User guide and tutorial

API overview

• Overview of seaborn plotting functions
  • Similar functions for similar tasks
  • Figure-level vs. axes-level functions
  • Combining multiple views on the data

• Data structures accepted by seaborn
  • Long-form vs. wide-form data
  • Options for visualizing long-form data
  • Options for visualizing wide-form data

Plotting functions

• Visualizing statistical relationships
  • Relating variables with scatter plots
  • Emphasizing continuity with line plots
  • Showing multiple relationships with facets

---

• Visualizing distributions of data
  • Plotting univariate histograms
  • Kernel density estimation
  • Empirical cumulative distributions
  • Visualizing bivariate distributions
  • Distribution visualization in other settings

---

• Plotting with categorical data
  • Categorical scatterplots
  • Distributions of observations within categories
  • Statistical estimation within categories
  • Plotting “wide-form” data
  • Showing multiple relationships with facets

---

• Visualizing regression models
  • Functions to draw linear regression models
  • Fitting different kinds of models
  • Conditioning on other variables
  • Controlling the size and shape of the plot
  • Plotting a regression in other contexts

Multi-plot grids

• Building structured multi-plot grids
  • Conditional small multiples
  • Using custom functions
  • Plotting pairwise data relationships

Plot aesthetics

• Controlling figure aesthetics
  • Seaborn figure styles
  • Removing axes spines
  • Temporarily setting figure style
  • Overriding elements of the seaborn styles
  • Scaling plot elements

---

• Choosing color palettes
  • General principles for using color in plots
  • Tools for choosing color palettes
  • Qualitative color palettes
  • Sequential color palettes
  • Diverging color palettes