The Data Science and Engineering Society

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lab-dataviz

A repository of laboratories for learning data vizualization concepts and tools.

Table of contents

• Launching this repository of labs on a binderhub instance
  • JupyterLab
  • Jupyter
  • Rstudio
  • Shiny
  • Nteract
  • Stencila
• Launching this repository of labs on a Google Colaboratory session
• Launching this repository of labs locally using Docker
  • Via our Docker image
  • Via repo2docker
  • Accessing your Docker container
• Contributing
• License

Launching this repository of labs on a binderhub instance

The list below provides badges/hyperlinks for launching specific UIs in one of the binderhub instances. Choose one and click on the badges.

JupyterLab

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Jupyter

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Rstudio

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Shiny

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Nteract

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Stencila

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About:

Binderhub uses repo2docker for launching and serving the computational environments. Repo2docker supports the following interfaces:

• Jupyter
• JupyterLab
• Rstudio
• Nteract
• Shiny
• Stencila

List of known binderhub instances.

• gke.mybinder.org
• ovh.mybinder.org
• binder.gesis.org
• binder.pangeo.io

Launching this repository of labs on a Google Colaboratory session

Launching this repository of labs locally using Docker

We offer here two options for launching this lab locally: via our Docker image or via repo2docker. Before firing up your container, make sure your local user is in the docker group. Please refer to this Docker documentation for more details. It is strongly advised to not to run the container as root.

Via our Docker image

You can run a containerized instance of this lab from our own Docker image. Please refer to this link for installing Docker. Then, try:

docker run -it -p 8888:8888 thedatasociety/lab-dataviz \
           jupyter lab --ip 0.0.0.0 --NotebookApp.token='dstoken1234567' 

Alternatively, you can map you local home folder into the container:

docker run -it -p 8888:8888  \
           -v $(echo ~):/jupyter/data/local-home \
           thedatasociety/lab-dataviz \
           jupyter lab --ip 0.0.0.0 --NotebookApp.token='dstoken1234567'

The Dockerfile used to build the image can be found here.

Please read the section Accessing your Docker container for more details about running/accessing your container.

Via repo2docker

You can also launch this laboratory locally using Docker and repo2docker. Please refer to this link for installing Docker and this link for installing repo2docker. Use the commands below to build a Docker image and start a container from it.

repo2docker -p 8888:8888 \
            -v $(echo ~):$(echo ~)/local-home \
            https://github.com/thedatasociety/lab-dataviz \
            jupyter lab --ip 0.0.0.0 --NotebookApp.token='dstoken1234567'

Please read the section Accessing your Docker container for details about running/accessing your container.

Accessing your Docker container

Both options above will launch a container on port 8888. They will also create a Docker volume that maps the user's home into the container (in the container, look for the local-home folder).

Please also be aware that the --ip 0.0.0.0 directive will start a sever which will accept connections from any ip. For security purposes the --NotebookApp.token='dstoken1234567' directive forces the need of a token for accessing any interface. Use the dstoken1234567 to login or feel free to set a stronger token.

Each interface will be available at a specific path, as follows:

• Jupyter: http://0.0.0.0:8888/tree

• JupyterLab: http://0.0.0.0:8888/lab

• Nteract: http://0.0.0.0:8888/nteract

• Stencila:http://0.0.0.0:8888/stencila

• Rstudio: http://0.0.0.0:8888/rstudio

• Shiny: http://0.0.0.0:8888/shiny

See the repo2docker documentation for more details regarding the use of multiple interfaces.

Contributing

License