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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.
If you are using Python from https://www.python.org, Homebrew, or Macports, then you can use the standard pip installer to install Matplotlib binaries in the form of wheels. pip is installed by default with python.org and Homebrew Python, but needs to be manually installed on Macports with
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.
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.
Matplotlib cheatsheets. Support Matplotlib. Matplotlib 3.9.2 documentation #. Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations.
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.
matplotlib.pyplot.plot(*args, scalex=True, scaley=True, data=None, **kwargs) [source] #. Plot y versus x as lines and/or markers. Call signatures: 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.
This tutorial covers some basic usage patterns and best practices to help you get started with Matplotlib. import matplotlib.pyplot as plt import numpy as np A simple example #
matplotlib.pyplot.scatter(x, y, s=None, c=None, marker=None, cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, *, edgecolors=None, plotnonfinite=False, data=None, **kwargs) [source] #. A scatter plot of y vs. x with varying marker size and/or color.