Gallery¶

This gallery contains examples of the many things you can do with Matplotlib. Click on any image to see the full image and source code.

For longer tutorials, see our tutorials page. You can also find external resources and a FAQ in our user guide.

Lines, bars and markers¶

Stacked bar chart¶

Grouped bar chart with labels¶

Horizontal bar chart¶

Broken Barh¶

Plotting categorical variables¶

Plotting the coherence of two signals¶

CSD Demo¶

Errorbar limit selection¶

Errorbar Subsample¶

EventCollection Demo¶

Eventplot Demo¶

Filled polygon¶

Filling the area between lines¶

Fill Betweenx Demo¶

Hatch-filled histograms¶

Bar chart with gradients¶

Discrete distribution as horizontal bar chart¶

Join styles and cap styles¶

Customizing dashed line styles¶

Linestyles¶

Marker filling-styles¶

Marker Reference¶

Markevery Demo¶

prop_cycle property markevery in rcParams¶

Plotting masked and NaN values¶

Multicolored lines¶

Psd Demo¶

Scatter Custom Symbol¶

Scatter Demo2¶

Scatter plot with histograms¶

Scatter Masked¶

Scatter plot with pie chart markers¶

Scatter Star Poly¶

Scatter Symbol¶

Scatter plots with a legend¶

Simple Plot¶

Using span_where¶

Spectrum Representations¶

Stackplot Demo¶

Stem Plot¶

Step Demo¶

Creating a timeline with lines, dates, and text¶

hlines and vlines¶

Cross- and Auto-Correlation Demo¶

Images, contours and fields¶

Affine transform of an image¶

Contourf and log color scale¶

BboxImage Demo¶

Figimage Demo¶

Creating annotated heatmaps¶

Image antialiasing¶

Clipping images with patches¶

Image Demo¶

Image Masked¶

Image Nonuniform¶

Blend transparency with color in 2-D images¶

Modifying the coordinate formatter¶

Interpolations for imshow¶

Contour plot of irregularly spaced data¶

Advanced quiver and quiverkey functions¶

Tricontour Smooth Delaunay¶

Tricontour Smooth User¶

Subplots, axes and figures¶

Aligning Labels¶

Axes Demo¶

Controlling view limits using margins and sticky_edges¶

Custom Figure subclasses¶

Resizing axes with constrained layout¶

Resizing axes with tight layout¶

Different scales on the same axes¶

Figure Title¶

Creating adjacent subplots¶

Geographic Projections¶

Combining two subplots using subplots and GridSpec¶

Using Gridspec to make multi-column/row subplot layouts¶

Creating multiple subplots using plt.subplots¶

Plots with different scales¶

Zoom region inset axes¶

Statistics¶

Percentiles as horizontal bar chart¶

Artist customization in box plots¶

Box plots with custom fill colors¶

Boxplots¶

Box plot vs. violin plot comparison¶

Boxplot drawer function¶

Plot a confidence ellipse of a two-dimensional dataset¶

Violin plot customization¶

Errorbar function¶

Different ways of specifying error bars¶

Including upper and lower limits in error bars¶

Creating boxes from error bars using PatchCollection¶

Hexbin Demo¶

Histograms¶

Using histograms to plot a cumulative distribution¶

Demo of the histogram (hist) function with a few features¶

Demo of the histogram function's different histtype settings¶

The histogram (hist) function with multiple data sets¶

Producing multiple histograms side by side¶

Violin plot basics¶

Pie and polar charts¶

Labeling a pie and a donut¶

Bar chart on polar axis¶

Polar Demo¶

Polar Legend¶

Scatter plot on polar axis¶

Text, labels and annotations¶

Using accented text in matplotlib¶

Composing Custom Legends¶

Dashpoint Label¶

Date tick labels¶

Custom tick formatter for time series¶

Demo Annotation Box¶

Demo Text Path¶

Demo Text Rotation Mode¶

$../_images/sphx_glr_dfrac_demo_thumb.png$

The difference between \dfrac and \frac¶

Labeling ticks using engineering notation¶

Fancyarrow Demo¶

Fancytextbox Demo¶

Figure legend demo¶

Configuring the font family¶

Using a ttf font file in Matplotlib¶

Font table¶

Fonts demo (object-oriented style)¶

Fonts demo (kwargs)¶

Legend using pre-defined labels¶

Legend Demo¶

Artist within an artist¶

A mathtext image as numpy array¶

Rendering math equation using TeX¶

Precise text layout¶

Controlling style of text and labels using a dictionary¶

Default text rotation demonstration¶

Text Rotation Relative To Line¶

Titles Demo¶

Unicode minus¶

Usetex Baseline Test¶

Usetex Demo¶

Usetex Fonteffects¶

Text watermark¶

Color¶

For more in-depth information about the colormaps available in matplotlib as well as a description of their properties, see the colormaps tutorial.

