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Controlling Figure Aesthetics

Explore how to control figure aesthetics in Seaborn to enhance the impact of your data visualizations. Learn to apply different styles, remove axes spines, adjust plot size and aspect ratio, and scale plot elements using methods like set_style, despine, and set_context. This lesson improves your ability to present data clearly and effectively.

It’s time to talk about one of the most important aspects of data presentation, report writing, and storytelling—figure aesthetics. This essential aspect is often ignored by many new data scientists, which significantly reduces the impact of all their efforts. We believe that it’s vital to always pay attention to figure aesthetics.

Although we’ve seen how to control figure aesthetics in seaborn in the previous lessons, let’s now go over it with more detail.

C++
import seaborn as sns
import matplotlib.pyplot as plt
tips = sns.load_dataset('tips')
print(tips.head())

Seaborn figure styles

The set_style() method

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