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Last pushed: 4 months ago
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R with Jupyter Notebook
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Docker Image for Data Computing with Jupyter Notebook.

This Docker image is for R with Jupyter Notebook. This images inherits compdatasci/base.

Running Jupyter Notebook with Docker

To install Docker for your platform (Windows, MacOS, Linux, cloud platforms, etc.), follow the instructions at

Once you have Docker installed, you can start Jupyter Notebook using the following command in the directory that contains your notebooks:

    docker-jupyter mynotebook.ipynb

where the docker-jupyter script can be downloaded at

Running Jupyter Notebook with Docker Toolbox

If your version of Windows does not support Docker, you may need to install Docker Toolbox instead. After you have installed Docker Toolbox, start it and run the following command in a Docker Toolbox terminal in your work directory:

     docker run --rm -w /home/compdatasci/shared -v $(pwd):/home/compdatasci/shared -d -p \
    $(docker-machine ip $(docker-machine active)):8088:8088 compdatasci/r-jupyter \
    'jupyter-notebook --no-browser --ip= --port=8088'

If successful, you will see some screen out such as:

Copy/paste this URL into your browser when you connect for the first time,
to login with a token:

Copy and paste the URL into a web browser (such as Google Chrome). If port 8088 is in use, you can change it to a different port (say 8089) by replacing 8088 with 8089 in the docker run command.

When you have finished using Jupyter Notebook, use Control-C to stop this server and shut down all kernels (twice to skip confirmation).

Running as Linux environment

You can also run the image as a Linux environment for R. You can run the image using the following command:

docker run --rm -ti -w/home/compdatasci/shared -v $(pwd):/home/compdatasci/shared \

which would share your current working directory into the container as ~/shared. Note that you should only save files under the shared directory because all other files will be lost when the process ends.

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