Python Data Science with Jupyter on Docker

By | November 12, 2022

Inspired by article “How to set up and run Python Data Science Development Environment with Jupyter on Docker” [Archived]

Data Scientists coders must work with a variety of Data Science development tools, including the  Anaconda (or Miniconda) Python distribution platform, the Python programming language, the R programming languageMatplotlib libraryPandas Library, the Jupyter application, and many others.

The article describes how to use pre-made  Docker images to run Jupyter Labs. the Jupyter Docker Stacks simplifies how to create a ready-to-use Jupyter application with Data Science libraries in a few commands.

The article contains the commands to install and run the necessary software and contains an embedded ~9min video demonstration.

Table of Contents

Here is a screen capture of the web browser that I started with command:

docker run -p 8888:8888 --name notebook -v "${PWD}":/home/jovyan/work -e JUPYTER_ENABLE_LAB=yes  -it jupyter/scipy-notebook
Jupyter Lab launched within my browser in localhost:8888

There are more options with the jupyter/datascience-notebook:

docker run -p 8888:8888 --name notebook -v "${PWD}":/home/jovyan/work -e JUPYTER_ENABLE_LAB=yes  -it jupyter/datascience-notebook
The datascience-notebook version adds R and Julia.

Quoting from the article:

Jupyter Docker Stacks provide various images for developers based on their requirements such as:

Please see more detail about all image types on Selecting an Image page.

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