A comprehensive practical guide

Data visualization is a fundamental piece of data science. If used in exploratory data analysis, data visualizations are highly effective at unveiling the underlying structure within a dataset or discovering relationships among variables.

Another common use case of data visualizations is to deliver results or findings. They carry much more informative power than plain numbers. Thus, we often use data visualization in storytelling, a critical part of the data science pipeline.

We can enhance the capabilities of data visualizations by adding interactivity. The Altair library for Python is highly efficient at creating interactive visualizations.

In this article, we will go over the basic components of interactivity in Altair. We will also do examples to put these components into action. Let’s start by importing the libraries.

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