Travis-CI:

# Sample plots in Matplotlib¶

Here you’ll find a host of example plots with the code that generated them.

## Line Plot¶

Here’s how to create a line plot with text labels using plot().

Simple Plot

## Subplot demo¶

Multiple axes (i.e. subplots) are created with the subplot() command:

Subplot

## Histograms¶

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

Histogram Features

## Path demo¶

You can add arbitrary paths in Matplotlib using the matplotlib.path module:

Path Patch

## mplot3d¶

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

Surface3d

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.

Plot Streamplot

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.

Ellipse Demo

## Bar charts¶

Use the bar() command to make bar charts, which includes customizations such as error bars:

Barchart Demo

You can also create stacked bars (bar_stacked.py), or horizontal bar charts (barh.py).

## Pie charts¶

The pie() command allows you to 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.

Pie Features

## Table demo¶

The table() command adds a text table to an axes.

Table Demo

## 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.

Scatter Demo2

## Slider demo¶

Matplotlib has basic GUI widgets that are independent of the graphical user interface you are using, allowing you to write cross GUI figures and widgets. See matplotlib.widgets and the widget examples.

Slider Demo

## Fill demo¶

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

Fill

Thanks to Andrew Straw for adding this function.

## Date demo¶

You can plot timeseries data with major and minor ticks and custom tick formatters for both.

Date

See matplotlib.ticker and matplotlib.dates for details and usage.

## Log plots¶

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

Log Demo

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

## Polar plots¶

The polar() command generates polar plots.

Polar Demo

## Legends¶

The legend() command automatically generates figure legends, with MATLAB-compatible legend placement commands.

Legend

Thanks to Charles Twardy for input on the legend command.

## 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.

Mathtext Examples

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.

Tex Demo

## EEG demo¶

You can embed Matplotlib into pygtk, wx, Tk, or Qt applications. Here is a screenshot of an EEG viewer called pbrain.

The lower axes uses specgram() to plot the spectrogram of one of the EEG channels.

For examples of how to embed Matplotlib in different toolkits, see:

## XKCD-style sketch plots¶

Matplotlib supports plotting in the style of xkcd.

Xkcd

# An extra set of sample plots for the thumbnail image.
import matplotlib.pyplot as plt
import numpy as np

np.random.seed(19680801)
data = np.random.randn(2, 100)

fig, axs = plt.subplots(2, 2, figsize=(5, 5))
axs[0, 0].hist(data[0])
axs[1, 0].scatter(data[0], data[1])
axs[0, 1].plot(data[0], data[1])
axs[1, 1].hist2d(data[0], data[1])

plt.show()

Total running time of the script: ( 0 minutes 0.075 seconds)

Gallery generated by Sphinx-Gallery