://pad.software-carpentry.org/RopenSci-docker-tutorial) ## Credit Formerly an rOpenSci project started at the [2016 Unconference](https://unconf16.ropensci.org/). Credit to all the [contributors](https://github.com/jsta/r-docker-tutorial/graphs/contributors)! ================================================ FILE: data/gapminder-FiveYearData.csv ================================================ country,year,pop,continent,lifeExp,gdpPercap Afghanistan,1952,8425333,Asia,28.801,779.4453145 Afghanistan,1957,9240934,Asia,30.332,820.8530296 Afghanistan,1962,10267083,Asia,31.997,853.10071 Afghanistan,1967,11537966,Asia,34.02,836.1971382 Afghanistan,1972,13079460,Asia,36.088,739.9811058 Afghanistan,1977,14880372,Asia,38.438,786.11336 Afghanistan,1982,12881816,Asia,39.854,978.0114388 Afghanistan,1987,13867957,Asia,40.822,852.3959448 Afghanistan,1992,16317921,Asia,41.674,649.3413952 Afghanistan,1997,22227415,Asia,41.763,635.341351 Afghanistan,2002,25268405,Asia,42.129,726.7340548 Afghanistan,2007,31889923,Asia,43.828,974.5803384 Albania,1952,1282697,Europe,55.23,1601.056136 Albania,1957,1476505,Europe,59.28,1942.284244 Albania,1962,1728137,Europe,64.82,2312.888958 Albania,1967,1984060,Europe,66.22,2760.196931 Albania,1972,2263554,Europe,67.69,3313.422188 Albania,1977,2509048,Europe,68.93,3533.00391 Albania,1982,2780097,Europe,70.42,3630.880722 Albania,1987,3075321,Europe,72,3738.932735 Albania,1992,3326498,Europe,71.581,2497.437901 Albania,1997,3428038,Europe,72.95,3193.054604 Albania,2002,3508512,Europe,75.651,4604.211737 Albania,2007,3600523,Europe,76.423,5937.029526 Algeria,1952,9279525,Africa,43.077,2449.008185 Algeria,1957,10270856,Africa,45.685,3013.976023 Algeria,1962,11000948,Africa,48.303,2550.81688 Algeria,1967,12760499,Africa,51.407,3246.991771 Algeria,1972,14760787,Africa,54.518,4182.663766 Algeria,1977,17152804,Africa,58.014,4910.416756 Algeria,1982,20033753,Africa,61.368,5745.160213 Algeria,1987,23254956,Africa,65.799,5681.358539 Algeria,1992,26298373,Africa,67.744,5023.216647 Algeria,1997,29072015,Africa,69.152,4797.295051 Algeria,2002,31287142,Africa,70.994,5288.040382 Algeria,2007,33333216,Africa,72.301,6223.367465 Angola,1952,4232095,Africa,30.015,3520.610273 Angola,1957,4561361,Africa,31.999,3827.940465 Angola,1962,4826015,Africa,34,4269.276742 Angola,1967,5247469,Africa,35.985,5522.776375 Angola,1972,5894858,Africa,37.928,5473.288005 Angola,1977,6162675,Africa,39.483,3008.647355 Angola,1982,7016384,Africa,39.942,2756.953672 Angola,1987,7874230,Africa,39.906,2430.208311 Angola,1992,8735988,Africa,40.647,2627.845685 Angola,1997,9875024,Africa,40.963,2277.140884 Angola,2002,10866106,Africa,41.003,2773.287312 Angola,2007,12420476,Africa,42.731,4797.231267 Argentina,1952,17876956,Americas,62.485,5911.315053 Argentina,1957,19610538,Americas,64.399,6856.856212 Argentina,1962,21283783,Americas,65.142,7133.166023 Argentina,1967,22934225,Americas,65.634,8052.953021 Argentina,1972,24779799,Americas,67.065,9443.038526 Argentina,1977,26983828,Americas,68.481,10079.02674 Argentina,1982,29341374,Americas,69.942,8997.897412 Argentina,1987,31620918,Americas,70.774,9139.671389 Argentina,1992,33958947,Americas,71.868,9308.41871 Argentina,1997,36203463,Americas,73.275,10967.28195 Argentina,2002,38331121,Americas,74.34,8797.640716 Argentina,2007,40301927,Americas,75.32,12779.37964 Australia,1952,8691212,Oceania,69.12,10039.59564 Australia,1957,9712569,Oceania,70.33,10949.64959 Australia,1962,10794968,Oceania,70.93,12217.22686 Australia,1967,11872264,Oceania,71.1,14526.12465 Australia,1972,13177000,Oceania,71.93,16788.62948 Australia,1977,14074100,Oceania,73.49,18334.19751 Australia,1982,15184200,Oceania,74.74,19477.00928 Australia,1987,16257249,Oceania,76.32,21888.88903 Australia,1992,17481977,Oceania,77.56,23424.76683 Australia,1997,18565243,Oceania,78.83,26997.93657 Australia,2002,19546792,Oceania,80.37,30687.75473 Australia,2007,20434176,Oceania,81.235,34435.36744 Austria,1952,6927772,Europe,66.8,6137.076492 Austria,1957,6965860,Europe,67.48,8842.59803 Austria,1962,7129864,Europe,69.54,10750.72111 Austria,1967,7376998,Europe,70.14,12834.6024 Austria,1972,7544201,Europe,70.63,16661.6256 Austria,1977,7568430,Europe,72.17,19749.4223 Austria,1982,7574613,Europe,73.18,21597.08362 Austria,1987,7578903,Europe,74.94,23687.82607 Austria,1992,7914969,Europe,76.04,27042.01868 Austria,1997,8069876,Europe,77.51,29095.92066 Austria,2002,8148312,Europe,78.98,32417.60769 Austria,2007,8199783,Europe,79.829,36126.4927 Bahrain,1952,120447,Asia,50.939,9867.084765 Bahrain,1957,138655,Asia,53.832,11635.79945 Bahrain,1962,171863,Asia,56.923,12753.27514 Bahrain,1967,202182,Asia,59.923,14804.6727 Bahrain,1972,230800,Asia,63.3,18268.65839 Bahrain,1977,297410,Asia,65.593,19340.10196 Bahrain,1982,377967,Asia,69.052,19211.14731 Bahrain,1987,454612,Asia,70.75,18524.02406 Bahrain,1992,529491,Asia,72.601,19035.57917 Bahrain,1997,598561,Asia,73.925,20292.01679 Bahrain,2002,656397,Asia,74.795,23403.55927 Bahrain,2007,708573,Asia,75.635,29796.04834 Bangladesh,1952,46886859,Asia,37.484,684.2441716 Bangladesh,1957,51365468,Asia,39.348,661.6374577 Bangladesh,1962,56839289,Asia,41.216,686.3415538 Bangladesh,1967,62821884,Asia,43.453,721.1860862 Bangladesh,1972,70759295,Asia,45.252,630.2336265 Bangladesh,1977,80428306,Asia,46.923,659.8772322 Bangladesh,1982,93074406,Asia,50.009,676.9818656 Bangladesh,1987,103764241,Asia,52.819,751.9794035 Bangladesh,1992,113704579,Asia,56.018,837.8101643 Bangladesh,1997,123315288,Asia,59.412,972.7700352 Bangladesh,2002,135656790,Asia,62.013,1136.39043 Bangladesh,2007,150448339,Asia,64.062,1391.253792 Belgium,1952,8730405,Europe,68,8343.105127 Belgium,1957,8989111,Europe,69.24,9714.960623 Belgium,1962,9218400,Europe,70.25,10991.20676 Belgium,1967,9556500,Europe,70.94,13149.04119 Belgium,1972,9709100,Europe,71.44,16672.14356 Belgium,1977,9821800,Europe,72.8,19117.97448 Belgium,1982,9856303,Europe,73.93,20979.84589 Belgium,1987,9870200,Europe,75.35,22525.56308 Belgium,1992,10045622,Europe,76.46,25575.57069 Belgium,1997,10199787,Europe,77.53,27561.19663 Belgium,2002,10311970,Europe,78.32,30485.88375 Belgium,2007,10392226,Europe,79.441,33692.60508 Benin,1952,1738315,Africa,38.223,1062.7522 Benin,1957,1925173,Africa,40.358,959.6010805 Benin,1962,2151895,Africa,42.618,949.4990641 Benin,1967,2427334,Africa,44.885,1035.831411 Benin,1972,2761407,Africa,47.014,1085.796879 Benin,1977,3168267,Africa,49.19,1029.161251 Benin,1982,3641603,Africa,50.904,1277.897616 Benin,1987,4243788,Africa,52.337,1225.85601 Benin,1992,4981671,Africa,53.919,1191.207681 Benin,1997,6066080,Africa,54.777,1232.975292 Benin,2002,7026113,Africa,54.406,1372.877931 Benin,2007,8078314,Africa,56.728,1441.284873 Bolivia,1952,2883315,Americas,40.414,2677.326347 Bolivia,1957,3211738,Americas,41.89,2127.686326 Bolivia,1962,3593918,Americas,43.428,2180.972546 Bolivia,1967,4040665,Americas,45.032,2586.886053 Bolivia,1972,4565872,Americas,46.714,2980.331339 Bolivia,1977,5079716,Americas,50.023,3548.097832 Bolivia,1982,5642224,Americas,53.859,3156.510452 Bolivia,1987,6156369,Americas,57.251,2753.69149 Bolivia,1992,6893451,Americas,59.957,2961.699694 Bolivia,1997,7693188,Americas,62.05,3326.143191 Bolivia,2002,8445134,Americas,63.883,3413.26269 Bolivia,2007,9119152,Americas,65.554,3822.137084 Bosnia and Herzegovina,1952,2791000,Europe,53.82,973.5331948 Bosnia and Herzegovina,1957,3076000,Europe,58.45,1353.989176 Bosnia and Herzegovina,1962,3349000,Europe,61.93,1709.683679 Bosnia and Herzegovina,1967,3585000,Europe,64.79,2172.352423 Bosnia and Herzegovina,1972,3819000,Europe,67.45,2860.16975 Bosnia and Herzegovina,1977,4086000,Europe,69.86,3528.481305 Bosnia and Herzegovina,1982,4172693,Europe,70.69,4126.613157 Bosnia and Herzegovina,1987,4338977,Europe,71.14,4314.114757 Bosnia and Herzegovina,1992,4256013,Europe,72.178,2546.781445 Bosnia and Herzegovina,1997,3607000,Europe,73.244,4766.355904 Bosnia and Herzegovina,2002,4165416,Europe,74.09,6018.975239 Bosnia and Herzegovina,2007,4552198,Europe,74.852,7446.298803 Botswana,1952,442308,Africa,47.622,851.2411407 Botswana,1957,474639,Africa,49.618,918.2325349 Botswana,1962,512764,Africa,51.52,983.6539764 Botswana,1967,553541,Africa,53.298,1214.709294 Botswana,1972,619351,Africa,56.024,2263.611114 Botswana,1977,781472,Africa,59.319,3214.857818 Botswana,1982,970347,Africa,61.484,4551.14215 Botswana,1987,1151184,Africa,63.622,6205.88385 Botswana,1992,1342614,Africa,62.745,7954.111645 Botswana,1997,1536536,Africa,52.556,8647.142313 Botswana,2002,1630347,Africa,46.634,11003.60508 Botswana,2007,1639131,Africa,50.728,12569.85177 Brazil,1952,56602560,Americas,50.917,2108.944355 Brazil,1957,65551171,Americas,53.285,2487.365989 Brazil,1962,76039390,Americas,55.665,3336.585802 Brazil,1967,88049823,Americas,57.632,3429.864357 Brazil,1972,100840058,Americas,59.504,4985.711467 Brazil,1977,114313951,Americas,61.489,6660.118654 Brazil,1982,128962939,Americas,63.336,7030.835878 Brazil,1987,142938076,Americas,65.205,7807.095818 Brazil,1992,155975974,Americas,67.057,6950.283021 Brazil,1997,168546719,Americas,69.388,7957.980824 Brazil,2002,179914212,Americas,71.006,8131.212843 Brazil,2007,190010647,Americas,72.39,9065.800825 Bulgaria,1952,7274900,Europe,59.6,2444.286648 Bulgaria,1957,7651254,Europe,66.61,3008.670727 Bulgaria,1962,8012946,Europe,69.51,4254.337839 Bulgaria,1967,8310226,Europe,70.42,5577.0028 Bulgaria,1972,8576200,Europe,70.9,6597.494398 Bulgaria,1977,8797022,Europe,70.81,7612.240438 Bulgaria,1982,8892098,Europe,71.08,8224.191647 Bulgaria,1987,8971958,Europe,71.34,8239.854824 Bulgaria,1992,8658506,Europe,71.19,6302.623438 Bulgaria,1997,8066057,Europe,70.32,5970.38876 Bulgaria,2002,7661799,Europe,72.14,7696.777725 Bulgaria,2007,7322858,Europe,73.005,10680.79282 Burkina Faso,1952,4469979,Africa,31.975,543.2552413 Burkina Faso,1957,4713416,Africa,34.906,617.1834648 Burkina Faso,1962,4919632,Africa,37.814,722.5120206 Burkina Faso,1967,5127935,Africa,40.697,794.8265597 Burkina Faso,1972,5433886,Africa,43.591,854.7359763 Burkina Faso,1977,5889574,Africa,46.137,743.3870368 Burkina Faso,1982,6634596,Africa,48.122,807.1985855 Burkina Faso,1987,7586551,Africa,49.557,912.0631417 Burkina Faso,1992,8878303,Africa,50.26,931.7527731 Burkina Faso,1997,10352843,Africa,50.324,946.2949618 Burkina Faso,2002,12251209,Africa,50.65,1037.645221 Burkina Faso,2007,14326203,Africa,52.295,1217.032994 Burundi,1952,2445618,Africa,39.031,339.2964587 Burundi,1957,2667518,Africa,40.533,379.5646281 Burundi,1962,2961915,Africa,42.045,355.2032273 Burundi,1967,3330989,Africa,43.548,412.9775136 Burundi,1972,3529983,Africa,44.057,464.0995039 