Facet、Hue、Style

Sometimes one plot hides too much. Faceting splits your data into a grid of small charts, one per category, so each group gets its own view.

The lightest way to compare groups is color. hue maps a category to colors inside a single plot, no extra panels needed.

To break groups into separate panels, use a figure-level plot with col. Each category becomes its own side-by-side chart.

Pair col with row to build a full grid. One variable spreads across columns while another stacks down the rows.

Faceting needs figure-level functions like relplot, displot, and catplot. The plain plots such as scatterplot live inside a single panel.

Many categories make an endless row. col_wrap tells seaborn how many panels to allow before starting a new line.

Beyond color, style maps a category to marker shapes or dashed lines, helping when prints are black and white.

Swap the colors with palette. Choose a vivid set for distinct groups or a gradient for values that go from low to high.

One call restyles every chart at once. set_theme controls the background, gridlines, and default palette for the session.

You can layer them: color within each panel and split panels by another field. Just avoid encoding so much that the message gets lost.

Every extra hue, style, and facet adds load for the reader. Aim for the simplest view that still answers the question.

You want each category drawn in its own separate panel.

You now layer information with hue and style, split groups using facets, and theme it all cleanly, while keeping the chart easy to read. 🎨