A variety of plotting capabilities. (taken from examples/Plotting.py)
Image analysis with automated data slicing.

3D graphics: volumetric rendering, surface plots, scatter plots, and isosurfaces.

A variety of ROI types. Each ROI selects data from the underlying image and redisplays it below. (taken from examples/test_ROItypes.py)

Programmable flowcharts for fast prototyping.

For an example of pyqtgraph in use (and more screenshots), see ACQ4

Scientific Graphics and GUI Library for Python
Documentation and API Reference   -    GitHub Repository   -    Support mailing list

Install from PyPI:
                pip install pyqtgraph
or via conda:
                conda install -c conda-forge pyqtgraph
or from source on GitHub:
                git clone https://github.com/pyqtgraph/pyqtgraph
                cd pyqtgraph
                pip install .
recent changes  -  older releases

PyQtGraph is a pure-python graphics and GUI library built on PyQt / PySide and numpy. It is intended for use in mathematics / scientific / engineering applications. Despite being written entirely in python, the library is very fast due to its heavy leverage of numpy for number crunching and Qt's GraphicsView framework for fast display. PyQtGraph is distributed under the MIT open-source license.

Main Features:


PyQtGraph is known to run on Linux, Windows, and OSX.
It should, however, run on any platform which supports the following packages:


Documentation is hosted here.
If you would like to request a specific section of documentation, please ask on the forum. There are also many examples to look through; for a menu of examples run:
    python -m pyqtgraph.examples

Packaging for Distribution:

Applications written with pyqtgraph may be packaged as Windows exe files using py2exe or OSX dmg files using py2app.

Questions, feedback, and bug reports:

Comparison to other python graphics packages:

[Please note: I have not used these libraries for some time; please let me know if this information is outdated.]