Most Python apps need to interact with data sources — whether that's a CSV file, database or remote APIs. One of the main benefits of using Python to build applications is being able to make use of Python's data science tools to process and analyse data.

With PySide6 you can make use of Qt's model view architecture to display performant views of any Python data in your applications. Or embed matplotlib and PyQtGraph plots for dynamic visualizations.

If you're using Qt Designer to create your applications, take a look at how to use PyQtGraph & Matplotlib widgets inside Qt Designer.

Explore PySide6 for Data Science

PySide6 for Data Science

Plotting With Matplotlib and PySide6

Create PySide6 plots with the popular Python plotting library

Plotting With PyQtGraph and PySide6

Create custom plots in PySide6 with PyQtGraph

Embedding Custom Widgets from Qt Designer in PySide6

Learn how to use custom widgets in your PySide6 applications when designing with Qt Designer

Matplotlib with QtQuick (QML)

How to display Matplotlib plots inside a QML application using PySide6

The ModelView Architecture in PySide6

Qt's MVC-like interface for displaying data in views

Displaying Tabular Data in PySide6 ModelViews

Create customized table views with conditional formatting, numpy and pandas data sources.

Size of Matplotlib's navigation toolbar (too large by default compared to the other widgets)

How to customize the size and appearance of the Matplotlib navigation toolbar in PyQt6/PySide6

Using PyQtGraph PlotWidget with PySide6

Fixing the graphWidget PlotWidget issue when porting PyQtGraph code from PyQt5 to PySide6

Fixing Crashes When Using NumPy Arrays with QImage in Qt Threads

How to safely pass image data between threads when streaming video or updating displays