Bar charts in Data Analysis Python - Mini Project: Build & Apply

Bar charts

📖 Scenario: You work at a small bakery. You want to show how many cakes of each type you sold last week. A bar chart is a great way to show this information clearly.

🎯 Goal: Create a bar chart that shows the number of cakes sold for each cake type.

📋 What You'll Learn

Create a dictionary with cake types and their sales numbers

Create a list of cake types from the dictionary keys

Create a list of sales numbers from the dictionary values

Use matplotlib to create a bar chart with cake types on the x-axis and sales numbers on the y-axis

Add labels for the x-axis, y-axis, and a title to the chart

Display the bar chart

💡 Why This Matters

🌍 Real World

Bar charts are used in business to show sales, in schools to show test scores, and in many places to compare amounts clearly.

💼 Career

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

1

Create the sales data dictionary

Create a dictionary called cake_sales with these exact entries: 'Chocolate': 30, 'