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  • Quick start guide
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  • Figures and backends
    • Introduction to figures
    • Output backends
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    • Interactive figures and asynchronous programming
    • Event handling
    • Writing a backend -- the pyplot interface
  • Axes and subplots
    • Introduction to Axes (or Subplots)
    • Arranging multiple Axes in a Figure
    • Placing Colorbars
    • Autoscaling axes
    • Axis scales
    • Axis Ticks
    • Legends
    • Subplot mosaic
    • Constrained layout guide
    • Tight layout guide (mildly discouraged)
  • Artists
    • Introduction to Artists
    • Automated color cycle
    • Optimizing Artists for performance
    • Paths
    • Path effects guide
    • Understanding the extent keyword argument of imshow
    • Transformations Tutorial
  • Customizing Matplotlib with style sheets and rcParams
  • Colors
    • Specifying colors
    • Standalone colorbars
    • Creating Colormaps
    • Colormap Normalization
    • Choosing Colormaps
  • Text
    • Text in Matplotlib
    • Text properties and layout
    • Annotations
    • Fonts in Matplotlib
    • Writing mathematical expressions
    • Text rendering with XeLaTeX/LuaLaTeX via the pgf backend
    • Text rendering with LaTeX
  • Animations using Matplotlib
    • Animations using Matplotlib
    • Faster rendering by using blitting
  • User Toolkits
    • The axisartist toolkit
    • The axes_grid1 toolkit
    • The mplot3d toolkit
  • User guide tutorials
  • Getting started
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  • Using Matplotlib
  • Colors

Colors#

Matplotlib has support for visualizing information with a wide array of colors and colormaps. These tutorials cover the basics of how these colormaps look, how you can create your own, and how you can customize colormaps for your use case.

For even more information see the examples page.

Specifying colors

Specifying colors

Standalone colorbars

Standalone colorbars

Creating Colormaps

Creating Colormaps

Colormap Normalization

Colormap Normalization

Choosing Colormaps

Choosing Colormaps

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