📊 Day 11: Violin Plot in Python

 

📊 Day 11: Violin Plot in Python

🔹 What is a Violin Plot?

A Violin Plot combines a box plot with a density plot.
It shows summary statistics and the full distribution shape of the data.

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🔹 When Should You Use It?

Use a violin plot when:

• You want to see distribution shape + statistics

• Comparing multiple groups

• Understanding data symmetry or multimodal behavior

• A box plot feels too minimal

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🔹 Example Scenario

Suppose you are analyzing:

• Exam scores of multiple classes

• Salary distribution across departments

• Customer wait times by location

A violin plot helps you see:

• Median and quartiles

• Where values are most concentrated

• Whether data has multiple peaks

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🔹 Key Idea Behind It

👉 Width of the violin shows data density
👉 Wider area = more data points
👉 Inner box/line shows median & quartiles

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🔹 Python Code (Violin Plot)

import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np 

data = np.random.normal(50, 10, 200) 

sns.violinplot(data=data)

plt.title("Violin Plot Example")
plt.ylabel("Values")
plt.show()

🔹 Output Explanation

• The shape shows distribution density

• The center line indicates the median

• Wider sections mean higher frequency

• Reveals patterns hidden in box plots

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🔹 Violin Plot vs Box Plot

Feature	Violin Plot	Box Plot
Distribution shape	Visible	Not visible
Statistics	Yes	Yes
Density info	Yes	No
Complexity	Medium	Simple

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🔹 Key Takeaways

• Violin plots reveal data distribution depth

• Best for comparative analysis

• Combines KDE + box plot

• Powerful tool for advanced EDA