Learn Drawing Violin Plots

A violinplot is a hybrid of a box plot and a kernel density plot (KDE).

While a boxplot only shows summary statistics (median, quartiles), a violinplot reveals the full distribution of the data. The "width" of the violin at any given point represents the density (how many data points are there).

Key Parameters

split=True: if you have a hue variable with exactly two categories (e.g., "Male"/"Female"), this parameter draws one category on the left half of the violin and the other on the right. This makes comparing them incredibly easy;
inner: controls what is drawn inside the violin;
'box' (default): draws a mini boxplot;
'point': draws individual data points;
'quartile': draws lines for the 25th, 50th, and 75th percentiles;
bw (bandwidth): controls the smoothness of the curve (just like in KDE). A smaller number reveals more detail (and noise); a larger number makes it smoother.

Example

Here is a violinplot showing the total_bill distribution. Notice how split=True allows us to compare "Smokers" vs "Non-Smokers" inside the same violin.


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import seaborn as sns
import matplotlib.pyplot as plt

# Load dataset
df = sns.load_dataset('tips')

# Create a split violinplot
sns.violinplot(
    data=df,
    x='day',
    y='total_bill',
    hue='smoker',
    split=True,    # Compare sides directly
    inner='quartile', # Show quartile lines
    palette='muted'
)

plt.show()

Task

Swipe to start coding

Create a detailed visualization of the tips data.

Import the necessary libraries and read the tips.csv dataset.
Create a violinplot and assign the result to a variable named g (this captures the plot's Axes object):
- Map 'day' to x and 'total_bill' to y.
- Group by 'sex' using hue.
- Use the 'rocket' palette.
- Split the violins to compare genders side-by-side (split=True).
- Show individual data points inside by setting inner='point'.
- Set the smoothing bandwidth bw to 0.2.
Set the title of the plot to 'Tips violinplot' using the g variable (e.g., g.set_title(...)).
Display the plot.

Solution

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Section 1. Chapter 12

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