Styling Options

As discussed earlier, one of the biggest advantages of using Seaborn is that you can retain its aesthetic properties and also the Matplotlib functionalities to perform additional customisations. Before we continue with our case study analysis, let’s study some styling options that are available in Seaborn.

As you just learnt, you can use several styling options by using the sns.set_style() function. This gives you control over the way the axes and grid are presented. Here’s the link to its official documentation. Given below are certain style options that you can use for Seaborn in conjunction with the original customisations.

You should go ahead and try out the styling options and select the one that suits you the best and stick to it for the rest of the case study demonstration. In the next segment, you will explore the case study data using pie charts and bar graphs from the seaborn library. 

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