Python Data Visualization Transcripts
Chapter: Seaborn
Lecture: Customizing Seaborn summary
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Let's summarize the options you have for customizing your Seaborn plots, first If you want to customize all plots,
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you can use the Seaborne theme API. This consists of set style and set theme and is easy to use and great for high level adjustments to the style of
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your visualization. If you want to get into more detail for the axis level plots you can use the matplot lib axes level API.
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In this example we would set up the figure in the axis and then using that ax1 variable, we can set the X label,
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the Y label, pretty much any customization that we could do in matplot lib We can do, it is very powerful but it is only available for the
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axis level plots for the figure level plots. There are facet grid methods that we can apply. We get a facet grid as a return object.
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When we call one of these plots. In this example, the displot and then we can use set or set access
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labels, set titles, save the figure or add our reference line using these facet grid methods. This is very simple and streamlined API.
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That works well when you create multiple plots but it does have limited customization options outside of the ones that are predefined.
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It's important to understand the distinction between these and as you start to use Seaborn, you can play around and find what works best for you.