This repository contains all materials related to a lecture / seminar I teach on practical data visualization with python. What I mean by "practical" is that the materials herein do not focus on one particularly library or data visualization method; rather, my goal is to empower the consumer of this content with the tools, heuristics, and methods needed to handle a wide variety of data visualization problems.
This is a work in progress that will be evolving rapidly over the coming weeks and months, so please check back often for new additions and refinements, and if you'd like to contact me, don't hesitate to reach out via Twitter here.
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For the main lecture notebook:
- Here is the link to the easy-to-view notebook
- Here is the link to the GitHub-hosted version of the notebook
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For the data prep notebook:
- Here is the link to the easy-to-view notebook
- Here is the link to the GitHub-hosted version of the notebook
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For the homework notebook (participant version):
- Here is the link to the easy-to-view notebook
- Here is the link to the GitHub-hosted version of the notebook
- clone this repository locally
- create a virtual environment using
python3 -m venv env- additional information about this can be found here
- activate that virtual environment using
source env/bin/activate - install needed packages using
pip install -r requirements.txt- additional information about this can be found here
- run an instance of jupyter lab out of your virutal env using
env/bin/jupyter-lab - start by opening and running the
main_lecture_nb.ipynbfile, in which the majority of the content is located