Axis Grids
Learn to create and customize various axis grids using seaborn including FacetGrid, PairGrid, Pairplot, and JointGrid. This lesson guides you through visualizing medium-sized dataset subsets, comparing patterns, and exploring pairwise relationships with clean, tidy data in pandas DataFrames.
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When exploring medium-sized datasets, plotting the same chart across different subsets helps compare patterns. Grid plots (panel, lattice, or trellis plots) display subsets of data as a series of similar graphs with consistent scales and axes. This supports comparison across subsets and provides an overview of the data.
Matplotlib offers good support for making figures with multiple axes. Seaborn builds on top of this to directly link the structure of the plot to the design of our dataset.
Let’s learn with some examples using the datasets tips and iris. We’ve already used tips in the previous lessons. The iris data set is a famous dataset that includes three species of the iris, with 50 samples of each, as well as some properties about each flower. This dataset is a part of the seaborn library and is also available on Kaggle.
Note: To use the axis grids features, ...