Burundi,1977,3834415,Africa,45.91,556.1032651 Burundi,1982,4580410,Africa,47.471,559.603231 Burundi,1987,5126023,Africa,48.211,621.8188189 Burundi,1992,5809236,Africa,44.736,631.6998778 Burundi,1997,6121610,Africa,45.326,463.1151478 Burundi,2002,7021078,Africa,47.36,446.4035126 Burundi,2007,8390505,Africa,49.58,430.0706916 Cambodia,1952,4693836,Asia,39.417,368.4692856 Cambodia,1957,5322536,Asia,41.366,434.0383364 Cambodia,1962,6083619,Asia,43.415,496.9136476 Cambodia,1967,6960067,Asia,45.415,523.4323142 Cambodia,1972,7450606,Asia,40.317,421.6240257 Cambodia,1977,6978607,Asia,31.22,524.9721832 Cambodia,1982,7272485,Asia,50.957,624.4754784 Cambodia,1987,8371791,Asia,53.914,683.8955732 Cambodia,1992,10150094,Asia,55.803,682.3031755 Cambodia,1997,11782962,Asia,56.534,734.28517 Cambodia,2002,12926707,Asia,56.752,896.2260153 Cambodia,2007,14131858,Asia,59.723,1713.778686 Cameroon,1952,5009067,Africa,38.523,1172.667655 Cameroon,1957,5359923,Africa,40.428,1313.048099 Cameroon,1962,5793633,Africa,42.643,1399.607441 Cameroon,1967,6335506,Africa,44.799,1508.453148 Cameroon,1972,7021028,Africa,47.049,1684.146528 Cameroon,1977,7959865,Africa,49.355,1783.432873 Cameroon,1982,9250831,Africa,52.961,2367.983282 Cameroon,1987,10780667,Africa,54.985,2602.664206 Cameroon,1992,12467171,Africa,54.314,1793.163278 Cameroon,1997,14195809,Africa,52.199,1694.337469 Cameroon,2002,15929988,Africa,49.856,1934.011449 Cameroon,2007,17696293,Africa,50.43,2042.09524 Canada,1952,14785584,Americas,68.75,11367.16112 Canada,1957,17010154,Americas,69.96,12489.95006 Canada,1962,18985849,Americas,71.3,13462.48555 Canada,1967,20819767,Americas,72.13,16076.58803 Canada,1972,22284500,Americas,72.88,18970.57086 Canada,1977,23796400,Americas,74.21,22090.88306 Canada,1982,25201900,Americas,75.76,22898.79214 Canada,1987,26549700,Americas,76.86,26626.51503 Canada,1992,28523502,Americas,77.95,26342.88426 Canada,1997,30305843,Americas,78.61,28954.92589 Canada,2002,31902268,Americas,79.77,33328.96507 Canada,2007,33390141,Americas,80.653,36319.23501 Central African Republic,1952,1291695,Africa,35.463,1071.310713 Central African Republic,1957,1392284,Africa,37.464,1190.844328 Central African Republic,1962,1523478,Africa,39.475,1193.068753 Central African Republic,1967,1733638,Africa,41.478,1136.056615 Central African Republic,1972,1927260,Africa,43.457,1070.013275 Central African Republic,1977,2167533,Africa,46.775,1109.374338 Central African Republic,1982,2476971,Africa,48.295,956.7529907 Central African Republic,1987,2840009,Africa,50.485,844.8763504 Central African Republic,1992,3265124,Africa,49.396,747.9055252 Central African Republic,1997,3696513,Africa,46.066,740.5063317 Central African Republic,2002,4048013,Africa,43.308,738.6906068 Central African Republic,2007,4369038,Africa,44.741,706.016537 Chad,1952,2682462,Africa,38.092,1178.665927 Chad,1957,2894855,Africa,39.881,1308.495577 Chad,1962,3150417,Africa,41.716,1389.817618 Chad,1967,3495967,Africa,43.601,1196.810565 Chad,1972,3899068,Africa,45.569,1104.103987 Chad,1977,4388260,Africa,47.383,1133.98495 Chad,1982,4875118,Africa,49.517,797.9081006 Chad,1987,5498955,Africa,51.051,952.386129 Chad,1992,6429417,Africa,51.724,1058.0643 Chad,1997,7562011,Africa,51.573,1004.961353 Chad,2002,8835739,Africa,50.525,1156.18186 Chad,2007,10238807,Africa,50.651,1704.063724 Chile,1952,6377619,Americas,54.745,3939.978789 Chile,1957,7048426,Americas,56.074,4315.622723 Chile,1962,7961258,Americas,57.924,4519.094331 Chile,1967,8858908,Americas,60.523,5106.654313 Chile,1972,9717524,Americas,63.441,5494.024437 Chile,1977,10599793,Americas,67.052,4756.763836 Chile,1982,11487112,Americas,70.565,5095.665738 Chile,1987,12463354,Americas,72.492,5547.063754 Chile,1992,13572994,Americas,74.126,7596.125964 Chile,1997,14599929,Americas,75.816,10118.05318 Chile,2002,15497046,Americas,77.86,10778.78385 Chile,2007,16284741,Americas,78.553,13171.63885 China,1952,556263527.999989,Asia,44,400.448610699994 China,1957,637408000,Asia,50.54896,575.9870009 China,1962,665770000,Asia,44.50136,487.6740183 China,1967,754550000,Asia,58.38112,612.7056934 China,1972,862030000,Asia,63.11888,676.9000921 China,1977,943455000,Asia,63.96736,741.2374699 China,1982,1000281000,Asia,65.525,962.4213805 China,1987,1084035000,Asia,67.274,1378.904018 China,1992,1164970000,Asia,68.69,1655.784158 China,1997,1230075000,Asia,70.426,2289.234136 China,2002,1280400000,Asia,72.028,3119.280896 China,2007,1318683096,Asia,72.961,4959.114854 Colombia,1952,12350771,Americas,50.643,2144.115096 Colombia,1957,14485993,Americas,55.118,2323.805581 Colombia,1962,17009885,Americas,57.863,2492.351109 Colombia,1967,19764027,Americas,59.963,2678.729839 Colombia,1972,22542890,Americas,61.623,3264.660041 Colombia,1977,25094412,Americas,63.837,3815.80787 Colombia,1982,27764644,Americas,66.653,4397.575659 Colombia,1987,30964245,Americas,67.768,4903.2191 Colombia,1992,34202721,Americas,68.421,5444.648617 Colombia,1997,37657830,Americas,70.313,6117.361746 Colombia,2002,41008227,Americas,71.682,5755.259962 Colombia,2007,44227550,Americas,72.889,7006.580419 Comoros,1952,153936,Africa,40.715,1102.990936 Comoros,1957,170928,Africa,42.46,1211.148548 Comoros,1962,191689,Africa,44.467,1406.648278 Comoros,1967,217378,Africa,46.472,1876.029643 Comoros,1972,250027,Africa,48.944,1937.577675 Comoros,1977,304739,Africa,50.939,1172.603047 Comoros,1982,348643,Africa,52.933,1267.100083 Comoros,1987,395114,Africa,54.926,1315.980812 Comoros,1992,454429,Africa,57.939,1246.90737 Comoros,1997,527982,Africa,60.66,1173.618235 Comoros,2002,614382,Africa,62.974,1075.811558 Comoros,2007,710960,Africa,65.152,986.1478792 Congo Dem. Rep.,1952,14100005,Africa,39.143,780.5423257 Congo Dem. Rep.,1957,15577932,Africa,40.652,905.8602303 Congo Dem. Rep.,1962,17486434,Africa,42.122,896.3146335 Congo Dem. Rep.,1967,19941073,Africa,44.056,861.5932424 Congo Dem. Rep.,1972,23007669,Africa,45.989,904.8960685 Congo Dem. Rep.,1977,26480870,Africa,47.804,795.757282 Congo Dem. Rep.,1982,30646495,Africa,47.784,673.7478181 Congo Dem. Rep.,1987,35481645,Africa,47.412,672.774812 Congo Dem. Rep.,1992,41672143,Africa,45.548,457.7191807 Congo Dem. Rep.,1997,47798986,Africa,42.587,312.188423 Congo Dem. Rep.,2002,55379852,Africa,44.966,241.1658765 Congo Dem. Rep.,2007,64606759,Africa,46.462,277.5518587 Congo Rep.,1952,854885,Africa,42.111,2125.621418 Congo Rep.,1957,940458,Africa,45.053,2315.056572 Congo Rep.,1962,1047924,Africa,48.435,2464.783157 Congo Rep.,1967,1179760,Africa,52.04,2677.939642 Congo Rep.,1972,1340458,Africa,54.907,3213.152683 Congo Rep.,1977,1536769,Africa,55.625,3259.178978 Congo Rep.,1982,1774735,Africa,56.695,4879.507522 Congo Rep.,1987,2064095,Africa,57.47,4201.194937 Congo Rep.,1992,2409073,Africa,56.433,4016.239529 Congo Rep.,1997,2800947,Africa,52.962,3484.164376 Congo Rep.,2002,3328795,Africa,52.97,3484.06197 Congo Rep.,2007,3800610,Africa,55.322,3632.557798 Costa Rica,1952,926317,Americas,57.206,2627.009471 Costa Rica,1957,1112300,Americas,60.026,2990.010802 Costa Rica,1962,1345187,Americas,62.842,3460.937025 Costa Rica,1967,1588717,Americas,65.424,4161.727834 Costa Rica,1972,1834796,Americas,67.849,5118.146939 Costa Rica,1977,2108457,Americas,70.75,5926.876967 Costa Rica,1982,2424367,Americas,73.45,5262.734751 Costa Rica,1987,2799811,Americas,74.752,5629.915318 Costa Rica,1992,3173216,Americas,75.713,6160.416317 Costa Rica,1997,3518107,Americas,77.26,6677.045314 Costa Rica,2002,3834934,Americas,78.123,7723.447195 Costa Rica,2007,4133884,Americas,78.782,9645.06142 "Cote d'Ivoire",1952,2977019,Africa,40.477,1388.594732 "Cote d'Ivoire",1957,3300000,Africa,42.469,1500.895925 "Cote d'Ivoire",1962,3832408,Africa,44.93,1728.869428 "Cote d'Ivoire",1967,4744870,Africa,47.35,2052.050473 "Cote d'Ivoire",1972,6071696,Africa,49.801,2378.201111 "Cote d'Ivoire",1977,7459574,Africa,52.374,2517.736547 "Cote d'Ivoire",1982,9025951,Africa,53.983,2602.710169 "Cote d'Ivoire",1987,10761098,Africa,54.655,2156.956069 "Cote d'Ivoire",1992,12772596,Africa,52.044,1648.073791 "Cote d'Ivoire",1997,14625967,Africa,47.991,1786.265407 "Cote d'Ivoire",2002,16252726,Africa,46.832,1648.800823 "Cote d'Ivoire",2007,18013409,Africa,48.328,1544.750112 Croatia,1952,3882229,Europe,61.21,3119.23652 Croatia,1957,3991242,Europe,64.77,4338.231617 Croatia,1962,4076557,Europe,67.13,5477.890018 Croatia,1967,4174366,Europe,68.5,6960.297861 Croatia,1972,4225310,Europe,69.61,9164.090127 Croatia,1977,4318673,Europe,70.64,11305.38517 Croatia,1982,4413368,Europe,70.46,13221.82184 Croatia,1987,4484310,Europe,71.52,13822.58394 Croatia,1992,4494013,Europe,72.527,8447.794873 Croatia,1997,4444595,Europe,73.68,9875.604515 Croatia,2002,4481020,Europe,74.876,11628.38895 Croatia,2007,4493312,Europe,75.748,14619.22272 Cuba,1952,6007797,Americas,59.421,5586.53878 Cuba,1957,6640752,Americas,62.325,6092.174359 Cuba,1962,7254373,Americas,65.246,5180.75591 Cuba,1967,8139332,Americas,68.29,5690.268015 Cuba,1972,8831348,Americas,70.723,5305.445256 Cuba,1977,9537988,Americas,72.649,6380.494966 Cuba,1982,9789224,Americas,73.717,7316.918107 Cuba,1987,10239839,Americas,74.174,7532.924763 Cuba,1992,10723260,Americas,74.414,5592.843963 Cuba,1997,10983007,Americas,76.151,5431.990415 Cuba,2002,11226999,Americas,77.158,6340.646683 Cuba,2007,11416987,Americas,78.273,8948.102923 Czech Republic,1952,9125183,Europe,66.87,6876.14025 Czech Republic,1957,9513758,Europe,69.03,8256.343918 Czech Republic,1962,9620282,Europe,69.9,10136.86713 Czech Republic,1967,9835109,Europe,70.38,11399.44489 Czech Republic,1972,9862158,Europe,70.29,13108.4536 Czech Republic,1977,10161915,Europe,70.71,14800.16062 Czech Republic,1982,10303704,Europe,70.96,15377.22855 Czech Republic,1987,10311597,Europe,71.58,16310.4434 Czech Republic,1992,10315702,Europe,72.4,14297.02122 Czech Republic,1997,10300707,Europe,74.01,16048.51424 Czech Republic,2002,10256295,Europe,75.51,17596.21022 Czech Republic,2007,10228744,Europe,76.486,22833.30851 Denmark,1952,4334000,Europe,70.78,9692.385245 Denmark,1957,4487831,Europe,71.81,11099.65935 Denmark,1962,4646899,Europe,72.35,13583.31351 Denmark,1967,4838800,Europe,72.96,15937.21123 Denmark,1972,4991596,Europe,73.47,18866.20721 Denmark,1977,5088419,Europe,74.69,20422.9015 Denmark,1982,5117810,Europe,74.63,21688.04048 Denmark,1987,5127024,Europe,74.8,25116.17581 Denmark,1992,5171393,Europe,75.33,26406.73985 Denmark,1997,5283663,Europe,76.11,29804.34567 Denmark,2002,5374693,Europe,77.18,32166.50006 Denmark,2007,5468120,Europe,78.332,35278.41874 Djibouti,1952,63149,Africa,34.812,2669.529475 Djibouti,1957,71851,Africa,37.328,2864.969076 Djibouti,1962,89898,Africa,39.693,3020.989263 