Horizontal grouped bars in Matplotlib - Mini Project: Build & Apply

Horizontal grouped bars

📖 Scenario: You are working for a small company that wants to compare sales of two products across three regions. They want a clear visual to see which product sells better in each region.

🎯 Goal: Create a horizontal grouped bar chart using matplotlib to compare sales of two products across three regions.

📋 What You'll Learn

Create a list called regions with the values 'North', 'South', and 'East'.

Create two lists called sales_product_a and sales_product_b with sales numbers for each region.

Create a variable called bar_width and set it to 0.4.

Use matplotlib.pyplot to create horizontal grouped bars for both products side by side for each region.

Add labels for the y-axis with region names and a legend for the products.

Display the plot.

💡 Why This Matters

🌍 Real World

Horizontal grouped bar charts are useful to compare multiple categories side by side across different groups, such as sales of different products in various regions.

💼 Career

Data analysts and scientists often create grouped bar charts to visualize and communicate comparisons clearly to stakeholders.

1

Create the sales data lists

Create a list called regions with the values 'North', 'South', and 'East'. Then create two lists called sales_product_a with values 120, 150, 100 and sales_product_b with values 90, 130, 110.

Matplotlib

# Create the regions and sales lists
# Your code here

Need a hint?

Use square brackets to create lists. Put the region names as strings in regions. Put the sales numbers as integers in sales_product_a and sales_product_b.

2

Set the bar width

Create a variable called bar_width and set it to 0.4.

Matplotlib

regions = ['North', 'South', 'East']
sales_product_a = [120, 150, 100]
sales_product_b = [90, 130, 110]
# Create bar_width variable
# Your code here

Need a hint?

Just assign the number 0.4 to the variable bar_width.

3

Create the horizontal grouped bars

Import matplotlib.pyplot as plt. Create a list called y_positions using range(len(regions)). Use plt.barh() to plot sales_product_a at y_positions with height bar_width. Then plot sales_product_b at [y + bar_width for y in y_positions] with height bar_width. Add y-axis ticks at the middle of the grouped bars with region names using plt.yticks(). Add a legend with labels 'Product A' and 'Product B'.

Matplotlib

import matplotlib.pyplot as plt

regions = ['North', 'South', 'East']
sales_product_a = [120, 150, 100]
sales_product_b = [90, 130, 110]
bar_width = 0.4

# Create y_positions list
# Plot horizontal bars for Product A and Product B
# Set y-axis ticks and legend
# Your code here

Need a hint?

Use plt.barh() twice with adjusted y positions to create grouped bars. Use plt.yticks() to label the regions in the middle of the groups.

4

Display the plot

Use plt.show() to display the horizontal grouped bar chart.

Matplotlib

import matplotlib.pyplot as plt

regions = ['North', 'South', 'East']
sales_product_a = [120, 150, 100]
sales_product_b = [90, 130, 110]
bar_width = 0.4

y_positions = list(range(len(regions)))

plt.barh(y_positions, sales_product_a, height=bar_width, label='Product A')
plt.barh([y + bar_width for y in y_positions], sales_product_b, height=bar_width, label='Product B')

plt.yticks([y + bar_width / 2 for y in y_positions], regions)
plt.legend()

# Display the plot
# Your code here

Need a hint?

Call plt.show() to display the chart window.