Creating a Bar Plot with Pandas and Matplotlib

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

2. Bar Plot with Pandas and Matplotlib

Write a Pandas program that create a Bar plot with Pandas and Matplotlib.

The following exercise create a bar plot using Pandas and Matplotlib to visualize categorical data.

Sample Solution :

Code :

import pandas as pd
import matplotlib.pyplot as plt

# Create a sample DataFrame
df = pd.DataFrame({
    'Category': ['A', 'B', 'C', 'D'],
    'Values': [50, 80, 30, 90]
})

# Create a bar plot of the 'Category' vs 'Values'
df.plot(kind='bar', x='Category', y='Values')

# Add a title
plt.title('Category vs Values')

# Display the plot
plt.show()

Output:

Explanation:

• Created a DataFrame with categories and corresponding values.
• Used the plot() function with kind='bar' to create a bar plot of 'Category' vs 'Values'.
• Added a title and displayed the plot using plt.show().

For more Practice: Solve these Related Problems:

• Write a Pandas program to create a vertical bar plot that shows the frequency of categorical data sorted in descending order.
• Write a Pandas program to generate a horizontal bar plot with custom colors for each bar and an accompanying legend.
• Write a Pandas program to create a stacked bar plot from a DataFrame with multiple categorical columns.
• Write a Pandas program to create a grouped bar plot from a pivoted DataFrame and include error bars representing standard deviation.

Python-Pandas Code Editor:

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