Quickest way to try out Jupyter Notebook: zero install, 3 CLI commands and 5 minutes to action

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This brief article shows you the quickest way to trying out Jupyter Notebooks.

Edit (22 November): since writing this article I learned about colab — a Google site that allows live Notebook authoring and exploration. Colab provides and even faster way of trying out Jupyter notebooks. Not on your own environment, not with a Docker container based environment that you can fully control. But an environment that is even more readily available. For an example — open this link to colab & my introductory Emp/Dept notebook on GitHub and start playing:

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The original approach:

It will not try to persuade you that you should try them out. You probably know that already. It will not show a complex Notebook in detail — plenty of those are available. It simply tells you:

  • open your browser at the Katacoda Ubuntu 20.4 Playground:
  • create directory
    mkdir work
  • change into directory
cd work
  • clone a GitHub Repository:
git clone https://github.com/lucasjellema/DOAG2020-DataWranglingWithJupyterNotebooks
  • run a Docker container with JupyterLab and Python 3 inside
docker run --rm -p 10000:8888 -v "$PWD":/home/jovyan/work  -e JUPYTER_ENABLE_LAB=yes jupyter/minimal-notebook
  • wait for several minutes while the fairly large container image is pulled, then started
  • when the container is running, the terminal window shows a token. Copy the token value to the clipboard
  • open a terminal for Host 1 at port 10000
    a new browser tab is started and the JupyterLab environment is available
  • open the HelloWorldNotebook and read and execute it. It will introduce you to the concept of the Notebook, to the Pandas en Matplotlib libraries and to some plain old Python.

In less than 10 minutes, you will have had you first hands on experience with JupyterLab, notebooks and Pandas. Note: the Katacoda environment is available for 60 minutes, then it will die on you, so do not get attached.

And now the same steps again, with screenshots:

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  • open your browser at the Katacoda Ubuntu 20.4 Playground:
  • create directory
    mkdir work
  • change into directory
    cd work
  • clone a GitHub Repository:
git clone https://github.com/lucasjellema/DOAG2020-DataWranglingWithJupyterNotebooks
  • run a Docker container with JupyterLab and Python 3 inside
docker run — rm -p 10000:8888 -v “$PWD”:/home/jovyan/work -e JUPYTER_ENABLE_LAB=yes jupyter/minimal-notebook
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  • wait for several minutes while the fairly large container image is pulled, then started
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  • when the container is running, the terminal window shows a token. Copy the token value to the clipboard
  • open a terminal for Host 1 at port 10000
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  • a new browser tab is started; paste the token
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  • and the JupyterLab environment is available
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  • open the HelloWorldNotebook
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  • and read and execute it. It will introduce you to the concept of the Notebook, to the Pandas en Matplotlib libraries and to some plain old Python.
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The Jupyter Notebook running on the Python3 kernel in the JupyterLab environment
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Small sample from the Jupyter Notebook

Resources

My GitHub Repo with sources and an introductory presentation on Jupyter Notebooks: https://github.com/lucasjellema/DOAG2020-DataWranglingWithJupyterNotebooks

A YouTube recording of my recent session for DOAG2020 on Jupyter Notebooks: https://youtu.be/pT62F542uhM

Originally published at https://technology.amis.nl on November 20, 2020.

Written by

Lucas Jellema is solution architect and CTO at AMIS, The Netherlands. He is Oracle ACE Director, Groundbreaker Ambassador, JavaOne Rockstar and programmer

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