https://github.com/living-with-machines/d3_js_viz_in_a_python_jupyter_notebook

Tutorial code showing how to put a D3 JavaScript visualisation in a Python Jupyter notebook.
https://github.com/living-with-machines/d3_js_viz_in_a_python_jupyter_notebook

blog d3 d3js javascript jupyter jupyter-notebook tutorial

Last synced: 1 day ago
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Tutorial code showing how to put a D3 JavaScript visualisation in a Python Jupyter notebook.

• Host: GitHub
• URL: https://github.com/living-with-machines/d3_js_viz_in_a_python_jupyter_notebook
• Owner: Living-with-machines
• License: mit
• Created: 2020-01-17T16:46:28.000Z (almost 5 years ago)
• Default Branch: main
• Last Pushed: 2023-01-18T17:46:19.000Z (almost 2 years ago)
• Last Synced: 2023-04-01T08:58:54.957Z (over 1 year ago)
• Topics: blog, d3, d3js, javascript, jupyter, jupyter-notebook, tutorial
• Language: Jupyter Notebook
• Homepage: https://livingwithmachines.ac.uk/d3-javascript-visualisation-in-a-python-jupyter-notebook/
• Size: 70.3 KB
• Stars: 12
• Watchers: 4
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# D3 JavaScript visualisation in a Python Jupyter notebook

A [Living with Machines](http://livingwithmachines.ac.uk/) repository for code underlying [a blogpost about how to put a D3 JavaScript visualisation in a Python Jupyter notebook](http://livingwithmachines.ac.uk/d3-javascript-visualisation-in-a-python-jupyter-notebook/). The blogpost text is duplicated in `blogpost.md`.

Try the notebook live on myBinder.org: [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/Living-with-machines/D3_JS_viz_in_a_Python_Jupyter_notebook/main?filepath=D3_JS_viz_in_a_Python_Jupyter_notebook.ipynb)

## Setting up

Clone the repository:

```sh

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

...

```

Navigate into the directory:

```sh

$ cd D3_JS_viz_in_a_Python_Jupyter_notebook

```

Set up all the dependencies:

```sh

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

...

```

Activate the environment:

```sh

$ conda activate d3forJupyter

```

Set up a kernel for Jupyter:

```sh

$ python -m ipykernel install --user --name=d3forJupyter

Installed kernelspec d3forJupyter in 

```

Start up Jupyter notebook:

```sh

$ jupyter notebook

[I 17:36:30.869 NotebookApp] Serving notebooks from local directory: 

...

```

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.