Stacked area chart in Matplotlib - Mini Project: Build & Apply

Stacked Area Chart

📖 Scenario: You work as a data analyst for a small company. You have sales data for three products over four quarters. Your manager wants to see how the total sales and individual product sales changed over time in a clear visual format.

🎯 Goal: Create a stacked area chart using matplotlib to show the sales trends of three products over four quarters.

📋 What You'll Learn

Create a dictionary called sales_data with keys 'Q1', 'Q2', 'Q3', 'Q4' and values as lists of sales numbers for three products.

Create a list called quarters with the values 'Q1', 'Q2', 'Q3', 'Q4'.

Use matplotlib.pyplot to create a stacked area chart.

Label the x-axis as 'Quarter' and y-axis as 'Sales'.

Add a legend with product names 'Product A', 'Product B', and 'Product C'.

💡 Why This Matters

🌍 Real World

Stacked area charts are useful to visualize how different parts contribute to a whole over time, such as sales of multiple products across quarters.

💼 Career

Data analysts and scientists often create stacked area charts to present trends and comparisons clearly to stakeholders.

1

Create the sales data dictionary

Create a dictionary called sales_data with keys 'Q1', 'Q2', 'Q3', 'Q4'. Each key should have a list of three sales numbers: [100, 150, 200] for 'Q1', [120, 160, 210] for 'Q2', [130, 170, 220] for 'Q3', and [140, 180, 230] for 'Q4'.

Matplotlib

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

Need a hint?

Use curly braces {} to create the dictionary. Each key is a quarter string, and the value is a list of three numbers.

2

Create the quarters list

Create a list called quarters with the values 'Q1', 'Q2', 'Q3', and 'Q4' in this order.

Matplotlib

sales_data = {
    'Q1': [100, 150, 200],
    'Q2': [120, 160, 210],
    'Q3': [130, 170, 220],
    'Q4': [140, 180, 230]
}
# Create the quarters list with exact values
# Your code here

Need a hint?

Use square brackets [] to create the list with the quarter strings in order.

3

Prepare data and plot the stacked area chart

Import matplotlib.pyplot as plt. Extract the sales lists for each quarter from sales_data in the order of quarters. Create three lists: product_a, product_b, and product_c containing sales for each product across quarters. Use plt.stackplot with quarters and these three lists to create a stacked area chart. Add a legend with labels 'Product A', 'Product B', and 'Product C'. Label the x-axis as 'Quarter' and y-axis as 'Sales'.

Matplotlib

sales_data = {
    'Q1': [100, 150, 200],
    'Q2': [120, 160, 210],
    'Q3': [130, 170, 220],
    'Q4': [140, 180, 230]
}
quarters = ['Q1', 'Q2', 'Q3', 'Q4']

# Import matplotlib.pyplot as plt
# Create product_a, product_b, product_c lists from sales_data
# Use plt.stackplot with quarters and product lists
# Add legend and axis labels
# Your code here

Need a hint?

Use list comprehension to get sales for each product. Use plt.stackplot with the quarters and product lists. Add labels and legend for clarity.

4

Display the stacked area chart

Use plt.show() to display the stacked area chart.

Matplotlib

import matplotlib.pyplot as plt

sales_data = {
    'Q1': [100, 150, 200],
    'Q2': [120, 160, 210],
    'Q3': [130, 170, 220],
    'Q4': [140, 180, 230]
}
quarters = ['Q1', 'Q2', 'Q3', 'Q4']

product_a = [sales_data[q][0] for q in quarters]
product_b = [sales_data[q][1] for q in quarters]
product_c = [sales_data[q][2] for q in quarters]

plt.stackplot(quarters, product_a, product_b, product_c, labels=['Product A', 'Product B', 'Product C'])
plt.xlabel('Quarter')
plt.ylabel('Sales')
plt.legend(loc='upper left')

# Display the plot
# Your code here

Need a hint?

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