Djibouti,1967,127617,Africa,42.074,3020.050513 Djibouti,1972,178848,Africa,44.366,3694.212352 Djibouti,1977,228694,Africa,46.519,3081.761022 Djibouti,1982,305991,Africa,48.812,2879.468067 Djibouti,1987,311025,Africa,50.04,2880.102568 Djibouti,1992,384156,Africa,51.604,2377.156192 Djibouti,1997,417908,Africa,53.157,1895.016984 Djibouti,2002,447416,Africa,53.373,1908.260867 Djibouti,2007,496374,Africa,54.791,2082.481567 Dominican Republic,1952,2491346,Americas,45.928,1397.717137 Dominican Republic,1957,2923186,Americas,49.828,1544.402995 Dominican Republic,1962,3453434,Americas,53.459,1662.137359 Dominican Republic,1967,4049146,Americas,56.751,1653.723003 Dominican Republic,1972,4671329,Americas,59.631,2189.874499 Dominican Republic,1977,5302800,Americas,61.788,2681.9889 Dominican Republic,1982,5968349,Americas,63.727,2861.092386 Dominican Republic,1987,6655297,Americas,66.046,2899.842175 Dominican Republic,1992,7351181,Americas,68.457,3044.214214 Dominican Republic,1997,7992357,Americas,69.957,3614.101285 Dominican Republic,2002,8650322,Americas,70.847,4563.808154 Dominican Republic,2007,9319622,Americas,72.235,6025.374752 Ecuador,1952,3548753,Americas,48.357,3522.110717 Ecuador,1957,4058385,Americas,51.356,3780.546651 Ecuador,1962,4681707,Americas,54.64,4086.114078 Ecuador,1967,5432424,Americas,56.678,4579.074215 Ecuador,1972,6298651,Americas,58.796,5280.99471 Ecuador,1977,7278866,Americas,61.31,6679.62326 Ecuador,1982,8365850,Americas,64.342,7213.791267 Ecuador,1987,9545158,Americas,67.231,6481.776993 Ecuador,1992,10748394,Americas,69.613,7103.702595 Ecuador,1997,11911819,Americas,72.312,7429.455877 Ecuador,2002,12921234,Americas,74.173,5773.044512 Ecuador,2007,13755680,Americas,74.994,6873.262326 Egypt,1952,22223309,Africa,41.893,1418.822445 Egypt,1957,25009741,Africa,44.444,1458.915272 Egypt,1962,28173309,Africa,46.992,1693.335853 Egypt,1967,31681188,Africa,49.293,1814.880728 Egypt,1972,34807417,Africa,51.137,2024.008147 Egypt,1977,38783863,Africa,53.319,2785.493582 Egypt,1982,45681811,Africa,56.006,3503.729636 Egypt,1987,52799062,Africa,59.797,3885.46071 Egypt,1992,59402198,Africa,63.674,3794.755195 Egypt,1997,66134291,Africa,67.217,4173.181797 Egypt,2002,73312559,Africa,69.806,4754.604414 Egypt,2007,80264543,Africa,71.338,5581.180998 El Salvador,1952,2042865,Americas,45.262,3048.3029 El Salvador,1957,2355805,Americas,48.57,3421.523218 El Salvador,1962,2747687,Americas,52.307,3776.803627 El Salvador,1967,3232927,Americas,55.855,4358.595393 El Salvador,1972,3790903,Americas,58.207,4520.246008 El Salvador,1977,4282586,Americas,56.696,5138.922374 El Salvador,1982,4474873,Americas,56.604,4098.344175 El Salvador,1987,4842194,Americas,63.154,4140.442097 El Salvador,1992,5274649,Americas,66.798,4444.2317 El Salvador,1997,5783439,Americas,69.535,5154.825496 El Salvador,2002,6353681,Americas,70.734,5351.568666 El Salvador,2007,6939688,Americas,71.878,5728.353514 Equatorial Guinea,1952,216964,Africa,34.482,375.6431231 Equatorial Guinea,1957,232922,Africa,35.983,426.0964081 Equatorial Guinea,1962,249220,Africa,37.485,582.8419714 Equatorial Guinea,1967,259864,Africa,38.987,915.5960025 Equatorial Guinea,1972,277603,Africa,40.516,672.4122571 Equatorial Guinea,1977,192675,Africa,42.024,958.5668124 Equatorial Guinea,1982,285483,Africa,43.662,927.8253427 Equatorial Guinea,1987,341244,Africa,45.664,966.8968149 Equatorial Guinea,1992,387838,Africa,47.545,1132.055034 Equatorial Guinea,1997,439971,Africa,48.245,2814.480755 Equatorial Guinea,2002,495627,Africa,49.348,7703.4959 Equatorial Guinea,2007,551201,Africa,51.579,12154.08975 Eritrea,1952,1438760,Africa,35.928,328.9405571 Eritrea,1957,1542611,Africa,38.047,344.1618859 Eritrea,1962,1666618,Africa,40.158,380.9958433 Eritrea,1967,1820319,Africa,42.189,468.7949699 Eritrea,1972,2260187,Africa,44.142,514.3242082 Eritrea,1977,2512642,Africa,44.535,505.7538077 Eritrea,1982,2637297,Africa,43.89,524.8758493 Eritrea,1987,2915959,Africa,46.453,521.1341333 Eritrea,1992,3668440,Africa,49.991,582.8585102 Eritrea,1997,4058319,Africa,53.378,913.47079 Eritrea,2002,4414865,Africa,55.24,765.3500015 Eritrea,2007,4906585,Africa,58.04,641.3695236 Ethiopia,1952,20860941,Africa,34.078,362.1462796 Ethiopia,1957,22815614,Africa,36.667,378.9041632 Ethiopia,1962,25145372,Africa,40.059,419.4564161 Ethiopia,1967,27860297,Africa,42.115,516.1186438 Ethiopia,1972,30770372,Africa,43.515,566.2439442 Ethiopia,1977,34617799,Africa,44.51,556.8083834 Ethiopia,1982,38111756,Africa,44.916,577.8607471 Ethiopia,1987,42999530,Africa,46.684,573.7413142 Ethiopia,1992,52088559,Africa,48.091,421.3534653 Ethiopia,1997,59861301,Africa,49.402,515.8894013 Ethiopia,2002,67946797,Africa,50.725,530.0535319 Ethiopia,2007,76511887,Africa,52.947,690.8055759 Finland,1952,4090500,Europe,66.55,6424.519071 Finland,1957,4324000,Europe,67.49,7545.415386 Finland,1962,4491443,Europe,68.75,9371.842561 Finland,1967,4605744,Europe,69.83,10921.63626 Finland,1972,4639657,Europe,70.87,14358.8759 Finland,1977,4738902,Europe,72.52,15605.42283 Finland,1982,4826933,Europe,74.55,18533.15761 Finland,1987,4931729,Europe,74.83,21141.01223 Finland,1992,5041039,Europe,75.7,20647.16499 Finland,1997,5134406,Europe,77.13,23723.9502 Finland,2002,5193039,Europe,78.37,28204.59057 Finland,2007,5238460,Europe,79.313,33207.0844 France,1952,42459667,Europe,67.41,7029.809327 France,1957,44310863,Europe,68.93,8662.834898 France,1962,47124000,Europe,70.51,10560.48553 France,1967,49569000,Europe,71.55,12999.91766 France,1972,51732000,Europe,72.38,16107.19171 France,1977,53165019,Europe,73.83,18292.63514 France,1982,54433565,Europe,74.89,20293.89746 France,1987,55630100,Europe,76.34,22066.44214 France,1992,57374179,Europe,77.46,24703.79615 France,1997,58623428,Europe,78.64,25889.78487 France,2002,59925035,Europe,79.59,28926.03234 France,2007,61083916,Europe,80.657,30470.0167 Gabon,1952,420702,Africa,37.003,4293.476475 Gabon,1957,434904,Africa,38.999,4976.198099 Gabon,1962,455661,Africa,40.489,6631.459222 Gabon,1967,489004,Africa,44.598,8358.761987 Gabon,1972,537977,Africa,48.69,11401.94841 Gabon,1977,706367,Africa,52.79,21745.57328 Gabon,1982,753874,Africa,56.564,15113.36194 Gabon,1987,880397,Africa,60.19,11864.40844 Gabon,1992,985739,Africa,61.366,13522.15752 Gabon,1997,1126189,Africa,60.461,14722.84188 Gabon,2002,1299304,Africa,56.761,12521.71392 Gabon,2007,1454867,Africa,56.735,13206.48452 Gambia,1952,284320,Africa,30,485.2306591 Gambia,1957,323150,Africa,32.065,520.9267111 Gambia,1962,374020,Africa,33.896,599.650276 Gambia,1967,439593,Africa,35.857,734.7829124 Gambia,1972,517101,Africa,38.308,756.0868363 Gambia,1977,608274,Africa,41.842,884.7552507 Gambia,1982,715523,Africa,45.58,835.8096108 Gambia,1987,848406,Africa,49.265,611.6588611 Gambia,1992,1025384,Africa,52.644,665.6244126 Gambia,1997,1235767,Africa,55.861,653.7301704 Gambia,2002,1457766,Africa,58.041,660.5855997 Gambia,2007,1688359,Africa,59.448,752.7497265 Germany,1952,69145952,Europe,67.5,7144.114393 Germany,1957,71019069,Europe,69.1,10187.82665 Germany,1962,73739117,Europe,70.3,12902.46291 Germany,1967,76368453,Europe,70.8,14745.62561 Germany,1972,78717088,Europe,71,18016.18027 Germany,1977,78160773,Europe,72.5,20512.92123 Germany,1982,78335266,Europe,73.8,22031.53274 Germany,1987,77718298,Europe,74.847,24639.18566 Germany,1992,80597764,Europe,76.07,26505.30317 Germany,1997,82011073,Europe,77.34,27788.88416 Germany,2002,82350671,Europe,78.67,30035.80198 Germany,2007,82400996,Europe,79.406,32170.37442 Ghana,1952,5581001,Africa,43.149,911.2989371 Ghana,1957,6391288,Africa,44.779,1043.561537 Ghana,1962,7355248,Africa,46.452,1190.041118 Ghana,1967,8490213,Africa,48.072,1125.69716 Ghana,1972,9354120,Africa,49.875,1178.223708 Ghana,1977,10538093,Africa,51.756,993.2239571 Ghana,1982,11400338,Africa,53.744,876.032569 Ghana,1987,14168101,Africa,55.729,847.0061135 Ghana,1992,16278738,Africa,57.501,925.060154 Ghana,1997,18418288,Africa,58.556,1005.245812 Ghana,2002,20550751,Africa,58.453,1111.984578 Ghana,2007,22873338,Africa,60.022,1327.60891 Greece,1952,7733250,Europe,65.86,3530.690067 Greece,1957,8096218,Europe,67.86,4916.299889 Greece,1962,8448233,Europe,69.51,6017.190733 Greece,1967,8716441,Europe,71,8513.097016 Greece,1972,8888628,Europe,72.34,12724.82957 Greece,1977,9308479,Europe,73.68,14195.52428 Greece,1982,9786480,Europe,75.24,15268.42089 Greece,1987,9974490,Europe,76.67,16120.52839 Greece,1992,10325429,Europe,77.03,17541.49634 Greece,1997,10502372,Europe,77.869,18747.69814 Greece,2002,10603863,Europe,78.256,22514.2548 Greece,2007,10706290,Europe,79.483,27538.41188 Guatemala,1952,3146381,Americas,42.023,2428.237769 Guatemala,1957,3640876,Americas,44.142,2617.155967 Guatemala,1962,4208858,Americas,46.954,2750.364446 Guatemala,1967,4690773,Americas,50.016,3242.531147 Guatemala,1972,5149581,Americas,53.738,4031.408271 Guatemala,1977,5703430,Americas,56.029,4879.992748 Guatemala,1982,6395630,Americas,58.137,4820.49479 Guatemala,1987,7326406,Americas,60.782,4246.485974 Guatemala,1992,8486949,Americas,63.373,4439.45084 Guatemala,1997,9803875,Americas,66.322,4684.313807 Guatemala,2002,11178650,Americas,68.978,4858.347495 Guatemala,2007,12572928,Americas,70.259,5186.050003 Guinea,1952,2664249,Africa,33.609,510.1964923 Guinea,1957,2876726,Africa,34.558,576.2670245 Guinea,1962,3140003,Africa,35.753,686.3736739 Guinea,1967,3451418,Africa,37.197,708.7595409 Guinea,1972,3811387,Africa,38.842,741.6662307 Guinea,1977,4227026,Africa,40.762,874.6858643 Guinea,1982,4710497,Africa,42.891,857.2503577 Guinea,1987,5650262,Africa,45.552,805.5724718 Guinea,1992,6990574,Africa,48.576,794.3484384 Guinea,1997,8048834,Africa,51.455,869.4497668 Guinea,2002,8807818,Africa,53.676,945.5835837 Guinea,2007,9947814,Africa,56.007,942.6542111 Guinea-Bissau,1952,580653,Africa,32.5,299.850319 Guinea-Bissau,1957,601095,Africa,33.489,431.7904566 Guinea-Bissau,1962,627820,Africa,34.488,522.0343725 Guinea-Bissau,1967,601287,Africa,35.492,715.5806402 Guinea-Bissau,1972,625361,Africa,36.486,820.2245876 Guinea-Bissau,1977,745228,Africa,37.465,764.7259628 Guinea-Bissau,1982,825987,Africa,39.327,838.1239671 Guinea-Bissau,1987,927524,Africa,41.245,736.4153921 Guinea-Bissau,1992,1050938,Africa,43.266,745.5398706 Guinea-Bissau,1997,1193708,Africa,44.873,796.6644681 Guinea-Bissau,2002,1332459,Africa,45.504,575.7047176 Guinea-Bissau,2007,1472041,Africa,46.388,579.231743 Haiti,1952,3201488,Americas,37.579,1840.366939 Haiti,1957,3507701,Americas,40.696,1726.887882 Haiti,1962,3880130,Americas,43.59,1796.589032 Haiti,1967,4318137,Americas,46.243,1452.057666 Haiti,1972,4698301,Americas,48.042,1654.456946 Haiti,1977,4908554,Americas,49.923,1874.298931 Haiti,1982,5198399,Americas,51.461,2011.159549 Haiti,1987,5756203,Americas,53.636,1823.015995 Haiti,1992,6326682,Americas,55.089,1456.309517 Haiti,1997,6913545,Americas,56.671,1341.726931 Haiti,2002,7607651,Americas,58.137,1270.364932 Haiti,2007,8502814,Americas,60.916,1201.637154 Honduras,1952,1517453,Americas,41.912,2194.926204 Honduras,1957,1770390,Americas,44.665,2220.487682 Honduras,1962,2090162,Americas,48.041,2291.156835 Honduras,1967,2500689,Americas,50.924,2538.269358 Honduras,1972,2965146,Americas,53.884,2529.842345 Honduras,1977,3055235,Americas,57.402,3203.208066 Honduras,1982,3669448,Americas,60.909,3121.760794 Honduras,1987,4372203,Americas,64.492,3023.096699 Honduras,1992,5077347,Americas,66.399,3081.694603 Honduras,1997,5867957,Americas,67.659,3160.454906 Honduras,2002,6677328,Americas,68.565,3099.72866 Honduras,2007,7483763,Americas,70.198,3548.330846 Hong Kong China,1952,2125900,Asia,60.96,3054.421209 Hong Kong China,1957,2736300,Asia,64.75,3629.076457 Hong Kong China,1962,3305200,Asia,67.65,4692.648272 Hong Kong China,1967,3722800,Asia,70,6197.962814 Hong Kong China,1972,4115700,Asia,72,8315.928145 Hong Kong China,1977,4583700,Asia,73.6,11186.14125 Hong Kong China,1982,5264500,Asia,75.45,14560.53051 Hong Kong China,1987,5584510,Asia,76.2,20038.47269 Hong Kong China,1992,5829696,Asia,77.601,24757.60301 Hong Kong China,1997,6495918,Asia,80,28377.63219 Hong Kong China,2002,6762476,Asia,81.495,30209.01516 Hong Kong China,2007,6980412,Asia,82.208,39724.97867 Hungary,1952,9504000,Europe,64.03,5263.673816 Hungary,1957,9839000,Europe,66.41,6040.180011 Hungary,1962,10063000,Europe,67.96,7550.359877 Hungary,1967,10223422,Europe,69.5,9326.64467 Hungary,1972,10394091,Europe,69.76,10168.65611 Hungary,1977,10637171,Europe,69.95,11674.83737 Hungary,1982,10705535,Europe,69.39,12545.99066 Hungary,1987,10612740,Europe,69.58,12986.47998 Hungary,1992,10348684,Europe,69.17,10535.62855 Hungary,1997,10244684,Europe,71.04,11712.7768 Hungary,2002,10083313,Europe,72.59,14843.93556 Hungary,2007,9956108,Europe,73.338,18008.94444 Iceland,1952,147962,Europe,72.49,7267.688428 Iceland,1957,165110,Europe,73.47,9244.001412 Iceland,1962,182053,Europe,73.68,10350.15906 Iceland,1967,198676,Europe,73.73,13319.89568 Iceland,1972,209275,Europe,74.46,15798.06362 Iceland,1977,221823,Europe,76.11,19654.96247 Iceland,1982,233997,Europe,76.99,23269.6075 Iceland,1987,244676,Europe,77.23,26923.20628 Iceland,1992,259012,Europe,78.77,25144.39201 Iceland,1997,271192,Europe,78.95,28061.09966 Iceland,2002,288030,Europe,80.5,31163.20196 Iceland,2007,301931,Europe,81.757,36180.78919 India,1952,3.72e+08,Asia,37.373,546.5657493 India,1957,4.09e+08,Asia,40.249,590.061996 India,1962,4.54e+08,Asia,43.605,658.3471509 India,1967,5.06e+08,Asia,47.193,700.7706107 India,1972,5.67e+08,Asia,50.651,724.032527 India,1977,6.34e+08,Asia,54.208,813.337323 India,1982,7.08e+08,Asia,56.596,855.7235377 India,1987,7.88e+08,Asia,58.553,976.5126756 India,1992,8.72e+08,Asia,60.223,1164.406809 India,1997,9.59e+08,Asia,61.765,1458.817442 India,2002,1034172547,Asia,62.879,1746.769454 India,2007,1110396331,Asia,64.698,2452.210407 Indonesia,1952,82052000,Asia,37.468,749.6816546 Indonesia,1957,90124000,Asia,39.918,858.9002707 Indonesia,1962,99028000,Asia,42.518,849.2897701 Indonesia,1967,109343000,Asia,45.964,762.4317721 Indonesia,1972,121282000,Asia,49.203,1111.107907 Indonesia,1977,136725000,Asia,52.702,1382.702056 Indonesia,1982,153343000,Asia,56.159,1516.872988 Indonesia,1987,169276000,Asia,60.137,1748.356961 Indonesia,1992,184816000,Asia,62.681,2383.140898 Indonesia,1997,199278000,Asia,66.041,3119.335603 Indonesia,2002,211060000,Asia,68.588,2873.91287 Indonesia,2007,223547000,Asia,70.65,3540.651564 Iran,1952,17272000,Asia,44.869,3035.326002 Iran,1957,19792000,Asia,47.181,3290.257643 Iran,1962,22874000,Asia,49.325,4187.329802 Iran,1967,26538000,Asia,52.469,5906.731805 Iran,1972,30614000,Asia,55.234,9613.818607 Iran,1977,35480679,Asia,57.702,11888.59508 Iran,1982,43072751,Asia,59.62,7608.334602 Iran,1987,51889696,Asia,63.04,6642.881371 Iran,1992,60397973,Asia,65.742,7235.653188 Iran,1997,63327987,Asia,68.042,8263.590301 Iran,2002,66907826,Asia,69.451,9240.761975 Iran,2007,69453570,Asia,70.964,11605.71449 Iraq,1952,5441766,Asia,45.32,4129.766056 Iraq,1957,6248643,Asia,48.437,6229.333562 Iraq,1962,7240260,Asia,51.457,8341.737815 Iraq,1967,8519282,Asia,54.459,8931.459811 Iraq,1972,10061506,Asia,56.95,9576.037596 Iraq,1977,11882916,Asia,60.413,14688.23507 Iraq,1982,14173318,Asia,62.038,14517.90711 Iraq,1987,16543189,Asia,65.044,11643.57268 Iraq,1992,17861905,Asia,59.461,3745.640687 Iraq,1997,20775703,Asia,58.811,3076.239795 Iraq,2002,24001816,Asia,57.046,4390.717312 Iraq,2007,27499638,Asia,59.545,4471.061906 Ireland,1952,2952156,Europe,66.91,5210.280328 Ireland,1957,2878220,Europe,68.9,5599.077872 Ireland,1962,2830000,Europe,70.29,6631.597314 Ireland,1967,2900100,Europe,71.08,7655.568963 Ireland,1972,3024400,Europe,71.28,9530.772896 Ireland,1977,3271900,Europe,72.03,11150.98113 Ireland,1982,3480000,Europe,73.1,12618.32141 Ireland,1987,3539900,Europe,74.36,13872.86652 Ireland,1992,3557761,Europe,75.467,17558.81555 Ireland,1997,3667233,Europe,76.122,24521.94713 Ireland,2002,3879155,Europe,77.783,34077.04939 Ireland,2007,4109086,Europe,78.885,40675.99635 Israel,1952,1620914,Asia,65.39,4086.522128 Israel,1957,1944401,Asia,67.84,5385.278451 Israel,1962,2310904,Asia,69.39,7105.630706 Israel,1967,2693585,Asia,70.75,8393.741404 Israel,1972,3095893,Asia,71.63,12786.93223 Israel,1977,3495918,Asia,73.06,13306.61921 Israel,1982,3858421,Asia,74.45,15367.0292 Israel,1987,4203148,Asia,75.6,17122.47986 Israel,1992,4936550,Asia,76.93,18051.52254 Israel,1997,5531387,Asia,78.269,20896.60924 Israel,2002,6029529,Asia,79.696,21905.59514 Israel,2007,6426679,Asia,80.745,25523.2771 Italy,1952,47666000,Europe,65.94,4931.404155 Italy,1957,49182000,Europe,67.81,6248.656232 Italy,1962,50843200,Europe,69.24,8243.58234 Italy,1967,52667100,Europe,71.06,10022.40131 Italy,1972,54365564,Europe,72.19,12269.27378 Italy,1977,56059245,Europe,73.48,14255.98475 Italy,1982,56535636,Europe,74.98,16537.4835 Italy,1987,56729703,Europe,76.42,19207.23482 Italy,1992,56840847,Europe,77.44,22013.64486 Italy,1997,57479469,Europe,78.82,24675.02446 Italy,2002,57926999,Europe,80.24,27968.09817 Italy,2007,58147733,Europe,80.546,28569.7197 Jamaica,1952,1426095,Americas,58.53,2898.530881 Jamaica,1957,1535090,Americas,62.61,4756.525781 Jamaica,1962,1665128,Americas,65.61,5246.107524 Jamaica,1967,1861096,Americas,67.51,6124.703451 Jamaica,1972,1997616,Americas,69,7433.889293 Jamaica,1977,2156814,Americas,70.11,6650.195573 Jamaica,1982,2298309,Americas,71.21,6068.05135 Jamaica,1987,2326606,Americas,71.77,6351.237495 Jamaica,1992,2378618,Americas,71.766,7404.923685 Jamaica,1997,2531311,Americas,72.262,7121.924704 Jamaica,2002,2664659,Americas,72.047,6994.774861 Jamaica,2007,2780132,Americas,72.567,7320.880262 Japan,1952,86459025,Asia,63.03,3216.956347 Japan,1957,91563009,Asia,65.5,4317.694365 Japan,1962,95831757,Asia,68.73,6576.649461 Japan,1967,100825279,Asia,71.43,9847.788607 Japan,1972,107188273,Asia,73.42,14778.78636 Japan,1977,113872473,Asia,75.38,16610.37701 Japan,1982,118454974,Asia,77.11,19384.10571 Japan,1987,122091325,Asia,78.67,22375.94189 Japan,1992,124329269,Asia,79.36,26824.89511 Japan,1997,125956499,Asia,80.69,28816.58499 Japan,2002,127065841,Asia,82,28604.5919 Japan,2007,127467972,Asia,82.603,31656.06806 Jordan,1952,607914,Asia,43.158,1546.907807 Jordan,1957,746559,Asia,45.669,1886.080591 Jordan,1962,933559,Asia,48.126,2348.009158 Jordan,1967,1255058,Asia,51.629,2741.796252 Jordan,1972,1613551,Asia,56.528,2110.856309 Jordan,1977,1937652,Asia,61.134,2852.351568 Jordan,1982,2347031,Asia,63.739,4161.415959 Jordan,1987,2820042,Asia,65.869,4448.679912 Jordan,1992,3867409,Asia,68.015,3431.593647 Jordan,1997,4526235,Asia,69.772,3645.379572 Jordan,2002,5307470,Asia,71.263,3844.917194 Jordan,2007,6053193,Asia,72.535,4519.461171 Kenya,1952,6464046,Africa,42.27,853.540919 Kenya,1957,7454779,Africa,44.686,944.4383152 Kenya,1962,8678557,Africa,47.949,896.9663732 Kenya,1967,10191512,Africa,50.654,1056.736457 Kenya,1972,12044785,Africa,53.559,1222.359968 Kenya,1977,14500404,Africa,56.155,1267.613204 Kenya,1982,17661452,Africa,58.766,1348.225791 Kenya,1987,21198082,Africa,59.339,1361.936856 Kenya,1992,25020539,Africa,59.285,1341.921721 Kenya,1997,28263827,Africa,54.407,1360.485021 Kenya,2002,31386842,Africa,50.992,1287.514732 Kenya,2007,35610177,Africa,54.11,1463.249282 Korea Dem. Rep.,1952,8865488,Asia,50.056,1088.277758 Korea Dem. Rep.,1957,9411381,Asia,54.081,1571.134655 Korea Dem. Rep.,1962,10917494,Asia,56.656,1621.693598 Korea Dem. Rep.,1967,12617009,Asia,59.942,2143.540609 Korea Dem. Rep.,1972,14781241,Asia,63.983,3701.621503 Korea Dem. Rep.,1977,16325320,Asia,67.159,4106.301249 Korea Dem. Rep.,1982,17647518,Asia,69.1,4106.525293 Korea Dem. Rep.,1987,19067554,Asia,70.647,4106.492315 Korea Dem. Rep.,1992,20711375,Asia,69.978,3726.063507 Korea Dem. Rep.,1997,21585105,Asia,67.727,1690.756814 Korea Dem. Rep.,2002,22215365,Asia,66.662,1646.758151 Korea Dem. Rep.,2007,23301725,Asia,67.297,1593.06548 Korea Rep.,1952,20947571,Asia,47.453,1030.592226 Korea Rep.,1957,22611552,Asia,52.681,1487.593537 Korea Rep.,1962,26420307,Asia,55.292,1536.344387 Korea Rep.,1967,30131000,Asia,57.716,2029.228142 Korea Rep.,1972,33505000,Asia,62.612,3030.87665 Korea Rep.,1977,36436000,Asia,64.766,4657.22102 Korea Rep.,1982,39326000,Asia,67.123,5622.942464 Korea Rep.,1987,41622000,Asia,69.81,8533.088805 Korea Rep.,1992,43805450,Asia,72.244,12104.27872 Korea Rep.,1997,46173816,Asia,74.647,15993.52796 Korea Rep.,2002,47969150,Asia,77.045,19233.98818 Korea Rep.,2007,49044790,Asia,78.623,23348.13973 Kuwait,1952,160000,Asia,55.565,108382.3529 Kuwait,1957,212846,Asia,58.033,113523.1329 Kuwait,1962,358266,Asia,60.47,95458.11176 Kuwait,1967,575003,Asia,64.624,80894.88326 Kuwait,1972,841934,Asia,67.712,109347.867 Kuwait,1977,1140357,Asia,69.343,59265.47714 Kuwait,1982,1497494,Asia,71.309,31354.03573 Kuwait,1987,1891487,Asia,74.174,28118.42998 Kuwait,1992,1418095,Asia,75.19,34932.91959 Kuwait,1997,1765345,Asia,76.156,40300.61996 Kuwait,2002,2111561,Asia,76.904,35110.10566 Kuwait,2007,2505559,Asia,77.588,47306.98978 Lebanon,1952,1439529,Asia,55.928,4834.804067 Lebanon,1957,1647412,Asia,59.489,6089.786934 Lebanon,1962,1886848,Asia,62.094,5714.560611 Lebanon,1967,2186894,Asia,63.87,6006.983042 Lebanon,1972,2680018,Asia,65.421,7486.384341 Lebanon,1977,3115787,Asia,66.099,8659.696836 