Subplots for multiple charts in Data Analysis Python - Mini Project: Build & Apply

Subplots for multiple charts

📖 Scenario: You work as a data analyst for a small store. You have sales data for two products over four months. You want to create two charts side by side to compare their sales trends easily.

🎯 Goal: Create two line charts side by side using subplots to show monthly sales for Product A and Product B.

📋 What You'll Learn

Create a dictionary called sales_data with monthly sales for Product A and Product B

Create a variable called months with the list of month names

Use plt.subplots() to create two side-by-side plots

Plot Product A sales on the first subplot and Product B sales on the second subplot

Add titles to each subplot: 'Product A Sales' and 'Product B Sales'

Display the plots side by side

💡 Why This Matters

🌍 Real World

Creating multiple charts side by side helps compare different data sets visually, which is common in business reports and presentations.

💼 Career

Data analysts and scientists often use subplots to present multiple related charts clearly and efficiently.

1

Create the sales data dictionary

Create a dictionary called sales_data with these exact entries: 'Product A': [150, 200, 250, 300] and 'Product B': [180, 210, 230, 280].

Data Analysis Python

# Create the sales_data dictionary with exact values
# Your code here

Hint

Use curly braces {} to create the dictionary with keys 'Product A' and 'Product B' and their sales lists as values.

2

Create the months list

Create a list called months with these exact values: ['Jan', 'Feb', 'Mar', 'Apr'].

Data Analysis Python

sales_data = {'Product A': [150, 200, 250, 300], 'Product B': [180, 210, 230, 280]}
# Create the months list with exact values
# Your code here

Hint

Use square brackets [] to create the list of months in order.

3

Create subplots and plot the sales data

Import matplotlib.pyplot as plt. Use plt.subplots() to create two side-by-side plots stored in variables fig and axes. Plot months vs sales_data['Product A'] on axes[0] and months vs sales_data['Product B'] on axes[1]. Add titles 'Product A Sales' and 'Product B Sales' to the respective subplots.

Data Analysis Python

sales_data = {'Product A': [150, 200, 250, 300], 'Product B': [180, 210, 230, 280]}
months = ['Jan', 'Feb', 'Mar', 'Apr']
# Import matplotlib.pyplot as plt
# Create subplots with 1 row and 2 columns
# Plot Product A sales on axes[0]
# Plot Product B sales on axes[1]
# Add titles to both subplots
# Your code here

Hint

Use plt.subplots(1, 2) to create two plots side by side. Use axes[0].plot() and axes[1].plot() to plot each product's sales. Use set_title() to add titles.

4

Display the subplots

Add a line to display the plots using plt.show().

Data Analysis Python

import matplotlib.pyplot as plt

sales_data = {'Product A': [150, 200, 250, 300], 'Product B': [180, 210, 230, 280]}
months = ['Jan', 'Feb', 'Mar', 'Apr']

fig, axes = plt.subplots(1, 2, figsize=(10, 4))

axes[0].plot(months, sales_data['Product A'], marker='o')
axes[0].set_title('Product A Sales')

axes[1].plot(months, sales_data['Product B'], marker='o')
axes[1].set_title('Product B Sales')
# Display the plots
# Your code here

Hint

Use plt.show() to display the figure with both subplots.