Creating a Grouped Bar Plot for Multiple Categories Using Pandas

Last update on April 09 2025 12:56:05 (UTC/GMT +8 hours)

10. Grouped Bar Plot for Multiple Categories

Write a Pandas program to create a grouped bar plot for multiple categories.

This exercise shows how to create a grouped bar plot for multiple categories using Pandas and Matplotlib.

Sample Solution :

Code :

import pandas as pd
import matplotlib.pyplot as plt

# Create a sample DataFrame
df = pd.DataFrame({
    'Category': ['A', 'B', 'C'],
    'Product_A': [50, 80, 30],
    'Product_B': [40, 60, 20]
})

# Create a bar plot for multiple products
df.plot(kind='bar', x='Category', y=['Product_A', 'Product_B'], figsize=(8, 5))

# Add a title
plt.title('Product A and B Sales by Category')

# Display the plot
plt.show()

Output:

Explanation:

• Created a DataFrame with sales data for two products across different categories.
• Used plot(kind='bar') to create a grouped bar plot showing both 'Product_A' and 'Product_B' sales by category.
• Added a title and displayed the plot.

For more Practice: Solve these Related Problems:

• Write a Pandas program to create a grouped bar plot from a pivot table and customize the spacing between groups.
• Write a Pandas program to generate a grouped bar plot that compares average values across multiple categories.
• Write a Pandas program to create a grouped bar plot with error bars representing the standard deviation for each group.
• Write a Pandas program to produce a grouped bar plot and sort the groups based on a specific numeric metric.

Python-Pandas Code Editor:

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