Plot scatter points on polar axis in Matplotlib

To plot scatter points on polar axis in Matplotlib, we can create a polar coordinate system where points are positioned using angles (theta) and radial distances (r). This is useful for visualizing circular or angular data patterns.

Basic Polar Scatter Plot

Let's start with a simple example that demonstrates the key components ?

import numpy as np
import matplotlib.pyplot as plt

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

# Generate sample data
N = 150
r = 2 * np.random.rand(N)
theta = 2 * np.pi * np.random.rand(N)
area = 200 * r**2
colors = theta

# Create polar plot
fig = plt.figure()
ax = fig.add_subplot(projection='polar')
c = ax.scatter(theta, r, c=colors, s=area, cmap='hsv', alpha=0.75)

plt.show()

How It Works

The polar scatter plot requires these key steps:

• Theta values − angles in radians (0 to 2?)
• R values − radial distances from the center
• Projection='polar' − creates the polar coordinate system
• Color mapping − uses theta values to create a color gradient
• Size mapping − point sizes based on radial distance

Customizing Polar Scatter Plots

Here's an example with more customization options ?

import numpy as np
import matplotlib.pyplot as plt

# Generate structured data
angles = np.linspace(0, 2*np.pi, 50)
radius = np.random.uniform(0.5, 3, 50)
sizes = np.random.uniform(50, 300, 50)
colors = radius

# Create customized polar scatter plot
fig, ax = plt.subplots(figsize=(8, 8), subplot_kw=dict(projection='polar'))

scatter = ax.scatter(angles, radius, c=colors, s=sizes, 
                    cmap='viridis', alpha=0.7, edgecolors='black', linewidth=0.5)

# Customize the plot
ax.set_title('Customized Polar Scatter Plot', pad=20)
ax.set_ylim(0, 3.5)
ax.grid(True)

# Add colorbar
plt.colorbar(scatter, ax=ax, shrink=0.8, pad=0.1)

plt.show()

Parameters

Output

Conclusion

Polar scatter plots are perfect for displaying data with angular relationships. Use projection='polar' to create the coordinate system, and map colors and sizes to data values for enhanced visualization.