These notebooks were created for the Visualisation and Tidy Data workshop, part of the Advanced Scientific Programming in Python Summer School.

To get started quickly if you already have all relevant packages installed:

git clone https://github.com/claresloggett/aspp-visualisation
cd aspp-visualisation
jupyter notebook --NotebookApp.iopub_data_rate_limit=10000000

We'll use the notebooks in the order:

• Matplotlib_and_tidy_data.ipynb
• Seaborn.ipynb
• Plotly.ipynb

You can create and activate a conda environment from the environment.yml file using

conda env create -f environment.yml
source activate aspp-visualisation-env

Depending on what version of Jupyter you're running, you may need to launch this notebook with a higher data rate limit so that visualisation libraries are not throttled in communicating with the browser, e.g.

jupyter notebook --NotebookApp.iopub_data_rate_limit=10000000

This issue is referenced here. README.md (END)