Marker size variation in Matplotlib - Mini Project: Build & Apply

Marker size variation

📖 Scenario: You are analyzing sales data for a small store. You want to visualize the sales amounts for different products using a scatter plot. To make the plot more informative, you will vary the size of the markers based on the sales amount.

🎯 Goal: Create a scatter plot where the marker size changes according to the sales amount for each product.

📋 What You'll Learn

Create a dictionary called sales with product names as keys and sales amounts as values.

Create a list called sizes that contains marker sizes based on the sales amounts.

Use matplotlib.pyplot to create a scatter plot with product names on the x-axis and sales amounts on the y-axis.

Set the marker sizes in the scatter plot using the sizes list.

Display the plot.

💡 Why This Matters

🌍 Real World

Visualizing sales data with marker size variation helps quickly identify which products sell more, making it easier to focus on popular items.

💼 Career

Data analysts and scientists often use scatter plots with varying marker sizes to represent additional data dimensions visually.

1

Create the sales data dictionary

Create a dictionary called sales with these exact entries: 'Apples': 50, 'Bananas': 30, 'Cherries': 70, 'Dates': 40, and 'Elderberries': 60.

Matplotlib

# Create the sales dictionary with product names and sales amounts
# Your code here

Need a hint?

Use curly braces {} to create the dictionary with the exact keys and values.

2

Create the sizes list based on sales

Create a list called sizes that contains the sales amounts multiplied by 10 for each product in sales. Use a list comprehension iterating over sales.values().

Matplotlib

sales = {'Apples': 50, 'Bananas': 30, 'Cherries': 70, 'Dates': 40, 'Elderberries': 60}
# Create the sizes list by multiplying each sales amount by 10
# Your code here

Need a hint?

Use a list comprehension like [amount * 10 for amount in sales.values()].

3

Create the scatter plot with varying marker sizes

Import matplotlib.pyplot as plt. Use plt.scatter() to create a scatter plot with product names on the x-axis and sales amounts on the y-axis. Set the marker sizes using the sizes list. Use sales.keys() for x values and sales.values() for y values.

Matplotlib

sales = {'Apples': 50, 'Bananas': 30, 'Cherries': 70, 'Dates': 40, 'Elderberries': 60}
sizes = [amount * 10 for amount in sales.values()]
# Import matplotlib.pyplot as plt
# Create scatter plot with product names on x-axis, sales amounts on y-axis, and marker sizes from sizes
# Your code here

Need a hint?

Use plt.scatter(list(sales.keys()), list(sales.values()), s=sizes) to plot.

4

Display the scatter plot

Use plt.show() to display the scatter plot.

Matplotlib

import matplotlib.pyplot as plt

sales = {'Apples': 50, 'Bananas': 30, 'Cherries': 70, 'Dates': 40, 'Elderberries': 60}
sizes = [amount * 10 for amount in sales.values()]

plt.scatter(list(sales.keys()), list(sales.values()), s=sizes)
plt.xlabel('Product')
plt.ylabel('Sales Amount')
plt.title('Sales Amounts with Marker Size Variation')
# Display the plot
# Your code here

Need a hint?

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