Matplotlib vs. PyQtGraph vs. Python vs. Seaborn Comparison Chart

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. Basic 2D plotting in interactive view boxes. Line and scatter plots. Data can be panned/scaled by mouse. Fast drawing for real-time data display and interaction. Displays most data types (int or float; any bit depth; RGB, RGBA, or luminance). Functions for slicing multidimensional images at arbitrary angles (great for MRI data). Rapid update for video display or real-time interaction. Image display with interactive lookup tables and level control. Mesh rendering with isosurface generation. Interactive viewports rotate/zoom with mouse. Basic 3D scenegraph for easier programming.

Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. For a brief introduction to the ideas behind the library, you can read the introductory notes or the paper. Visit the installation page to see how you can download the package and get started with it. You can browse the example gallery to see some of the things that you can do with seaborn, and then check out the tutorials or API reference to find out how. To see the code or report a bug, please visit the GitHub repository. General support questions are most at home on StackOverflow, which has a dedicated channel for seaborn.