It is essential to choose the right color for the plot. If your plot looks good, it will be easy to study it.

Setting the Palette

There are two main ways to set colors in Seaborn:

1. Global level (set_palette): this changes the colors for all plots created afterwards. It is useful when you want a consistent style throughout your entire notebook;
2. Plot level (palette argument): this changes colors only for the specific plot.

# 1. Global setting (affects all future plots)
sns.set_palette('mako')

# 2. Local setting (affects only this plot)
sns.countplot(x=data, palette='mako')

Common Palettes

Instead of guessing colors, you can use these built-in Seaborn palette names:

• Categorical (qualitative): best for distinct categories (e.g., fruits, cities).
• deep (default);
• muted;
• bright;
• pastel;
• dark;
• colorblind.

• Sequential (perceptually uniform): best for showing numeric progression or intensity.
• rocket (warm);
• mako (cool, teal-blue);
• flare;
• crest;
• virdis;
• rocket_r (adding _r reverses any palette);
• magma.