Lebanon,1982,3086876,Asia,66.983,7640.519521 Lebanon,1987,3089353,Asia,67.926,5377.091329 Lebanon,1992,3219994,Asia,69.292,6890.806854 Lebanon,1997,3430388,Asia,70.265,8754.96385 Lebanon,2002,3677780,Asia,71.028,9313.93883 Lebanon,2007,3921278,Asia,71.993,10461.05868 Lesotho,1952,748747,Africa,42.138,298.8462121 Lesotho,1957,813338,Africa,45.047,335.9971151 Lesotho,1962,893143,Africa,47.747,411.8006266 Lesotho,1967,996380,Africa,48.492,498.6390265 Lesotho,1972,1116779,Africa,49.767,496.5815922 Lesotho,1977,1251524,Africa,52.208,745.3695408 Lesotho,1982,1411807,Africa,55.078,797.2631074 Lesotho,1987,1599200,Africa,57.18,773.9932141 Lesotho,1992,1803195,Africa,59.685,977.4862725 Lesotho,1997,1982823,Africa,55.558,1186.147994 Lesotho,2002,2046772,Africa,44.593,1275.184575 Lesotho,2007,2012649,Africa,42.592,1569.331442 Liberia,1952,863308,Africa,38.48,575.5729961 Liberia,1957,975950,Africa,39.486,620.9699901 Liberia,1962,1112796,Africa,40.502,634.1951625 Liberia,1967,1279406,Africa,41.536,713.6036483 Liberia,1972,1482628,Africa,42.614,803.0054535 Liberia,1977,1703617,Africa,43.764,640.3224383 Liberia,1982,1956875,Africa,44.852,572.1995694 Liberia,1987,2269414,Africa,46.027,506.1138573 Liberia,1992,1912974,Africa,40.802,636.6229191 Liberia,1997,2200725,Africa,42.221,609.1739508 Liberia,2002,2814651,Africa,43.753,531.4823679 Liberia,2007,3193942,Africa,45.678,414.5073415 Libya,1952,1019729,Africa,42.723,2387.54806 Libya,1957,1201578,Africa,45.289,3448.284395 Libya,1962,1441863,Africa,47.808,6757.030816 Libya,1967,1759224,Africa,50.227,18772.75169 Libya,1972,2183877,Africa,52.773,21011.49721 Libya,1977,2721783,Africa,57.442,21951.21176 Libya,1982,3344074,Africa,62.155,17364.27538 Libya,1987,3799845,Africa,66.234,11770.5898 Libya,1992,4364501,Africa,68.755,9640.138501 Libya,1997,4759670,Africa,71.555,9467.446056 Libya,2002,5368585,Africa,72.737,9534.677467 Libya,2007,6036914,Africa,73.952,12057.49928 Madagascar,1952,4762912,Africa,36.681,1443.011715 Madagascar,1957,5181679,Africa,38.865,1589.20275 Madagascar,1962,5703324,Africa,40.848,1643.38711 Madagascar,1967,6334556,Africa,42.881,1634.047282 Madagascar,1972,7082430,Africa,44.851,1748.562982 Madagascar,1977,8007166,Africa,46.881,1544.228586 Madagascar,1982,9171477,Africa,48.969,1302.878658 Madagascar,1987,10568642,Africa,49.35,1155.441948 Madagascar,1992,12210395,Africa,52.214,1040.67619 Madagascar,1997,14165114,Africa,54.978,986.2958956 Madagascar,2002,16473477,Africa,57.286,894.6370822 Madagascar,2007,19167654,Africa,59.443,1044.770126 Malawi,1952,2917802,Africa,36.256,369.1650802 Malawi,1957,3221238,Africa,37.207,416.3698064 Malawi,1962,3628608,Africa,38.41,427.9010856 Malawi,1967,4147252,Africa,39.487,495.5147806 Malawi,1972,4730997,Africa,41.766,584.6219709 Malawi,1977,5637246,Africa,43.767,663.2236766 Malawi,1982,6502825,Africa,45.642,632.8039209 Malawi,1987,7824747,Africa,47.457,635.5173634 Malawi,1992,10014249,Africa,49.42,563.2000145 Malawi,1997,10419991,Africa,47.495,692.2758103 Malawi,2002,11824495,Africa,45.009,665.4231186 Malawi,2007,13327079,Africa,48.303,759.3499101 Malaysia,1952,6748378,Asia,48.463,1831.132894 Malaysia,1957,7739235,Asia,52.102,1810.066992 Malaysia,1962,8906385,Asia,55.737,2036.884944 Malaysia,1967,10154878,Asia,59.371,2277.742396 Malaysia,1972,11441462,Asia,63.01,2849.09478 Malaysia,1977,12845381,Asia,65.256,3827.921571 Malaysia,1982,14441916,Asia,68,4920.355951 Malaysia,1987,16331785,Asia,69.5,5249.802653 Malaysia,1992,18319502,Asia,70.693,7277.912802 Malaysia,1997,20476091,Asia,71.938,10132.90964 Malaysia,2002,22662365,Asia,73.044,10206.97794 Malaysia,2007,24821286,Asia,74.241,12451.6558 Mali,1952,3838168,Africa,33.685,452.3369807 Mali,1957,4241884,Africa,35.307,490.3821867 Mali,1962,4690372,Africa,36.936,496.1743428 Mali,1967,5212416,Africa,38.487,545.0098873 Mali,1972,5828158,Africa,39.977,581.3688761 Mali,1977,6491649,Africa,41.714,686.3952693 Mali,1982,6998256,Africa,43.916,618.0140641 Mali,1987,7634008,Africa,46.364,684.1715576 Mali,1992,8416215,Africa,48.388,739.014375 Mali,1997,9384984,Africa,49.903,790.2579846 Mali,2002,10580176,Africa,51.818,951.4097518 Mali,2007,12031795,Africa,54.467,1042.581557 Mauritania,1952,1022556,Africa,40.543,743.1159097 Mauritania,1957,1076852,Africa,42.338,846.1202613 Mauritania,1962,1146757,Africa,44.248,1055.896036 Mauritania,1967,1230542,Africa,46.289,1421.145193 Mauritania,1972,1332786,Africa,48.437,1586.851781 Mauritania,1977,1456688,Africa,50.852,1497.492223 Mauritania,1982,1622136,Africa,53.599,1481.150189 Mauritania,1987,1841240,Africa,56.145,1421.603576 Mauritania,1992,2119465,Africa,58.333,1361.369784 Mauritania,1997,2444741,Africa,60.43,1483.136136 Mauritania,2002,2828858,Africa,62.247,1579.019543 Mauritania,2007,3270065,Africa,64.164,1803.151496 Mauritius,1952,516556,Africa,50.986,1967.955707 Mauritius,1957,609816,Africa,58.089,2034.037981 Mauritius,1962,701016,Africa,60.246,2529.067487 Mauritius,1967,789309,Africa,61.557,2475.387562 Mauritius,1972,851334,Africa,62.944,2575.484158 Mauritius,1977,913025,Africa,64.93,3710.982963 Mauritius,1982,992040,Africa,66.711,3688.037739 Mauritius,1987,1042663,Africa,68.74,4783.586903 Mauritius,1992,1096202,Africa,69.745,6058.253846 Mauritius,1997,1149818,Africa,70.736,7425.705295 Mauritius,2002,1200206,Africa,71.954,9021.815894 Mauritius,2007,1250882,Africa,72.801,10956.99112 Mexico,1952,30144317,Americas,50.789,3478.125529 Mexico,1957,35015548,Americas,55.19,4131.546641 Mexico,1962,41121485,Americas,58.299,4581.609385 Mexico,1967,47995559,Americas,60.11,5754.733883 Mexico,1972,55984294,Americas,62.361,6809.40669 Mexico,1977,63759976,Americas,65.032,7674.929108 Mexico,1982,71640904,Americas,67.405,9611.147541 Mexico,1987,80122492,Americas,69.498,8688.156003 Mexico,1992,88111030,Americas,71.455,9472.384295 Mexico,1997,95895146,Americas,73.67,9767.29753 Mexico,2002,102479927,Americas,74.902,10742.44053 Mexico,2007,108700891,Americas,76.195,11977.57496 Mongolia,1952,800663,Asia,42.244,786.5668575 Mongolia,1957,882134,Asia,45.248,912.6626085 Mongolia,1962,1010280,Asia,48.251,1056.353958 Mongolia,1967,1149500,Asia,51.253,1226.04113 Mongolia,1972,1320500,Asia,53.754,1421.741975 Mongolia,1977,1528000,Asia,55.491,1647.511665 Mongolia,1982,1756032,Asia,57.489,2000.603139 Mongolia,1987,2015133,Asia,60.222,2338.008304 Mongolia,1992,2312802,Asia,61.271,1785.402016 Mongolia,1997,2494803,Asia,63.625,1902.2521 Mongolia,2002,2674234,Asia,65.033,2140.739323 Mongolia,2007,2874127,Asia,66.803,3095.772271 Montenegro,1952,413834,Europe,59.164,2647.585601 Montenegro,1957,442829,Europe,61.448,3682.259903 Montenegro,1962,474528,Europe,63.728,4649.593785 Montenegro,1967,501035,Europe,67.178,5907.850937 Montenegro,1972,527678,Europe,70.636,7778.414017 Montenegro,1977,560073,Europe,73.066,9595.929905 Montenegro,1982,562548,Europe,74.101,11222.58762 Montenegro,1987,569473,Europe,74.865,11732.51017 Montenegro,1992,621621,Europe,75.435,7003.339037 Montenegro,1997,692651,Europe,75.445,6465.613349 Montenegro,2002,720230,Europe,73.981,6557.194282 Montenegro,2007,684736,Europe,74.543,9253.896111 Morocco,1952,9939217,Africa,42.873,1688.20357 Morocco,1957,11406350,Africa,45.423,1642.002314 Morocco,1962,13056604,Africa,47.924,1566.353493 Morocco,1967,14770296,Africa,50.335,1711.04477 Morocco,1972,16660670,Africa,52.862,1930.194975 Morocco,1977,18396941,Africa,55.73,2370.619976 Morocco,1982,20198730,Africa,59.65,2702.620356 Morocco,1987,22987397,Africa,62.677,2755.046991 Morocco,1992,25798239,Africa,65.393,2948.047252 Morocco,1997,28529501,Africa,67.66,2982.101858 Morocco,2002,31167783,Africa,69.615,3258.495584 Morocco,2007,33757175,Africa,71.164,3820.17523 Mozambique,1952,6446316,Africa,31.286,468.5260381 Mozambique,1957,7038035,Africa,33.779,495.5868333 Mozambique,1962,7788944,Africa,36.161,556.6863539 Mozambique,1967,8680909,Africa,38.113,566.6691539 Mozambique,1972,9809596,Africa,40.328,724.9178037 Mozambique,1977,11127868,Africa,42.495,502.3197334 Mozambique,1982,12587223,Africa,42.795,462.2114149 Mozambique,1987,12891952,Africa,42.861,389.8761846 Mozambique,1992,13160731,Africa,44.284,410.8968239 Mozambique,1997,16603334,Africa,46.344,472.3460771 Mozambique,2002,18473780,Africa,44.026,633.6179466 Mozambique,2007,19951656,Africa,42.082,823.6856205 Myanmar,1952,20092996,Asia,36.319,331 Myanmar,1957,21731844,Asia,41.905,350 Myanmar,1962,23634436,Asia,45.108,388 Myanmar,1967,25870271,Asia,49.379,349 Myanmar,1972,28466390,Asia,53.07,357 Myanmar,1977,31528087,Asia,56.059,371 Myanmar,1982,34680442,Asia,58.056,424 Myanmar,1987,38028578,Asia,58.339,385 Myanmar,1992,40546538,Asia,59.32,347 Myanmar,1997,43247867,Asia,60.328,415 Myanmar,2002,45598081,Asia,59.908,611 Myanmar,2007,47761980,Asia,62.069,944 Namibia,1952,485831,Africa,41.725,2423.780443 Namibia,1957,548080,Africa,45.226,2621.448058 Namibia,1962,621392,Africa,48.386,3173.215595 Namibia,1967,706640,Africa,51.159,3793.694753 Namibia,1972,821782,Africa,53.867,3746.080948 Namibia,1977,977026,Africa,56.437,3876.485958 Namibia,1982,1099010,Africa,58.968,4191.100511 Namibia,1987,1278184,Africa,60.835,3693.731337 Namibia,1992,1554253,Africa,61.999,3804.537999 Namibia,1997,1774766,Africa,58.909,3899.52426 Namibia,2002,1972153,Africa,51.479,4072.324751 Namibia,2007,2055080,Africa,52.906,4811.060429 Nepal,1952,9182536,Asia,36.157,545.8657229 Nepal,1957,9682338,Asia,37.686,597.9363558 Nepal,1962,10332057,Asia,39.393,652.3968593 Nepal,1967,11261690,Asia,41.472,676.4422254 Nepal,1972,12412593,Asia,43.971,674.7881296 Nepal,1977,13933198,Asia,46.748,694.1124398 Nepal,1982,15796314,Asia,49.594,718.3730947 Nepal,1987,17917180,Asia,52.537,775.6324501 Nepal,1992,20326209,Asia,55.727,897.7403604 Nepal,1997,23001113,Asia,59.426,1010.892138 Nepal,2002,25873917,Asia,61.34,1057.206311 Nepal,2007,28901790,Asia,63.785,1091.359778 Netherlands,1952,10381988,Europe,72.13,8941.571858 Netherlands,1957,11026383,Europe,72.99,11276.19344 Netherlands,1962,11805689,Europe,73.23,12790.84956 Netherlands,1967,12596822,Europe,73.82,15363.25136 Netherlands,1972,13329874,Europe,73.75,18794.74567 Netherlands,1977,13852989,Europe,75.24,21209.0592 Netherlands,1982,14310401,Europe,76.05,21399.46046 Netherlands,1987,14665278,Europe,76.83,23651.32361 Netherlands,1992,15174244,Europe,77.42,26790.94961 Netherlands,1997,15604464,Europe,78.03,30246.13063 Netherlands,2002,16122830,Europe,78.53,33724.75778 Netherlands,2007,16570613,Europe,79.762,36797.93332 New Zealand,1952,1994794,Oceania,69.39,10556.57566 New Zealand,1957,2229407,Oceania,70.26,12247.39532 New Zealand,1962,2488550,Oceania,71.24,13175.678 New Zealand,1967,2728150,Oceania,71.52,14463.91893 New