Visualizing distributions of data — seaborn 0.12.2 documentation:

• TIL KDE means “Kernel Density Estimation”
• common_norm=True by default applies the same normalization to the entire distribution. False scales each independently. This is critical in many cases, esp. with stat="probability"

Generally: I read the seaborn documentation, esp. the high level architecture things, and a lot of things I’ve been asking myself since forever (e.g. 230515-2257 seaborn setting titles etc. with matplotlib set) have become much clearer - and will be its own post. I love seaborn and it’s honestly worth learning to use well and systematically.