
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 things possible. Create publication quality plots. …
Matplotlib cheatsheets — Visualization with Python
Contribute # Issues, suggestions, or pull-requests gratefully accepted at matplotlib/cheatsheets
Examples — Matplotlib 3.10.8 documentation
This has two advantages: the code you write will be more portable, and Matplotlib events are aware of things like data coordinate space and which axes the event occurs in so you don't have to mess with …
Tutorials — Matplotlib 3.10.8 documentation
Download all examples in Python source code: tutorials_python.zip Download all examples in Jupyter notebooks: tutorials_jupyter.zip
The Python Graph Gallery: hundreds of python charts with reproducible ...
Jul 24, 2021 · The Python Graph Gallery is a website that displays hundreds of chart examples made with python. It goes from very basic to highly customized examples and is based on common viz …
Timeline with lines, dates, and text - Matplotlib
Timeline with lines, dates, and text # How to create a simple timeline using Matplotlib release dates. Timelines can be created with a collection of dates and text. In this example, we show how to create …
History — Matplotlib 3.10.8 documentation
Matplotlib is a library for making 2D plots of arrays in Python. Although it has its origins in emulating the MATLAB graphics commands, it is independent of MATLAB, and can be used in a Pythonic, object …
Pyplot tutorial — Matplotlib 3.10.8 documentation
An example of four plots with the same data and different scales for the y-axis is shown below.
Plot types — Matplotlib 3.10.8 documentation
3D and volumetric data # Plots of three-dimensional (x, y, z), surface f (x, y) = z, and volumetric V x, y, z data using the mpl_toolkits.mplot3d library.
Mission Statement — Matplotlib 3.10.8 documentation
The Matplotlib developer community develops, maintains, and supports Matplotlib and its extensions to provide data visualization tools for the Scientific Python Ecosystem.