Zealand,1972,2929100,Oceania,71.89,16046.03728 New Zealand,1977,3164900,Oceania,72.22,16233.7177 New Zealand,1982,3210650,Oceania,73.84,17632.4104 New Zealand,1987,3317166,Oceania,74.32,19007.19129 New Zealand,1992,3437674,Oceania,76.33,18363.32494 New Zealand,1997,3676187,Oceania,77.55,21050.41377 New Zealand,2002,3908037,Oceania,79.11,23189.80135 New Zealand,2007,4115771,Oceania,80.204,25185.00911 Nicaragua,1952,1165790,Americas,42.314,3112.363948 Nicaragua,1957,1358828,Americas,45.432,3457.415947 Nicaragua,1962,1590597,Americas,48.632,3634.364406 Nicaragua,1967,1865490,Americas,51.884,4643.393534 Nicaragua,1972,2182908,Americas,55.151,4688.593267 Nicaragua,1977,2554598,Americas,57.47,5486.371089 Nicaragua,1982,2979423,Americas,59.298,3470.338156 Nicaragua,1987,3344353,Americas,62.008,2955.984375 Nicaragua,1992,4017939,Americas,65.843,2170.151724 Nicaragua,1997,4609572,Americas,68.426,2253.023004 Nicaragua,2002,5146848,Americas,70.836,2474.548819 Nicaragua,2007,5675356,Americas,72.899,2749.320965 Niger,1952,3379468,Africa,37.444,761.879376 Niger,1957,3692184,Africa,38.598,835.5234025 Niger,1962,4076008,Africa,39.487,997.7661127 Niger,1967,4534062,Africa,40.118,1054.384891 Niger,1972,5060262,Africa,40.546,954.2092363 Niger,1977,5682086,Africa,41.291,808.8970728 Niger,1982,6437188,Africa,42.598,909.7221354 Niger,1987,7332638,Africa,44.555,668.3000228 Niger,1992,8392818,Africa,47.391,581.182725 Niger,1997,9666252,Africa,51.313,580.3052092 Niger,2002,11140655,Africa,54.496,601.0745012 Niger,2007,12894865,Africa,56.867,619.6768924 Nigeria,1952,33119096,Africa,36.324,1077.281856 Nigeria,1957,37173340,Africa,37.802,1100.592563 Nigeria,1962,41871351,Africa,39.36,1150.927478 Nigeria,1967,47287752,Africa,41.04,1014.514104 Nigeria,1972,53740085,Africa,42.821,1698.388838 Nigeria,1977,62209173,Africa,44.514,1981.951806 Nigeria,1982,73039376,Africa,45.826,1576.97375 Nigeria,1987,81551520,Africa,46.886,1385.029563 Nigeria,1992,93364244,Africa,47.472,1619.848217 Nigeria,1997,106207839,Africa,47.464,1624.941275 Nigeria,2002,119901274,Africa,46.608,1615.286395 Nigeria,2007,135031164,Africa,46.859,2013.977305 Norway,1952,3327728,Europe,72.67,10095.42172 Norway,1957,3491938,Europe,73.44,11653.97304 Norway,1962,3638919,Europe,73.47,13450.40151 Norway,1967,3786019,Europe,74.08,16361.87647 Norway,1972,3933004,Europe,74.34,18965.05551 Norway,1977,4043205,Europe,75.37,23311.34939 Norway,1982,4114787,Europe,75.97,26298.63531 Norway,1987,4186147,Europe,75.89,31540.9748 Norway,1992,4286357,Europe,77.32,33965.66115 Norway,1997,4405672,Europe,78.32,41283.16433 Norway,2002,4535591,Europe,79.05,44683.97525 Norway,2007,4627926,Europe,80.196,49357.19017 Oman,1952,507833,Asia,37.578,1828.230307 Oman,1957,561977,Asia,40.08,2242.746551 Oman,1962,628164,Asia,43.165,2924.638113 Oman,1967,714775,Asia,46.988,4720.942687 Oman,1972,829050,Asia,52.143,10618.03855 Oman,1977,1004533,Asia,57.367,11848.34392 Oman,1982,1301048,Asia,62.728,12954.79101 Oman,1987,1593882,Asia,67.734,18115.22313 Oman,1992,1915208,Asia,71.197,18616.70691 Oman,1997,2283635,Asia,72.499,19702.05581 Oman,2002,2713462,Asia,74.193,19774.83687 Oman,2007,3204897,Asia,75.64,22316.19287 Pakistan,1952,41346560,Asia,43.436,684.5971438 Pakistan,1957,46679944,Asia,45.557,747.0835292 Pakistan,1962,53100671,Asia,47.67,803.3427418 Pakistan,1967,60641899,Asia,49.8,942.4082588 Pakistan,1972,69325921,Asia,51.929,1049.938981 Pakistan,1977,78152686,Asia,54.043,1175.921193 Pakistan,1982,91462088,Asia,56.158,1443.429832 Pakistan,1987,105186881,Asia,58.245,1704.686583 Pakistan,1992,120065004,Asia,60.838,1971.829464 Pakistan,1997,135564834,Asia,61.818,2049.350521 Pakistan,2002,153403524,Asia,63.61,2092.712441 Pakistan,2007,169270617,Asia,65.483,2605.94758 Panama,1952,940080,Americas,55.191,2480.380334 Panama,1957,1063506,Americas,59.201,2961.800905 Panama,1962,1215725,Americas,61.817,3536.540301 Panama,1967,1405486,Americas,64.071,4421.009084 Panama,1972,1616384,Americas,66.216,5364.249663 Panama,1977,1839782,Americas,68.681,5351.912144 Panama,1982,2036305,Americas,70.472,7009.601598 Panama,1987,2253639,Americas,71.523,7034.779161 Panama,1992,2484997,Americas,72.462,6618.74305 Panama,1997,2734531,Americas,73.738,7113.692252 Panama,2002,2990875,Americas,74.712,7356.031934 Panama,2007,3242173,Americas,75.537,9809.185636 Paraguay,1952,1555876,Americas,62.649,1952.308701 Paraguay,1957,1770902,Americas,63.196,2046.154706 Paraguay,1962,2009813,Americas,64.361,2148.027146 Paraguay,1967,2287985,Americas,64.951,2299.376311 Paraguay,1972,2614104,Americas,65.815,2523.337977 Paraguay,1977,2984494,Americas,66.353,3248.373311 Paraguay,1982,3366439,Americas,66.874,4258.503604 Paraguay,1987,3886512,Americas,67.378,3998.875695 Paraguay,1992,4483945,Americas,68.225,4196.411078 Paraguay,1997,5154123,Americas,69.4,4247.400261 Paraguay,2002,5884491,Americas,70.755,3783.674243 Paraguay,2007,6667147,Americas,71.752,4172.838464 Peru,1952,8025700,Americas,43.902,3758.523437 Peru,1957,9146100,Americas,46.263,4245.256698 Peru,1962,10516500,Americas,49.096,4957.037982 Peru,1967,12132200,Americas,51.445,5788.09333 Peru,1972,13954700,Americas,55.448,5937.827283 Peru,1977,15990099,Americas,58.447,6281.290855 Peru,1982,18125129,Americas,61.406,6434.501797 Peru,1987,20195924,Americas,64.134,6360.943444 Peru,1992,22430449,Americas,66.458,4446.380924 Peru,1997,24748122,Americas,68.386,5838.347657 Peru,2002,26769436,Americas,69.906,5909.020073 Peru,2007,28674757,Americas,71.421,7408.905561 Philippines,1952,22438691,Asia,47.752,1272.880995 Philippines,1957,26072194,Asia,51.334,1547.944844 Philippines,1962,30325264,Asia,54.757,1649.552153 Philippines,1967,35356600,Asia,56.393,1814.12743 Philippines,1972,40850141,Asia,58.065,1989.37407 Philippines,1977,46850962,Asia,60.06,2373.204287 Philippines,1982,53456774,Asia,62.082,2603.273765 Philippines,1987,60017788,Asia,64.151,2189.634995 Philippines,1992,67185766,Asia,66.458,2279.324017 Philippines,1997,75012988,Asia,68.564,2536.534925 Philippines,2002,82995088,Asia,70.303,2650.921068 Philippines,2007,91077287,Asia,71.688,3190.481016 Poland,1952,25730551,Europe,61.31,4029.329699 Poland,1957,28235346,Europe,65.77,4734.253019 Poland,1962,30329617,Europe,67.64,5338.752143 Poland,1967,31785378,Europe,69.61,6557.152776 Poland,1972,33039545,Europe,70.85,8006.506993 Poland,1977,34621254,Europe,70.67,9508.141454 Poland,1982,36227381,Europe,71.32,8451.531004 Poland,1987,37740710,Europe,70.98,9082.351172 Poland,1992,38370697,Europe,70.99,7738.881247 Poland,1997,38654957,Europe,72.75,10159.58368 Poland,2002,38625976,Europe,74.67,12002.23908 Poland,2007,38518241,Europe,75.563,15389.92468 Portugal,1952,8526050,Europe,59.82,3068.319867 Portugal,1957,8817650,Europe,61.51,3774.571743 Portugal,1962,9019800,Europe,64.39,4727.954889 Portugal,1967,9103000,Europe,66.6,6361.517993 Portugal,1972,8970450,Europe,69.26,9022.247417 Portugal,1977,9662600,Europe,70.41,10172.48572 Portugal,1982,9859650,Europe,72.77,11753.84291 Portugal,1987,9915289,Europe,74.06,13039.30876 Portugal,1992,9927680,Europe,74.86,16207.26663 Portugal,1997,10156415,Europe,75.97,17641.03156 Portugal,2002,10433867,Europe,77.29,19970.90787 Portugal,2007,10642836,Europe,78.098,20509.64777 Puerto Rico,1952,2227000,Americas,64.28,3081.959785 Puerto Rico,1957,2260000,Americas,68.54,3907.156189 Puerto Rico,1962,2448046,Americas,69.62,5108.34463 Puerto Rico,1967,2648961,Americas,71.1,6929.277714 Puerto Rico,1972,2847132,Americas,72.16,9123.041742 Puerto Rico,1977,3080828,Americas,73.44,9770.524921 Puerto Rico,1982,3279001,Americas,73.75,10330.98915 Puerto Rico,1987,3444468,Americas,74.63,12281.34191 Puerto Rico,1992,3585176,Americas,73.911,14641.58711 Puerto Rico,1997,3759430,Americas,74.917,16999.4333 Puerto Rico,2002,3859606,Americas,77.778,18855.60618 Puerto Rico,2007,3942491,Americas,78.746,19328.70901 Reunion,1952,257700,Africa,52.724,2718.885295 Reunion,1957,308700,Africa,55.09,2769.451844 Reunion,1962,358900,Africa,57.666,3173.72334 Reunion,1967,414024,Africa,60.542,4021.175739 Reunion,1972,461633,Africa,64.274,5047.658563 Reunion,1977,492095,Africa,67.064,4319.804067 Reunion,1982,517810,Africa,69.885,5267.219353 Reunion,1987,562035,Africa,71.913,5303.377488 Reunion,1992,622191,Africa,73.615,6101.255823 Reunion,1997,684810,Africa,74.772,6071.941411 Reunion,2002,743981,Africa,75.744,6316.1652 Reunion,2007,798094,Africa,76.442,7670.122558 Romania,1952,16630000,Europe,61.05,3144.613186 Romania,1957,17829327,Europe,64.1,3943.370225 Romania,1962,18680721,Europe,66.8,4734.997586 Romania,1967,19284814,Europe,66.8,6470.866545 Romania,1972,20662648,Europe,69.21,8011.414402 Romania,1977,21658597,Europe,69.46,9356.39724 Romania,1982,22356726,Europe,69.66,9605.314053 Romania,1987,22686371,Europe,69.53,9696.273295 Romania,1992,22797027,Europe,69.36,6598.409903 Romania,1997,22562458,Europe,69.72,7346.547557 Romania,2002,22404337,Europe,71.322,7885.360081 Romania,2007,22276056,Europe,72.476,10808.47561 Rwanda,1952,2534927,Africa,40,493.3238752 Rwanda,1957,2822082,Africa,41.5,540.2893983 Rwanda,1962,3051242,Africa,43,597.4730727 Rwanda,1967,3451079,Africa,44.1,510.9637142 Rwanda,1972,3992121,Africa,44.6,590.5806638 Rwanda,1977,4657072,Africa,45,670.0806011 Rwanda,1982,5507565,Africa,46.218,881.5706467 Rwanda,1987,6349365,Africa,44.02,847.991217 Rwanda,1992,7290203,Africa,23.599,737.0685949 Rwanda,1997,7212583,Africa,36.087,589.9445051 Rwanda,2002,7852401,Africa,43.413,785.6537648 Rwanda,2007,8860588,Africa,46.242,863.0884639 Sao Tome and Principe,1952,60011,Africa,46.471,879.5835855 Sao Tome and Principe,1957,61325,Africa,48.945,860.7369026 Sao Tome and Principe,1962,65345,Africa,51.893,1071.551119 Sao Tome and Principe,1967,70787,Africa,54.425,1384.840593 Sao Tome and Principe,1972,76595,Africa,56.48,1532.985254 Sao Tome and Principe,1977,86796,Africa,58.55,1737.561657 Sao Tome and Principe,1982,98593,Africa,60.351,1890.218117 Sao Tome and Principe,1987,110812,Africa,61.728,1516.525457 Sao Tome and Principe,1992,125911,Africa,62.742,1428.777814 Sao Tome and Principe,1997,145608,Africa,63.306,1339.076036 Sao Tome and Principe,2002,170372,Africa,64.337,1353.09239 Sao Tome and Principe,2007,199579,Africa,65.528,1598.435089 Saudi Arabia,1952,4005677,Asia,39.875,6459.554823 Saudi Arabia,1957,4419650,Asia,42.868,8157.591248 Saudi Arabia,1962,4943029,Asia,45.914,11626.41975 Saudi Arabia,1967,5618198,Asia,49.901,16903.04886 Saudi Arabia,1972,6472756,Asia,53.886,24837.42865 Saudi Arabia,1977,8128505,Asia,58.69,34167.7626 Saudi Arabia,1982,11254672,Asia,63.012,33693.17525 Saudi Arabia,1987,14619745,Asia,66.295,21198.26136 Saudi