Why bar charts compare categories in Matplotlib - See It in Action

Why Bar Charts Compare Categories

📖 Scenario: Imagine you run a small bakery. You want to see which types of cakes sell the most each day. You have sales numbers for three cake types: Chocolate, Vanilla, and Strawberry.

🎯 Goal: You will create a bar chart to compare the sales of these cake types. This will help you see which cake is the most popular at a glance.

📋 What You'll Learn

Create a dictionary called cake_sales with exact entries: 'Chocolate': 30, 'Vanilla': 45, 'Strawberry': 25

Create a list called categories that contains the keys from cake_sales

Create a list called sales that contains the values from cake_sales

Use matplotlib.pyplot to create a bar chart with categories on the x-axis and sales on the y-axis

Add a title to the chart: 'Cake Sales Comparison'

Label the x-axis as 'Cake Type' and the y-axis as 'Number Sold'

Display the bar chart

💡 Why This Matters

🌍 Real World

Bar charts help businesses quickly compare sales or counts across different categories, like product types or customer groups.

💼 Career

Data analysts and scientists use bar charts to communicate insights clearly to teams and decision makers.

1

Create the cake sales data

Create a dictionary called cake_sales with these exact entries: 'Chocolate': 30, 'Vanilla': 45, 'Strawberry': 25

Matplotlib

# Create the cake_sales dictionary with exact entries
# Your code here

Need a hint?

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

2

Prepare categories and sales lists

Create a list called categories that contains the keys from cake_sales. Then create a list called sales that contains the values from cake_sales.

Matplotlib

cake_sales = {'Chocolate': 30, 'Vanilla': 45, 'Strawberry': 25}
# Create categories list from cake_sales keys
# Create sales list from cake_sales values
# Your code here

Need a hint?

Use list() with cake_sales.keys() and cake_sales.values() to get lists.

3

Create the bar chart

Import matplotlib.pyplot as plt. Use plt.bar() with categories and sales to create a bar chart. Add the title 'Cake Sales Comparison'. Label the x-axis as 'Cake Type' and the y-axis as 'Number Sold'.

Matplotlib

cake_sales = {'Chocolate': 30, 'Vanilla': 45, 'Strawberry': 25}
categories = list(cake_sales.keys())
sales = list(cake_sales.values())
# Import matplotlib.pyplot as plt
# Create bar chart with categories and sales
# Add title and axis labels
# Your code here

Need a hint?

Use plt.bar() to create bars, and plt.title(), plt.xlabel(), plt.ylabel() to add text.

4

Show the bar chart

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

Matplotlib

import matplotlib.pyplot as plt

cake_sales = {'Chocolate': 30, 'Vanilla': 45, 'Strawberry': 25}
categories = list(cake_sales.keys())
sales = list(cake_sales.values())

plt.bar(categories, sales)
plt.title('Cake Sales Comparison')
plt.xlabel('Cake Type')
plt.ylabel('Number Sold')
# Display the bar chart
# Your code here

Need a hint?

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