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 PyQt5 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 Data Science

Displaying tabular data in Qt5 ModelViews

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

Plotting with Matplotlib

Create PyQt5 plots with the popular Python plotting library

Plotting With PyQtGraph updated

Create Custom Plots in PyQt with PyQtGraph

The ModelView Architecture

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