Matplotlib introduction

By Martin McBride, 2019-03-03
Tags: installing webserver numeric python pandas matplotlib scipy data science
Categories: matplotlib numpy

Matplotlib is a versatile 2D plotting library. The main website is here, but in these tutorials we will highlight some of the main features, using simple examples.

Matplotlib can be used to create quick plots, from a Python script or even the Python console. You can create a plot with a couple of lines of code, using the default styling. If you want more control, the API lets you set all aspects of the plot, such as the fonts, colours and line styles. You can add titles, place several plots in the same image, control the axes, and so on.

Matplotlib is an important component of Python's support for data science. You can use Matplotlib with NumPy, which allows you to interface with any other library that supports numpy data, such as scipy, pandas etc.

It can also be integrated into UI applications (using Tkinter, wxWidgets or Qt for example), and can be used in a webserver backend to serve dynamic graphs (for example using Flask of Django).


Later versions of Matplotlib can be installed using

pip install matplotlib

or see the main Matplotlib website for other options.

Data and code

All the data and code used in this tutorial is available on github, as described in Data and code.

In this section

See also

If you found this article useful, you might be interested in the book NumPy Recipes or other books by the same author.

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