How to label and change the scale of a Seaborn kdeplot's axes? (Matplotlib)

To label and change the scale of a Seaborn kdeplot's axes, we can customize both the axis labels and scale using matplotlib functions. This is useful for creating more informative and professionally formatted density plots.

Basic Steps

• Set the figure size and adjust the padding between and around the subplots
• Create random data points using numpy
• Plot Kernel Density Estimate (KDE) using kdeplot() method
• Set axis scale and labels using matplotlib functions
• Display the figure using show() method

Example

Here's how to create a KDE plot with customized axis labels and scale ?

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

plt.rcParams["figure.figsize"] = [7.50, 3.50]
plt.rcParams["figure.autolayout"] = True

# Generate random data
data = np.random.randn(100)

# Create KDE plot
k = sns.kdeplot(x=data, fill=True)

# Customize Y-axis
plt.yticks(k.get_yticks(), [f'{tick:.2f}' for tick in k.get_yticks()])
plt.ylabel('Density', fontsize=12)

# Customize X-axis
plt.xlabel('Value', fontsize=12)

plt.show()

Advanced Customization

You can further customize the plot with different scales and formatting ?

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

plt.rcParams["figure.figsize"] = [8.00, 4.00]
plt.rcParams["figure.autolayout"] = True

# Generate sample data
data = np.random.exponential(2, 200)

# Create KDE plot
ax = sns.kdeplot(x=data, fill=True, color='skyblue')

# Set logarithmic scale for x-axis
ax.set_xscale('log')

# Customize labels
ax.set_xlabel('Log Scale Values', fontsize=12, fontweight='bold')
ax.set_ylabel('Density', fontsize=12, fontweight='bold')
ax.set_title('KDE Plot with Logarithmic Scale', fontsize=14)

# Format tick labels
ax.tick_params(axis='both', labelsize=10)

plt.show()

Key Parameters

Output

Conclusion

Use matplotlib functions like set_xlabel(), set_ylabel(), and set_xscale() to customize Seaborn KDE plot axes. This allows for better data presentation and improved plot readability.