Lecture 11 – Visualization II
Presented by Suraj Rampure
Content by Suraj Rampure, Ani Adhikari, Deborah Nolan, Joseph Gonzalez
Extra reading on colormaps:
- matplotlib colormaps (BIDS)
- How the Rainbow Color Map Misleads
- When to use Sequential and Diverging Palettes
- Color Use Guidelines
A reminder – the right column of the table below contains Quick Checks. These are not required but suggested to help you check your understanding.
Ensuring that the axes in our visualizations aren't misleading.
Designing visualizations that are well-suited for making comparisons.
How to use color to create effective visualizations. How to choose color schemes that are clear and accessible.
How to choose markings that the human eye can easily interpret. Issues to avoid, such as jiggling baselines and overplotting.
Discussing the supplemental text that publication-ready plots need.
When to use smoothing. How kernel density estimates are created. Looking at various kernels. Understanding the impact of the bandwidth hyperparameter.
Discussing why we prefer linear relationships. Understanding how to "reverse-engineer" a linearized relationship to determine the true relationship. Identifying which transformations to use in order to linearize a relationship.