Description
Impact charts, as implemented in the impactchart (https://github.com/vengroff/impactchart) package, make it easy to take a data set and visualize the impact of one variable on another in ways that techniques like scatter plots and linear regression can't, especially when there are other variables involved.
In this talk, we will introduce impact charts, demonstrate how they find easter-egg impacts we embed in synthetic data, show how they can find hidden impacts in a real-world use case, show how you can create your first impact chart with just a few lines of code, and finally talk a bit about the interpretable machine learning techniques they are built upon.
Impact charts are primarily visual, so this talk will be too.