Enrich Matplotlib Plots with Annotations

Guide the viewer’s attention.

While creating data visualizations, there are often certain parts that are particularly important, and they may require some additional context.

Yet, this additional information may not be immediately obvious to the viewer.

A good data storyteller always ensures that:

• The plot guides the viewer’s attention to these key areas.

• The plot concisely provides any information needed for better interpretation.

One great (yet underrated) to provide extra info is by adding text annotations to a plot, as depicted below:

Such efforts always ensure that the plot indeed communicates what we intend it to depict — even if the plot’s creator is not present at that time.

In matplotlib, you can use 𝐚𝐧𝐧𝐨𝐭𝐚𝐭𝐞(), as depicted below:

It adds explanatory texts to your plot, which lets you guide a viewer’s attention to specific areas and aid their understanding.

Isn’t that cool?

You can find the Jupyter notebook for today’s newsletter here: Annotated plots notebook.

👉 Over to you: What are some other ways you use to enrich Matplotlib plots

Thanks for reading!

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