Color Demo¶

Color by y-value¶

Colors in the default property cycle¶

Styling with cycler¶

Colorbar¶

Colormap reference¶

Creating a colormap from a list of colors¶

List of named colors¶

Style sheets¶

Bayesian Methods for Hackers style sheet¶

Dark background style sheet¶

FiveThirtyEight style sheet¶

ggplot style sheet¶

Grayscale style sheet¶

Solarized Light stylesheet¶

Style sheets reference¶

Showcase¶

Anatomy of a figure¶

Bachelor's degrees by gender¶

Firefox¶

Integral as the area under a curve¶

Shaded & power normalized rendering¶

XKCD¶

Event handling¶

Matplotlib supports event handling with a GUI neutral event model, so you can connect to Matplotlib events without knowledge of what user interface Matplotlib will ultimately be plugged in to. This has two advantages: the code you write will be more portable, and Matplotlib events are aware of things like data coordinate space and which axes the event occurs in so you don't have to mess with low level transformation details to go from canvas space to data space. Object picking examples are also included.

Close Event¶

Coords demo¶

Data Browser¶

Figure Axes Enter Leave¶

Interactive functions¶

Trifinder Event Demo¶

Viewlims¶

Zoom Window¶

Front Page¶

Frontpage 3D example¶

Frontpage contour example¶

Frontpage histogram example¶

Frontpage plot example¶

3D plotting¶

Plot 2D data on 3D plot¶

Demo of 3D bar charts¶

Create 2D bar graphs in different planes¶

Demonstrates plotting contour (level) curves in 3D¶

Demonstrates plotting contour (level) curves in 3D using the extend3d option¶

Projecting contour profiles onto a graph¶

Filled contours¶

Projecting filled contour onto a graph¶

Custom hillshading in a 3D surface plot¶

Create 3D histogram of 2D data¶

Parametric Curve¶

Lorenz Attractor¶

2D and 3D Axes in same Figure¶

Automatic Text Offsetting¶

Draw flat objects in 3D plot¶

Generate polygons to fill under 3D line graph¶

3D quiver plot¶

Rotating a 3D plot¶

3D scatterplot¶

3D plots as subplots¶

3D surface (color map)¶

3D surface (solid color)¶

3D surface (checkerboard)¶

3D surface with polar coordinates¶

Text annotations in 3D¶

Triangular 3D contour plot¶

Triangular 3D filled contour plot¶

Triangular 3D surfaces¶

More triangular 3D surfaces¶

3D voxel / volumetric plot¶

3D voxel plot of the numpy logo¶

3D voxel / volumetric plot with rgb colors¶

3D voxel / volumetric plot with cylindrical coordinates¶

3D wireframe plot¶

Rotating 3D wireframe plot¶

3D wireframe plots in one direction¶

Our Favorite Recipes¶

Here is a collection of short tutorials, examples and code snippets that illustrate some of the useful idioms and tricks to make snazzier figures and overcome some matplotlib warts.

Fixing common date annoyances¶

Easily creating subplots¶

Fill Between and Alpha¶

Placing text boxes¶

Sharing axis limits and views¶

Scales¶

These examples cover how different scales are handled in Matplotlib.

Exploring normalizations¶

Scales¶

Symlog Demo¶

Units¶

These examples cover the many representations of units in Matplotlib.

Annotation with units¶

Artist tests¶

Bar demo with units¶

Group barchart with units¶

Inches and Centimeters¶

Unit handling¶

Embedding Matplotlib in graphical user interfaces¶

You can embed Matplotlib directly into a user interface application by following the embedding_in_SOMEGUI.py examples here. Currently matplotlib supports wxpython, pygtk, tkinter and pyqt4/5.

When embedding Matplotlib in a GUI, you must use the Matplotlib API directly rather than the pylab/pyplot proceedural interface, so take a look at the examples/api directory for some example code working with the API.