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  1. Matplotlib — Visualization with Python

    Matplotlib: Visualization with Python. Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard …

  2. Pyplot tutorial — Matplotlib 3.10.3 documentation

    matplotlib.pyplot is a collection of functions that make matplotlib work like MATLAB. Each pyplot function makes some change to a figure: e.g., creates a figure, creates a plotting area in a …

  3. Matplotlib cheatsheets — Visualization with Python

    Contribute#. Issues, suggestions, or pull-requests gratefully accepted at matplotlib/cheatsheets On this page Cheatsheets; Handouts; Contribute

  4. Using Matplotlib — Matplotlib 3.10.3 documentation

    Customizing Matplotlib with style sheets and rcParams. Runtime rc settings; Using style sheets; The matplotlibrc file

  5. Examples — Matplotlib 3.10.3 documentation

    Currently Matplotlib supports PyQt/PySide, PyGObject, Tkinter, and wxPython. When embedding Matplotlib in a GUI, you must use the Matplotlib API directly rather than the pylab/pyplot …

  6. Plot types — Matplotlib 3.10.3 documentation

    Overview of many common plotting commands provided by Matplotlib. See the gallery for more examples and the tutorials page for longer examples.

  7. 3D plotting — Matplotlib 3.10.3 documentation

    Plot 2D data on 3D plot; Demo of 3D bar charts; Clip the data to the axes view limits; Create 2D bar graphs in different planes; 3D box surface plot; Plot contour (level) curves in 3D; Plot …

  8. Tutorials — Matplotlib 3.10.3 documentation

    This page contains a few tutorials for using Matplotlib. For the old tutorials, see below. For shorter examples, see our examples page. You can also find external resources and a FAQ in our …

  9. Matplotlib for beginners Matplotlibisalibraryformaking2DplotsinPython. Itis designedwiththephilosophythatyoushouldbeableto createsimpleplotswithjustafewcommands:

  10. Interactive figures — Matplotlib 3.10.3 documentation

    Interactivity can be invaluable when exploring plots. The pan/zoom and mouse-location tools built into the Matplotlib GUI windows are often sufficient, but you can also use the event system to …

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