Arabia,1992,16945857,Asia,68.768,24841.61777 Saudi Arabia,1997,21229759,Asia,70.533,20586.69019 Saudi Arabia,2002,24501530,Asia,71.626,19014.54118 Saudi Arabia,2007,27601038,Asia,72.777,21654.83194 Senegal,1952,2755589,Africa,37.278,1450.356983 Senegal,1957,3054547,Africa,39.329,1567.653006 Senegal,1962,3430243,Africa,41.454,1654.988723 Senegal,1967,3965841,Africa,43.563,1612.404632 Senegal,1972,4588696,Africa,45.815,1597.712056 Senegal,1977,5260855,Africa,48.879,1561.769116 Senegal,1982,6147783,Africa,52.379,1518.479984 Senegal,1987,7171347,Africa,55.769,1441.72072 Senegal,1992,8307920,Africa,58.196,1367.899369 Senegal,1997,9535314,Africa,60.187,1392.368347 Senegal,2002,10870037,Africa,61.6,1519.635262 Senegal,2007,12267493,Africa,63.062,1712.472136 Serbia,1952,6860147,Europe,57.996,3581.459448 Serbia,1957,7271135,Europe,61.685,4981.090891 Serbia,1962,7616060,Europe,64.531,6289.629157 Serbia,1967,7971222,Europe,66.914,7991.707066 Serbia,1972,8313288,Europe,68.7,10522.06749 Serbia,1977,8686367,Europe,70.3,12980.66956 Serbia,1982,9032824,Europe,70.162,15181.0927 Serbia,1987,9230783,Europe,71.218,15870.87851 Serbia,1992,9826397,Europe,71.659,9325.068238 Serbia,1997,10336594,Europe,72.232,7914.320304 Serbia,2002,10111559,Europe,73.213,7236.075251 Serbia,2007,10150265,Europe,74.002,9786.534714 Sierra Leone,1952,2143249,Africa,30.331,879.7877358 Sierra Leone,1957,2295678,Africa,31.57,1004.484437 Sierra Leone,1962,2467895,Africa,32.767,1116.639877 Sierra Leone,1967,2662190,Africa,34.113,1206.043465 Sierra Leone,1972,2879013,Africa,35.4,1353.759762 Sierra Leone,1977,3140897,Africa,36.788,1348.285159 Sierra Leone,1982,3464522,Africa,38.445,1465.010784 Sierra Leone,1987,3868905,Africa,40.006,1294.447788 Sierra Leone,1992,4260884,Africa,38.333,1068.696278 Sierra Leone,1997,4578212,Africa,39.897,574.6481576 Sierra Leone,2002,5359092,Africa,41.012,699.489713 Sierra Leone,2007,6144562,Africa,42.568,862.5407561 Singapore,1952,1127000,Asia,60.396,2315.138227 Singapore,1957,1445929,Asia,63.179,2843.104409 Singapore,1962,1750200,Asia,65.798,3674.735572 Singapore,1967,1977600,Asia,67.946,4977.41854 Singapore,1972,2152400,Asia,69.521,8597.756202 Singapore,1977,2325300,Asia,70.795,11210.08948 Singapore,1982,2651869,Asia,71.76,15169.16112 Singapore,1987,2794552,Asia,73.56,18861.53081 Singapore,1992,3235865,Asia,75.788,24769.8912 Singapore,1997,3802309,Asia,77.158,33519.4766 Singapore,2002,4197776,Asia,78.77,36023.1054 Singapore,2007,4553009,Asia,79.972,47143.17964 Slovak Republic,1952,3558137,Europe,64.36,5074.659104 Slovak Republic,1957,3844277,Europe,67.45,6093.26298 Slovak Republic,1962,4237384,Europe,70.33,7481.107598 Slovak Republic,1967,4442238,Europe,70.98,8412.902397 Slovak Republic,1972,4593433,Europe,70.35,9674.167626 Slovak Republic,1977,4827803,Europe,70.45,10922.66404 Slovak Republic,1982,5048043,Europe,70.8,11348.54585 Slovak Republic,1987,5199318,Europe,71.08,12037.26758 Slovak Republic,1992,5302888,Europe,71.38,9498.467723 Slovak Republic,1997,5383010,Europe,72.71,12126.23065 Slovak Republic,2002,5410052,Europe,73.8,13638.77837 Slovak Republic,2007,5447502,Europe,74.663,18678.31435 Slovenia,1952,1489518,Europe,65.57,4215.041741 Slovenia,1957,1533070,Europe,67.85,5862.276629 Slovenia,1962,1582962,Europe,69.15,7402.303395 Slovenia,1967,1646912,Europe,69.18,9405.489397 Slovenia,1972,1694510,Europe,69.82,12383.4862 Slovenia,1977,1746919,Europe,70.97,15277.03017 Slovenia,1982,1861252,Europe,71.063,17866.72175 Slovenia,1987,1945870,Europe,72.25,18678.53492 Slovenia,1992,1999210,Europe,73.64,14214.71681 Slovenia,1997,2011612,Europe,75.13,17161.10735 Slovenia,2002,2011497,Europe,76.66,20660.01936 Slovenia,2007,2009245,Europe,77.926,25768.25759 Somalia,1952,2526994,Africa,32.978,1135.749842 Somalia,1957,2780415,Africa,34.977,1258.147413 Somalia,1962,3080153,Africa,36.981,1369.488336 Somalia,1967,3428839,Africa,38.977,1284.73318 Somalia,1972,3840161,Africa,40.973,1254.576127 Somalia,1977,4353666,Africa,41.974,1450.992513 Somalia,1982,5828892,Africa,42.955,1176.807031 Somalia,1987,6921858,Africa,44.501,1093.244963 Somalia,1992,6099799,Africa,39.658,926.9602964 Somalia,1997,6633514,Africa,43.795,930.5964284 Somalia,2002,7753310,Africa,45.936,882.0818218 Somalia,2007,9118773,Africa,48.159,926.1410683 South Africa,1952,14264935,Africa,45.009,4725.295531 South Africa,1957,16151549,Africa,47.985,5487.104219 South Africa,1962,18356657,Africa,49.951,5768.729717 South Africa,1967,20997321,Africa,51.927,7114.477971 South Africa,1972,23935810,Africa,53.696,7765.962636 South Africa,1977,27129932,Africa,55.527,8028.651439 South Africa,1982,31140029,Africa,58.161,8568.266228 South Africa,1987,35933379,Africa,60.834,7825.823398 South Africa,1992,39964159,Africa,61.888,7225.069258 South Africa,1997,42835005,Africa,60.236,7479.188244 South Africa,2002,44433622,Africa,53.365,7710.946444 South Africa,2007,43997828,Africa,49.339,9269.657808 Spain,1952,28549870,Europe,64.94,3834.034742 Spain,1957,29841614,Europe,66.66,4564.80241 Spain,1962,31158061,Europe,69.69,5693.843879 Spain,1967,32850275,Europe,71.44,7993.512294 Spain,1972,34513161,Europe,73.06,10638.75131 Spain,1977,36439000,Europe,74.39,13236.92117 Spain,1982,37983310,Europe,76.3,13926.16997 Spain,1987,38880702,Europe,76.9,15764.98313 Spain,1992,39549438,Europe,77.57,18603.06452 Spain,1997,39855442,Europe,78.77,20445.29896 Spain,2002,40152517,Europe,79.78,24835.47166 Spain,2007,40448191,Europe,80.941,28821.0637 Sri Lanka,1952,7982342,Asia,57.593,1083.53203 Sri Lanka,1957,9128546,Asia,61.456,1072.546602 Sri Lanka,1962,10421936,Asia,62.192,1074.47196 Sri Lanka,1967,11737396,Asia,64.266,1135.514326 Sri Lanka,1972,13016733,Asia,65.042,1213.39553 Sri Lanka,1977,14116836,Asia,65.949,1348.775651 Sri Lanka,1982,15410151,Asia,68.757,1648.079789 Sri Lanka,1987,16495304,Asia,69.011,1876.766827 Sri Lanka,1992,17587060,Asia,70.379,2153.739222 Sri Lanka,1997,18698655,Asia,70.457,2664.477257 Sri Lanka,2002,19576783,Asia,70.815,3015.378833 Sri Lanka,2007,20378239,Asia,72.396,3970.095407 Sudan,1952,8504667,Africa,38.635,1615.991129 Sudan,1957,9753392,Africa,39.624,1770.337074 Sudan,1962,11183227,Africa,40.87,1959.593767 Sudan,1967,12716129,Africa,42.858,1687.997641 Sudan,1972,14597019,Africa,45.083,1659.652775 Sudan,1977,17104986,Africa,47.8,2202.988423 Sudan,1982,20367053,Africa,50.338,1895.544073 Sudan,1987,24725960,Africa,51.744,1507.819159 Sudan,1992,28227588,Africa,53.556,1492.197043 Sudan,1997,32160729,Africa,55.373,1632.210764 Sudan,2002,37090298,Africa,56.369,1993.398314 Sudan,2007,42292929,Africa,58.556,2602.394995 Swaziland,1952,290243,Africa,41.407,1148.376626 Swaziland,1957,326741,Africa,43.424,1244.708364 Swaziland,1962,370006,Africa,44.992,1856.182125 Swaziland,1967,420690,Africa,46.633,2613.101665 Swaziland,1972,480105,Africa,49.552,3364.836625 Swaziland,1977,551425,Africa,52.537,3781.410618 Swaziland,1982,649901,Africa,55.561,3895.384018 Swaziland,1987,779348,Africa,57.678,3984.839812 Swaziland,1992,962344,Africa,58.474,3553.0224 Swaziland,1997,1054486,Africa,54.289,3876.76846 Swaziland,2002,1130269,Africa,43.869,4128.116943 Swaziland,2007,1133066,Africa,39.613,4513.480643 Sweden,1952,7124673,Europe,71.86,8527.844662 Sweden,1957,7363802,Europe,72.49,9911.878226 Sweden,1962,7561588,Europe,73.37,12329.44192 Sweden,1967,7867931,Europe,74.16,15258.29697 Sweden,1972,8122293,Europe,74.72,17832.02464 Sweden,1977,8251648,Europe,75.44,18855.72521 Sweden,1982,8325260,Europe,76.42,20667.38125 Sweden,1987,8421403,Europe,77.19,23586.92927 Sweden,1992,8718867,Europe,78.16,23880.01683 Sweden,1997,8897619,Europe,79.39,25266.59499 Sweden,2002,8954175,Europe,80.04,29341.63093 Sweden,2007,9031088,Europe,80.884,33859.74835 Switzerland,1952,4815000,Europe,69.62,14734.23275 Switzerland,1957,5126000,Europe,70.56,17909.48973 Switzerland,1962,5666000,Europe,71.32,20431.0927 Switzerland,1967,6063000,Europe,72.77,22966.14432 Switzerland,1972,6401400,Europe,73.78,27195.11304 Switzerland,1977,6316424,Europe,75.39,26982.29052 Switzerland,1982,6468126,Europe,76.21,28397.71512 Switzerland,1987,6649942,Europe,77.41,30281.70459 Switzerland,1992,6995447,Europe,78.03,31871.5303 Switzerland,1997,7193761,Europe,79.37,32135.32301 Switzerland,2002,7361757,Europe,80.62,34480.95771 Switzerland,2007,7554661,Europe,81.701,37506.41907 Syria,1952,3661549,Asia,45.883,1643.485354 Syria,1957,4149908,Asia,48.284,2117.234893 Syria,1962,4834621,Asia,50.305,2193.037133 Syria,1967,5680812,Asia,53.655,1881.923632 Syria,1972,6701172,Asia,57.296,2571.423014 Syria,1977,7932503,Asia,61.195,3195.484582 Syria,1982,9410494,Asia,64.59,3761.837715 Syria,1987,11242847,Asia,66.974,3116.774285 Syria,1992,13219062,Asia,69.249,3340.542768 Syria,1997,15081016,Asia,71.527,4014.238972 Syria,2002,17155814,Asia,73.053,4090.925331 Syria,2007,19314747,Asia,74.143,4184.548089 Taiwan,1952,8550362,Asia,58.5,1206.947913 Taiwan,1957,10164215,Asia,62.4,1507.86129 Taiwan,1962,11918938,Asia,65.2,1822.879028 Taiwan,1967,13648692,Asia,67.5,2643.858681 Taiwan,1972,15226039,Asia,69.39,4062.523897 Taiwan,1977,16785196,Asia,70.59,5596.519826 Taiwan,1982,18501390,Asia,72.16,7426.354774 Taiwan,1987,19757799,Asia,73.4,11054.56175 Taiwan,1992,20686918,Asia,74.26,15215.6579 Taiwan,1997,21628605,Asia,75.25,20206.82098 Taiwan,2002,22454239,Asia,76.99,23235.42329 Taiwan,2007,23174294,Asia,78.4,28718.27684 Tanzania,1952,8322925,Africa,41.215,716.6500721 Tanzania,1957,9452826,Africa,42.974,698.5356073 Tanzania,1962,10863958,Africa,44.246,722.0038073 Tanzania,1967,12607312,Africa,45.757,848.2186575 Tanzania,1972,14706593,Africa,47.62,915.9850592 Tanzania,1977,17129565,Africa,49.919,962.4922932 Tanzania,1982,19844382,Africa,50.608,874.2426069 Tanzania,1987,23040630,Africa,51.535,831.8220794 Tanzania,1992,26605473,Africa,50.44,825.682454 Tanzania,1997,30686889,Africa,48.466,789.1862231 Tanzania,2002,34593779,Africa,49.651,899.0742111 Tanzania,2007,38139640,Africa,52.517,1107.482182 Thailand,1952,21289402,Asia,50.848,757.7974177 Thailand,1957,25041917,Asia,53.63,793.5774148 Thailand,1962,29263397,Asia,56.061,1002.199172 Thailand,1967,34024249,Asia,58.285,1295.46066 Thailand,1972,39276153,Asia,60.405,1524.358936 Thailand,1977,44148285,Asia,62.494,1961.224635 Thailand,1982,48827160,Asia,64.597,2393.219781 Thailand,1987,52910342,Asia,66.084,2982.653773 Thailand,1992,56667095,Asia,67.298,4616.896545 Thailand,1997,60216677,Asia,67.521,5852.625497 Thailand,2002,62806748,Asia,68.564,5913.187529 Thailand,2007,65068149,Asia,70.616,7458.396327 Togo,1952,1219113,Africa,38.596,859.8086567 Togo,1957,1357445,Africa,41.208,925.9083202 Togo,1962,1528098,Africa,43.922,1067.53481 