Python Polars: The Definitive Guide

Chapter 16. Visualizing Data

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The previous chapters have given you all the tools you need to transform raw data into a polished DataFrame. But how do you turn such a DataFrame into something insightful?

One way is through data visualization, and Python provides a plethora of packages for that. Packages include Matplotlib for low-level plotting, hvPlot for quick visualizations, Bokeh for interactive graphs, Plotnine for leveraging the grammar of graphics in Python, and Altair for using the built-in plotting capabilties of Polars. Figure 16-1 gives an impression of Python’s elaborate data visualization landscape.

Figure 16-1. Python’s data visualization landscape. Adapted, with permission, from the original by Jake VanderPlas.

This is both a blessing and a curse, because it’s likely there’s a package that fits your needs, while it’s ...