How to Use KDE Plot in Python: Simple Guide with Examples

To create a KDE plot in Python, use the kdeplot function from the seaborn library, which visualizes the probability density of a dataset smoothly. Import seaborn, pass your data to kdeplot, and call plt.show() to display the plot.

Syntax

The basic syntax for a KDE plot in Python using seaborn is:

• seaborn.kdeplot(data, shade=False, bw_adjust=1, clip=None, ax=None)
• data: The dataset to plot (list, array, or pandas Series).
• shade: If True, fills the area under the curve.
• bw_adjust: Adjusts the smoothness of the curve (higher is smoother).
• clip: Limits the range of the plot.
• ax: Matplotlib axis to plot on (optional).

python

import seaborn as sns
import matplotlib.pyplot as plt

sns.kdeplot(data=[1, 2, 3, 4, 5], shade=True)
plt.show()

Example

This example shows how to create a KDE plot for a list of numbers and customize its appearance by shading the area under the curve and adjusting the bandwidth for smoothness.

python

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

# Generate 100 random numbers from a normal distribution
data = np.random.normal(loc=0, scale=1, size=100)

# Create KDE plot with shaded area and smoother curve
sns.kdeplot(data, shade=True, bw_adjust=0.5)
plt.title('KDE Plot of Normal Distribution')
plt.xlabel('Value')
plt.ylabel('Density')
plt.show()

Output

A smooth bell-shaped curve plot appears showing the density distribution of the data.

Common Pitfalls

Common mistakes when using kdeplot include:

• Passing empty or non-numeric data causes errors or empty plots.
• Not calling plt.show() so the plot does not display.
• Using very small datasets can produce noisy or misleading KDE curves.
• Confusing shade with fill (use shade=True to fill under the curve).

Always check your data and call plt.show() after plotting.

python

import seaborn as sns
import matplotlib.pyplot as plt

# Wrong: empty data
sns.kdeplot([])
plt.show()

# Right: valid numeric data
sns.kdeplot([1, 2, 3, 4, 5], shade=True)
plt.show()

Output

First plot shows no curve (empty), second plot shows a smooth KDE curve with shaded area.

Quick Reference

Remember these tips for KDE plots:

• Use seaborn.kdeplot(data) to create the plot.
• Set shade=True to fill under the curve.
• Adjust smoothness with bw_adjust (default is 1).
• Always call plt.show() to display the plot.
• Works best with numeric data and enough samples (usually 20+).

Key Takeaways

Use seaborn's kdeplot to create smooth density plots from numeric data.

Set shade=True to fill the area under the KDE curve for better visualization.

Call plt.show() after plotting to display the graph.

Avoid empty or very small datasets to get meaningful KDE plots.

Adjust bw_adjust to control the smoothness of the KDE curve.