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Violin Plot

  • This module teaches how to create violin plots in Seaborn to visualize data distribution and density. You will learn how violin plots combine boxplot elements and help compare categories effectively in Python.

  • What is a Violin Plot?

    A Violin Plot is a combination of:

    • Box Plot

    • Kernel Density Plot (Distribution curve)

    It shows:

    Distribution of data
    Probability density
    Median & Quartiles
    Spread
    Shape of data


    Distribution + Boxplot Combination

    Theory

    A violin plot includes:

    • Inner box → Median & Quartiles

    • Outer shape → Data distribution (density curve)

    It gives more information than a box plot.

    Why better than box plot?

    Box plot shows only summary statistics.
     Violin plot also shows shape of distribution.

    Example Code

Distribution of Total Bill – Violin Plot

This code creates a violin plot to visualize the distribution of the total_bill column from the tips dataset. 

import seaborn as sns
import matplotlib.pyplot as plt

tips = sns.load_dataset("tips")

sns.violinplot(y="total_bill", data=tips)
plt.title("Violin Plot of Total Bill")
plt.show()
Lesson image

  • Output Explanation

    • Middle line → Median

    • Thick center → High data density

    • Wide areas → Many observations

    • Thin areas → Fewer observations

    If violin is wide in middle → Most values are concentrated there.


    Density Visualization

    Theory

    Violin plot uses Kernel Density Estimation (KDE) to show:

    • How data is distributed

    • Where values are concentrated

    • Skewness of data

    Key Observations

    • Symmetrical shape → Normal distribution

    • Long tail → Skewed distribution

    • Two wide areas → Bimodal distribution

    Example — Tip Distribution

Distribution of Tips – Violin Plot

This code creates a violin plot to visualize the distribution of the tip amounts from the tips dataset. 

sns.violinplot(y="tip", data=tips)
plt.title("Distribution of Tips")
plt.show()
Lesson image

  • Output Explanation

    • If top is thin → Few high tips

    • If bottom is wide → Many small tips

    • Shape shows spending behavior


    Category Comparison

    Theory

    Violin plot is very powerful for:

    • Comparing distributions across categories

    • Understanding variation between groups

    Example — Compare Total Bill by Day

Total Bill Distribution by Day – Violin Plot

This code creates a grouped violin plot to visualize how total bill amounts are distributed across different days of the week. 

sns.violinplot(x="day", y="total_bill", data=tips)
plt.title("Total Bill Distribution by Day")
plt.show()
Lesson image

  • Output Explanation

    • X-axis → Days

    • Y-axis → Total Bill

    • Each violin → Distribution per day

    Insights Example:

    • Saturday may have wider shape → Higher variability

    • Sunday may show skewness

    • Friday may have smaller distribution

    Example — Multiple Category Comparison (Hue)

Total Bill by Day and Gender hue

This visualization compares the distribution of total bill amounts across different days of the week, separated by gender. 

sns.violinplot(x="day", y="total_bill", hue="sex", data=tips)
plt.title("Total Bill by Day and Gender")
plt.show()
Lesson image

  • Output Explanation

    • Two violins per day

    • Compare Male vs Female spending

    • Observe:

      • Who has wider spread

      • Who has higher median

      • Distribution differences


    Custom Styling

    Split Violin

sns.violinplot(x="day", y="total_bill", hue="sex",
              data=tips, split=True)

  • Shows half violin for each gender.

    Horizontal Violin

sns.violinplot(y="day", x="total_bill", data=tips)

  • Show Only Distribution (Remove Inner Box)

sns.violinplot(x="day", y="total_bill", data=tips, inner=None)
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