Togo,1967,1735550,Africa,46.769,1477.59676 Togo,1972,2056351,Africa,49.759,1649.660188 Togo,1977,2308582,Africa,52.887,1532.776998 Togo,1982,2644765,Africa,55.471,1344.577953 Togo,1987,3154264,Africa,56.941,1202.201361 Togo,1992,3747553,Africa,58.061,1034.298904 Togo,1997,4320890,Africa,58.39,982.2869243 Togo,2002,4977378,Africa,57.561,886.2205765 Togo,2007,5701579,Africa,58.42,882.9699438 Trinidad and Tobago,1952,662850,Americas,59.1,3023.271928 Trinidad and Tobago,1957,764900,Americas,61.8,4100.3934 Trinidad and Tobago,1962,887498,Americas,64.9,4997.523971 Trinidad and Tobago,1967,960155,Americas,65.4,5621.368472 Trinidad and Tobago,1972,975199,Americas,65.9,6619.551419 Trinidad and Tobago,1977,1039009,Americas,68.3,7899.554209 Trinidad and Tobago,1982,1116479,Americas,68.832,9119.528607 Trinidad and Tobago,1987,1191336,Americas,69.582,7388.597823 Trinidad and Tobago,1992,1183669,Americas,69.862,7370.990932 Trinidad and Tobago,1997,1138101,Americas,69.465,8792.573126 Trinidad and Tobago,2002,1101832,Americas,68.976,11460.60023 Trinidad and Tobago,2007,1056608,Americas,69.819,18008.50924 Tunisia,1952,3647735,Africa,44.6,1468.475631 Tunisia,1957,3950849,Africa,47.1,1395.232468 Tunisia,1962,4286552,Africa,49.579,1660.30321 Tunisia,1967,4786986,Africa,52.053,1932.360167 Tunisia,1972,5303507,Africa,55.602,2753.285994 Tunisia,1977,6005061,Africa,59.837,3120.876811 Tunisia,1982,6734098,Africa,64.048,3560.233174 Tunisia,1987,7724976,Africa,66.894,3810.419296 Tunisia,1992,8523077,Africa,70.001,4332.720164 Tunisia,1997,9231669,Africa,71.973,4876.798614 Tunisia,2002,9770575,Africa,73.042,5722.895655 Tunisia,2007,10276158,Africa,73.923,7092.923025 Turkey,1952,22235677,Europe,43.585,1969.10098 Turkey,1957,25670939,Europe,48.079,2218.754257 Turkey,1962,29788695,Europe,52.098,2322.869908 Turkey,1967,33411317,Europe,54.336,2826.356387 Turkey,1972,37492953,Europe,57.005,3450.69638 Turkey,1977,42404033,Europe,59.507,4269.122326 Turkey,1982,47328791,Europe,61.036,4241.356344 Turkey,1987,52881328,Europe,63.108,5089.043686 Turkey,1992,58179144,Europe,66.146,5678.348271 Turkey,1997,63047647,Europe,68.835,6601.429915 Turkey,2002,67308928,Europe,70.845,6508.085718 Turkey,2007,71158647,Europe,71.777,8458.276384 Uganda,1952,5824797,Africa,39.978,734.753484 Uganda,1957,6675501,Africa,42.571,774.3710692 Uganda,1962,7688797,Africa,45.344,767.2717398 Uganda,1967,8900294,Africa,48.051,908.9185217 Uganda,1972,10190285,Africa,51.016,950.735869 Uganda,1977,11457758,Africa,50.35,843.7331372 Uganda,1982,12939400,Africa,49.849,682.2662268 Uganda,1987,15283050,Africa,51.509,617.7244065 Uganda,1992,18252190,Africa,48.825,644.1707969 Uganda,1997,21210254,Africa,44.578,816.559081 Uganda,2002,24739869,Africa,47.813,927.7210018 Uganda,2007,29170398,Africa,51.542,1056.380121 United Kingdom,1952,50430000,Europe,69.18,9979.508487 United Kingdom,1957,51430000,Europe,70.42,11283.17795 United Kingdom,1962,53292000,Europe,70.76,12477.17707 United Kingdom,1967,54959000,Europe,71.36,14142.85089 United Kingdom,1972,56079000,Europe,72.01,15895.11641 United Kingdom,1977,56179000,Europe,72.76,17428.74846 United Kingdom,1982,56339704,Europe,74.04,18232.42452 United Kingdom,1987,56981620,Europe,75.007,21664.78767 United Kingdom,1992,57866349,Europe,76.42,22705.09254 United Kingdom,1997,58808266,Europe,77.218,26074.53136 United Kingdom,2002,59912431,Europe,78.471,29478.99919 United Kingdom,2007,60776238,Europe,79.425,33203.26128 United States,1952,157553000,Americas,68.44,13990.48208 United States,1957,171984000,Americas,69.49,14847.12712 United States,1962,186538000,Americas,70.21,16173.14586 United States,1967,198712000,Americas,70.76,19530.36557 United States,1972,209896000,Americas,71.34,21806.03594 United States,1977,220239000,Americas,73.38,24072.63213 United States,1982,232187835,Americas,74.65,25009.55914 United States,1987,242803533,Americas,75.02,29884.35041 United States,1992,256894189,Americas,76.09,32003.93224 United States,1997,272911760,Americas,76.81,35767.43303 United States,2002,287675526,Americas,77.31,39097.09955 United States,2007,301139947,Americas,78.242,42951.65309 Uruguay,1952,2252965,Americas,66.071,5716.766744 Uruguay,1957,2424959,Americas,67.044,6150.772969 Uruguay,1962,2598466,Americas,68.253,5603.357717 Uruguay,1967,2748579,Americas,68.468,5444.61962 Uruguay,1972,2829526,Americas,68.673,5703.408898 Uruguay,1977,2873520,Americas,69.481,6504.339663 Uruguay,1982,2953997,Americas,70.805,6920.223051 Uruguay,1987,3045153,Americas,71.918,7452.398969 Uruguay,1992,3149262,Americas,72.752,8137.004775 Uruguay,1997,3262838,Americas,74.223,9230.240708 Uruguay,2002,3363085,Americas,75.307,7727.002004 Uruguay,2007,3447496,Americas,76.384,10611.46299 Venezuela,1952,5439568,Americas,55.088,7689.799761 Venezuela,1957,6702668,Americas,57.907,9802.466526 Venezuela,1962,8143375,Americas,60.77,8422.974165 Venezuela,1967,9709552,Americas,63.479,9541.474188 Venezuela,1972,11515649,Americas,65.712,10505.25966 Venezuela,1977,13503563,Americas,67.456,13143.95095 Venezuela,1982,15620766,Americas,68.557,11152.41011 Venezuela,1987,17910182,Americas,70.19,9883.584648 Venezuela,1992,20265563,Americas,71.15,10733.92631 Venezuela,1997,22374398,Americas,72.146,10165.49518 Venezuela,2002,24287670,Americas,72.766,8605.047831 Venezuela,2007,26084662,Americas,73.747,11415.80569 Vietnam,1952,26246839,Asia,40.412,605.0664917 Vietnam,1957,28998543,Asia,42.887,676.2854478 Vietnam,1962,33796140,Asia,45.363,772.0491602 Vietnam,1967,39463910,Asia,47.838,637.1232887 Vietnam,1972,44655014,Asia,50.254,699.5016441 Vietnam,1977,50533506,Asia,55.764,713.5371196 Vietnam,1982,56142181,Asia,58.816,707.2357863 Vietnam,1987,62826491,Asia,62.82,820.7994449 Vietnam,1992,69940728,Asia,67.662,989.0231487 Vietnam,1997,76048996,Asia,70.672,1385.896769 Vietnam,2002,80908147,Asia,73.017,1764.456677 Vietnam,2007,85262356,Asia,74.249,2441.576404 West Bank and Gaza,1952,1030585,Asia,43.16,1515.592329 West Bank and Gaza,1957,1070439,Asia,45.671,1827.067742 West Bank and Gaza,1962,1133134,Asia,48.127,2198.956312 West Bank and Gaza,1967,1142636,Asia,51.631,2649.715007 West Bank and Gaza,1972,1089572,Asia,56.532,3133.409277 West Bank and Gaza,1977,1261091,Asia,60.765,3682.831494 West Bank and Gaza,1982,1425876,Asia,64.406,4336.032082 West Bank and Gaza,1987,1691210,Asia,67.046,5107.197384 West Bank and Gaza,1992,2104779,Asia,69.718,6017.654756 West Bank and Gaza,1997,2826046,Asia,71.096,7110.667619 West Bank and Gaza,2002,3389578,Asia,72.37,4515.487575 West Bank and Gaza,2007,4018332,Asia,73.422,3025.349798 Yemen Rep.,1952,4963829,Asia,32.548,781.7175761 Yemen Rep.,1957,5498090,Asia,33.97,804.8304547 Yemen Rep.,1962,6120081,Asia,35.18,825.6232006 Yemen Rep.,1967,6740785,Asia,36.984,862.4421463 Yemen Rep.,1972,7407075,Asia,39.848,1265.047031 Yemen Rep.,1977,8403990,Asia,44.175,1829.765177 Yemen Rep.,1982,9657618,Asia,49.113,1977.55701 Yemen Rep.,1987,11219340,Asia,52.922,1971.741538 Yemen Rep.,1992,13367997,Asia,55.599,1879.496673 Yemen Rep.,1997,15826497,Asia,58.02,2117.484526 Yemen Rep.,2002,18701257,Asia,60.308,2234.820827 Yemen Rep.,2007,22211743,Asia,62.698,2280.769906 Zambia,1952,2672000,Africa,42.038,1147.388831 Zambia,1957,3016000,Africa,44.077,1311.956766 Zambia,1962,3421000,Africa,46.023,1452.725766 Zambia,1967,3900000,Africa,47.768,1777.077318 Zambia,1972,4506497,Africa,50.107,1773.498265 Zambia,1977,5216550,Africa,51.386,1588.688299 Zambia,1982,6100407,Africa,51.821,1408.678565 Zambia,1987,7272406,Africa,50.821,1213.315116 Zambia,1992,8381163,Africa,46.1,1210.884633 Zambia,1997,9417789,Africa,40.238,1071.353818 Zambia,2002,10595811,Africa,39.193,1071.613938 Zambia,2007,11746035,Africa,42.384,1271.211593 Zimbabwe,1952,3080907,Africa,48.451,406.8841148 Zimbabwe,1957,3646340,Africa,50.469,518.7642681 Zimbabwe,1962,4277736,Africa,52.358,527.2721818 Zimbabwe,1967,4995432,Africa,53.995,569.7950712 Zimbabwe,1972,5861135,Africa,55.635,799.3621758 Zimbabwe,1977,6642107,Africa,57.674,685.5876821 Zimbabwe,1982,7636524,Africa,60.363,788.8550411 Zimbabwe,1987,9216418,Africa,62.351,706.1573059 Zimbabwe,1992,10704340,Africa,60.377,693.4207856 Zimbabwe,1997,11404948,Africa,46.809,792.4499603 Zimbabwe,2002,11926563,Africa,39.989,672.0386227 Zimbabwe,2007,12311143,Africa,43.487,469.7092981 ================================================ FILE: index.html ================================================ R Docker tutorial by ropenscilabs

R Docker tutorial

View the Project on GitHub jsta/r-docker-tutorial

A Docker tutorial for reproducible research.

This is an introduction to Docker designed for participants with knowledge about R and RStudio. The introduction is intended to be helping people who need Docker for a project. We first explain what Docker is and why it is useful. Then we go into the the details on how to use it for a reproducible transportable project.

Lessons:

  1. Lesson 01 What and Why
  2. Lesson 02 Launching Docker
  3. Lesson 03 Installing R packages
  4. Lesson 04 Pushing and Pulling with Docker Hub
  5. Lesson 05 Dockerfiles
  6. Lesson 06 Sharing your analysis

Before You Start

Try to install Docker before you come to the workshop, by following the instructions for mac, linux, or windows. If you get stuck, don't worry! We'll help you get set up at the beginning of the workshop.

This tutorial is work in progress. If you have any suggestions how we could make it better please open a new issue.

This project is maintained by jsta.

You can find the contributors here.

Hosted on GitHub Pages — Theme by orderedlist

================================================ FILE: instructors.md ================================================ ## Instructor's Guide This file contains the collected tips and tricks for teaching this lesson. After you teach it, please add your comments by sending us a pull request, or letting us know in an [issue](https://github.com/jsta/r-docker-tutorial/issues). ### General - Bring thumb drives with the docker images. If a bunch of people want to download the same 3GB image you might run into problems. - Optional parts are marked with the word "Optional:" and *italic text*. ### Section Specific #### 01: What and Why - Lead a 5 min discussion to help students imagine where they'll use Docker. Places to guide the conversation towards if they're stuck: department clusters, cloud services, their new computer etc. ================================================ FILE: javascripts/scale.fix.js ================================================ var metas = document.getElementsByTagName('meta'); var i; if (navigator.userAgent.match(/iPhone/i)) { for (i=0; i