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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. Make interactive figures that can zoom, pan, update. Customize visual style and layout.
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 figure, plots some lines in a plotting area, decorates the plot with labels, etc.
Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations.
Check out Plot types to get an overview of the types of plots you can create with Matplotlib. Learn Matplotlib from the ground up in the Quick-start guide.
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 user guide. Pyplot tutorial. Image tutorial. The Lifecycle of a Plot. Artist tutorial.
This tutorial covers some basic usage patterns and best practices to help you get started with Matplotlib.
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 procedural interface, so take a look at the examples/api directory for some example code working with the API.
One convenient way to install Matplotlib with other useful Python software is to use the Anaconda Python scientific software collection, which includes Python itself and a wide range of libraries; if you need a library that is not available from the collection, you can install it yourself using standard methods such as pip. See the Anaconda web ...
Matplotlib Application Interfaces (APIs) Interacting with figures. 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.
plot([x], y, [fmt], *, data=None, **kwargs) plot([x], y, [fmt], [x2], y2, [fmt2], ..., **kwargs) The coordinates of the points or line nodes are given by x, y. The optional parameter fmt is a convenient way for defining basic formatting like color, marker and linestyle.