Histograms¶

The hist() command automatically generates histograms and returns the bin counts or probabilities:

(Source code, png, pdf)

mplot3d¶

The mplot3d toolkit (see mplot3d tutorial and mplot3d Examples) has support for simple 3d graphs including surface, wireframe, scatter, and bar charts.

(Source code, png, pdf)

Thanks to John Porter, Jonathon Taylor, Reinier Heeres, and Ben Root for the mplot3d toolkit. This toolkit is included with all standard matplotlib installs.

Streamplot¶

The streamplot() function plots the streamlines of a vector field. In addition to simply plotting the streamlines, it allows you to map the colors and/or line widths of streamlines to a separate parameter, such as the speed or local intensity of the vector field.

(Source code)

This feature complements the quiver() function for plotting vector fields. Thanks to Tom Flannaghan and Tony Yu for adding the streamplot function.

Ellipses¶

In support of the Phoenix mission to Mars (which used matplotlib to display ground tracking of spacecraft), Michael Droettboom built on work by Charlie Moad to provide an extremely accurate 8-spline approximation to elliptical arcs (see Arc), which are insensitive to zoom level.

(Source code, png, pdf)

Pie charts¶

The pie() command allows you to easily create pie charts. Optional features include auto-labeling the percentage of area, exploding one or more wedges from the center of the pie, and a shadow effect. Take a close look at the attached code, which generates this figure in just a few lines of code.

(Source code, png, pdf)

Scatter demo¶

The scatter() command makes a scatter plot with (optional) size and color arguments. This example plots changes in Google’s stock price, with marker sizes reflecting the trading volume and colors varying with time. Here, the alpha attribute is used to make semitransparent circle markers.

(Source code, png, pdf)

Fill demo¶

The fill() command lets you plot filled curves and polygons:

(Source code, png, pdf)

Thanks to Andrew Straw for adding this function.

Log plots¶

The semilogx(), semilogy() and loglog() functions simplify the creation of logarithmic plots.

(Source code, png, pdf)

Thanks to Andrew Straw, Darren Dale and Gregory Lielens for contributions log-scaling infrastructure.

Mathtext_examples¶

Below is a sampling of the many TeX expressions now supported by matplotlib’s internal mathtext engine. The mathtext module provides TeX style mathematical expressions using FreeType and the DejaVu, BaKoMa computer modern, or STIX fonts. See the matplotlib.mathtext module for additional details.

(Source code)

(png, pdf)

Matplotlib’s mathtext infrastructure is an independent implementation and does not require TeX or any external packages installed on your computer. See the tutorial at Writing mathematical expressions.

Native TeX rendering¶

Although matplotlib’s internal math rendering engine is quite powerful, sometimes you need TeX. Matplotlib supports external TeX rendering of strings with the usetex option.

(Source code, png, pdf)

XKCD-style sketch plots¶

matplotlib supports plotting in the style of xkcd.

(Source code)