Stacked bar charts in Matplotlib - Mini Project: Build & Apply

Stacked Bar Charts

📖 Scenario: You work for a small company that sells three types of products: Books, Games, and Electronics. You want to show how many units of each product were sold in the first three months of the year.

🎯 Goal: Create a stacked bar chart using matplotlib to visualize the monthly sales of each product. Each bar will represent a month, and the segments in the bar will show sales of Books, Games, and Electronics stacked on top of each other.

📋 What You'll Learn

Create lists for months and sales of each product

Create a variable for the width of the bars

Use plt.bar to plot stacked bars for Books, Games, and Electronics

Display the final stacked bar chart with labels and legend

💡 Why This Matters

🌍 Real World

Stacked bar charts help businesses compare multiple categories over time or groups, making it easier to see total and individual contributions.

💼 Career

Data analysts and scientists use stacked bar charts to present sales, survey results, or any grouped data clearly to stakeholders.

1

Create sales data lists

Create a list called months with values 'Jan', 'Feb', 'Mar'. Create three lists called books_sales, games_sales, and electronics_sales with the values [120, 150, 170], [80, 90, 100], and [60, 70, 90] respectively.

Matplotlib

# Create lists for months and sales of Books, Games, and Electronics
# Your code here

Need a hint?

Use square brackets [] to create lists with the exact values given.

2

Set bar width

Create a variable called bar_width and set it to 0.5. This will control the width of each bar in the chart.

Matplotlib

months = ['Jan', 'Feb', 'Mar']
books_sales = [120, 150, 170]
games_sales = [80, 90, 100]
electronics_sales = [60, 70, 90]
# Create a variable bar_width and set it to 0.5
# Your code here

Need a hint?

Use a simple assignment to create bar_width with value 0.5.

3

Plot stacked bars

Import matplotlib.pyplot as plt. Create a list positions with values [0, 1, 2] for the x-axis positions. Use plt.bar to plot the books_sales bars at positions with width bar_width. Then plot games_sales bars stacked on top of books_sales by setting the bottom parameter to books_sales. Finally, plot electronics_sales bars stacked on top of the sum of books_sales and games_sales. Use plt.bar with bottom set to the sum of books_sales and games_sales. Use the variable names exactly as given.

Matplotlib

months = ['Jan', 'Feb', 'Mar']
books_sales = [120, 150, 170]
games_sales = [80, 90, 100]
electronics_sales = [60, 70, 90]
bar_width = 0.5
# Import matplotlib.pyplot as plt
# Create positions list [0, 1, 2]
# Plot books_sales bars
# Plot games_sales bars stacked on books_sales
# Plot electronics_sales bars stacked on books_sales + games_sales
# Your code here

Need a hint?

Use zip to add books_sales and games_sales element-wise for the bottom parameter of the last bar.

4

Display the stacked bar chart

Add x-axis labels using plt.xticks with positions and months. Add a legend with plt.legend(). Finally, call plt.show() to display the chart.

Matplotlib

import matplotlib.pyplot as plt

months = ['Jan', 'Feb', 'Mar']
books_sales = [120, 150, 170]
games_sales = [80, 90, 100]
electronics_sales = [60, 70, 90]
bar_width = 0.5

positions = [0, 1, 2]

plt.bar(positions, books_sales, width=bar_width, label='Books')
plt.bar(positions, games_sales, width=bar_width, bottom=books_sales, label='Games')

books_games_sum = [b + g for b, g in zip(books_sales, games_sales)]
plt.bar(positions, electronics_sales, width=bar_width, bottom=books_games_sum, label='Electronics')
# Add x-axis labels with plt.xticks
# Add legend with plt.legend()
# Show the plot with plt.show()
# Your code here

Need a hint?

Use plt.xticks(positions, months) to label the x-axis. Use plt.legend() to show the legend. Use plt.show() to display the chart window.