Tutorials

DATA 23700 Tutorials

This is where we'll post links to tutorials, examples, and software tools separated by topic.

Welcome to Google Colab
Using Google Colab with GitHub
UChicago CS guide to setting up VS Code. If you want to use VS Code instead of Google Colab, the environment setup is your responsibility.
Although we do not use R much this quarter, it supports an excellent data science toolkit. You can check out RStudio as an alternative IDE for R if you don't want to use VS Code or Colab.

Basic pandas tutor demonstrating common dataframe operations
Intro to pandas in Google Colab
The primary visualization API we teach in this course is Altair. Check out their user guide, example gallery, API, and more on the same website!
Altair is actually a wrapper around a JavaScript library called Vega-Lite. If you're interested, check out the Vega-Lite example gallery to compare its syntax with that of Altair.
Vega and Vega-Lite are declarative grammars for interactive visualization that compile to D3 visualizations. Altair leverages this software stack by wrapping python syntax around Vega-Lite.
From the creators of popular visualization toolkits like D3, Vega, and Vega-Lite, the University of Washington Interactive Data Lab has graciously made their visualization curriculum public! The notebooks posted here give an excellent walkthrough of some topics we'll cover in this course.
The PyMC and arviz APIs for Bayesian statistics workflows in Python.
Matthew Kay's ggdist R package for visualizing distributions.
Scikit-learn Python module for ML.
Microsoft's open source Python module for ML interpretability, interpret.

Interactive scatterplot matrix
Hans Rosling's visualization storytelling.
Amanda Cox from the New York Times on uncertainty visualizations in the news (2:55 – 10:43).
Fred Hohman's presentations about his work on ML interpretability.