D3 JavaScript visualisation in a Python Jupyter notebook

A Living with Machines repository for code underlying a blogpost about how to put a D3 JavaScript visualisation in a Python Jupyter notebook. The blogpost text is duplicated in blogpost.md.

Try the notebook live on myBinder.org:

Setting up

Clone the repository:

$ git clone https://github.com/Living-with-machines/D3_JS_viz_in_a_Python_Jupyter_notebook
...

Navigate into the directory:

$ cd D3_JS_viz_in_a_Python_Jupyter_notebook

Set up all the dependencies:

$ conda create --name d3forJupyter --file requirements.txt
...

Activate the environment:

$ conda activate d3forJupyter

Set up a kernel for Jupyter:

$ python -m ipykernel install --user --name=d3forJupyter
Installed kernelspec d3forJupyter in <path>

Start up Jupyter notebook:

$ jupyter notebook
[I 17:36:30.869 NotebookApp] Serving notebooks from local directory: <path>
...

Now you should be able to open up the notebook in this repository, D3_JS_viz_in_a_Python_Jupyter_notebook.ipynb and try it out for yourself.