matplotlib is a pure Python 2D plotting library designed to bring publication quality plotting to Python with a syntax familiar to MATLAB users. All of the plotting commands in the pylab interface can be accessed either via a functional interface familiar to MATLAB users or an object oriented interface familiar to Python users.
The library uses numpy for handling large data sets and supports a variety of output backends including GTK GTKAgg, GTKCairo, FltkAgg, QtAgg, TkAgg and WXAgg.
matplotlib is designed with the philosophy that you should be able to create simple plots with just a few commands, or even just one. It was originally conceived with MatLab’s users in mind. It’s the oldest plotting library but is still under active development.
Key Features
- Extremely powerful – matplotlib can create almost any visualization.
- Generate:
- Plots;
- Histograms;
- Power spectra;
- Bar charts;
- Error charts;
- Scatter plots and more.
- Designed to be usable as MATLAB.
- Object-oriented API for embedding plots into applications.
- Procedural “pylab” interface based on a state machine.
- Based on Python, a full-featured modern object-oriented programming language suitable for large-scale software development.
- Numerous rendering backends: GTK, GTKAgg, GTKCairo, GTK3Agg, GTK3Cairo, MacOSX, nbAgg, Qt4Agg, Qt4Cairo, Qt5Agg, Qt5Cairo, TkAgg, TkCairo, WebAgg, WX, WXAgg, WXCairo, agg, cairo, gdk, pdf, pgf, ps, svg, template
- Suitable for fast scripting, including CGI scripts.
- Free, open source, no license servers.
- Native SVG support.
- Well-tested tool with mature code.
- Rich ecosystem of Python tools are built around matplotlib.
- Support for Python 3 (support for Python 2 was dropped).
If you are looking to create web/interactive graphs, I’d recommend one of the other Python visualization packages.
Website: matplotlib.org
Support: Documentation, GitHub Code Repository
Developer: Michael Droettboom and many contributors (project started by the late John Hunter)
License: Based on the PSF license. Matplotlib only uses BSD compatible code.
matplotlib is written in Python. Learn Python with our recommended free books and free tutorials.
Related Software
| Image Processing Libraries | |
|---|---|
| matplotlib | Python 2D plotting library |
| OpenCV | Library that includes several hundreds of computer vision algorithms |
| VIPS | Fast image processing library with low memory requirements |
| SciPy | Scientific Computing Tools for Python |
| Pillow | Fork of the Python Imaging Library |
| Pillow-SIMD | Highly optimized downstream Pillow fork |
| scikit-image | Collection of algorithms for image processing |
| ImageMagick | Uses multiple computational threads to increase performance |
| GraphicsMagick | Billed as the Swiss army knife of image processing. |
| GEGL | Generic Graphics Library |
| Mahotas | Library of fast computer vision algorithms |
| SimpleITK | Image analysis toolkit with a large number of components |
| Netpbm | Toolkit for manipulation of graphic images |
| LibGD | Library for the dynamic creation of images by developers |
Read our verdict in the software roundup.
| Plotting Tools | |
|---|---|
| matplotlib | Python based plotting system in a style similar to Matlab |
| ggplot2 | Powerful R package for declaratively creating graphics |
| gnuplot | Command-line driven interactive plotting program |
| ROOT | Solves the data analysis challenges of high-energy physics |
| Octave | Built-in plotting and visualization tools |
| DataMelt | Produces professional graphics with libraries for data manipulation |
| Veusz | Scientific plotting and graphing program |
| LabPlot | Data plotting and function analysis tool for KDE |
| GLE | Graphics Layout Engine |
| PyVista | 3D plotting and mesh analysis |
| SciDAVis | Scientific Data Analysis and Visualization |
| PLplot | Scientific plotting library |
| Ctioga | Command-line plotting utility |
| AlphaPlot | Fork of SciDAVis |
| RLPlot | Generate publication quality graphs |
| ZeGrapher | 2D math and data plotter |
| Genius | Educational tool in mathematics and for research |
| Kst | Real-time large dataset viewing and plotting tool |
| Plots | Simple graph plotting app for GNOME |
| SSPlot | Simple plotting utility and numerical simulator |
Read our verdict in the software roundup.
| Python Visualization Packages | |
|---|---|
| matplotlib | Python 2D plotting library which produces publication quality figures |
| Diagrams | Draw the cloud system architecture in Python code |
| Bokeh | Elegant, concise construction of versatile graphics |
| Dash | Python framework for building analytical web applications |
| seaborn | Python visualization library based on matplotlib |
| Plotly | Interactive, browser-based graphing library for Python |
| VisPy | Visualize massive datasets in real time |
| Vega-Altair | Declarative Visualization in Python |
| plotnine | Grammar of graphics for Python |
| PyQtGraph | Python graphics and GUI library built on PyQt4 / PySide and numpy |
| bqplot | Interactive Plotting Framework for the Jupyter Notebook |
| Vaex | Fast visualization of big data |
| folium | Visualize data in a Leaflet map |
| HoloViews | Make Data Analysis and Visualization Seamless |
| Datashader | Generates aggregate arrays and representations of them as images |
| yt | Multi-code Toolkit for Analyzing and Visualizing Volumetric Data |
| Glumpy | Intuitive interface between NumPy and modern OpenGL |
| GeoViews | Explore and visualize geographical, meteorological, and oceanographic datasets |
| Pygal | Dynamic SVG charting library |
| Glue | Multi-dimensional linked-data exploration |
Read our verdict in the software roundup.
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