Circular Bar Plot in Python

Below, are the code examples, of a circular ar plot in Python.

Example 1: Circular Bar Plot Creation Using Matplotlib

In this example, below Python code uses the Matplotlib library to generate a circular bar plot. It imports necessary modules, defines sample data with categories and values, and then creates a subplot with polar projection. Finally, it generates bars on the polar axes corresponding to each category’s value, resulting in a circular bar plot visualization.

Python3

import matplotlib.pyplot as plt
import numpy as np

# Sample data
categories = ['Category 1', 'Category 2', 'Category 3', 'Category 4']
values = [20, 35, 30, 25]

# Create a circular bar plot
fig, ax = plt.subplots(subplot_kw=dict(polar=True))
bars = ax.bar(np.arange(len(categories)) * 2 * np.pi / len(categories), values)

plt.show()

Output

fig 1. Output of the above code.

Example 2: Customizing a Circular Bar Plot in Matplotlib

In this example, below code uses Matplotlib to create a circular bar plot with customizations. It includes sample data, custom colors, and adds labels to each bar. Additional plot adjustments such as starting angle, direction, and axis limits are applied for improved visualization before displaying the final circular bar plot.

Python3

import matplotlib.pyplot as plt
import numpy as np

# Sample data
categories = ['Category 1', 'Category 2', 'Category 3', 'Category 4']
values = [20, 35, 30, 25]
colors = ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728']  # Custom colors for bars

# Create a circular bar plot
fig, ax = plt.subplots(subplot_kw=dict(polar=True))
bars = ax.bar(np.arange(len(categories)) * 2 * np.pi /
              len(categories), values, color=colors, alpha=1)

# Add labels to each bar
for i, (label, angle) in enumerate(zip(categories, np.arange(len(categories)) * 2 * np.pi / len(categories))):
    x = angle
    y = values[i] + 1  # Adjust height for label placement
    ax.text(x, y, label, ha='center', va='center', fontsize=8, color='black')

# Customizing the plot
ax.set_theta_offset(np.pi / 2)  # Offset to start the bars from the top
ax.set_theta_direction(-1)  # Clockwise direction for bars
# Adjust the y-axis limit for better visualization
ax.set_ylim(0, max(values) + 5)
ax.set_yticks([])  # Hide the y-axis ticks
ax.spines['polar'].set_visible(False)  # Hide the polar axis line

plt.show()

Output

fig 2. Creative way of circular bar