Plotting multiple lines in Matplotlib - Mini Project: Build & Apply

Plotting multiple lines

📖 Scenario: You work as a data analyst for a small company that tracks sales of three products over four months. You want to visualize how sales changed over time for each product.

🎯 Goal: Create a line plot with matplotlib that shows sales trends for three products over four months. Each product's sales should be a separate line on the same graph.

📋 What You'll Learn

Use matplotlib.pyplot to create the plot

Plot three lines, one for each product's sales

Label the x-axis with the months

Add a legend to identify each product's line

💡 Why This Matters

🌍 Real World

Visualizing sales trends helps businesses understand which products are performing well over time and make better decisions.

💼 Career

Data analysts and data scientists often create line plots to compare multiple data series and communicate insights clearly.

1

Create sales data for three products

Create a dictionary called sales_data with keys 'Product A', 'Product B', and 'Product C'. Each key should have a list of four sales numbers: [10, 15, 20, 25] for Product A, [12, 18, 22, 28] for Product B, and [5, 7, 12, 15] for Product C.

Matplotlib

# Create the sales_data dictionary with sales lists for three products
# Your code here

Need a hint?

Use curly braces {} to create a dictionary. Each product name is a key with a list of four numbers as the value.

2

Create a list of months for the x-axis

Create a list called months with the values ['Jan', 'Feb', 'Mar', 'Apr'] to represent the four months.

Matplotlib

sales_data = {
    'Product A': [10, 15, 20, 25],
    'Product B': [12, 18, 22, 28],
    'Product C': [5, 7, 12, 15]
}
# Create the months list with four month names
# Your code here

Need a hint?

Use square brackets [] to create a list of strings for the months.

3

Plot the sales lines for each product

Import matplotlib.pyplot as plt. Use a for loop with variables product and sales to iterate over sales_data.items(). Inside the loop, call plt.plot(months, sales, label=product) to plot each product's sales line with a label.

Matplotlib

sales_data = {
    'Product A': [10, 15, 20, 25],
    'Product B': [12, 18, 22, 28],
    'Product C': [5, 7, 12, 15]
}
months = ['Jan', 'Feb', 'Mar', 'Apr']

# Import matplotlib.pyplot as plt
# Use a for loop with product, sales in sales_data.items()
# Inside the loop, plot months vs sales with label=product
# Your code here

Need a hint?

Remember to import matplotlib.pyplot as plt. Use for product, sales in sales_data.items(): to loop through the dictionary.

4

Add labels, legend, and show the plot

Call plt.xlabel('Month') and plt.ylabel('Sales') to label the axes. Then call plt.legend() to show the legend. Finally, call plt.show() to display the plot.

Matplotlib

import matplotlib.pyplot as plt

sales_data = {
    'Product A': [10, 15, 20, 25],
    'Product B': [12, 18, 22, 28],
    'Product C': [5, 7, 12, 15]
}
months = ['Jan', 'Feb', 'Mar', 'Apr']

for product, sales in sales_data.items():
    plt.plot(months, sales, label=product)

# Add x-axis label 'Month'
# Add y-axis label 'Sales'
# Add legend
# Show the plot
# Your code here

Need a hint?

Use plt.xlabel() and plt.ylabel() to label axes. Use plt.legend() to add the legend. Use plt.show() to display the plot window.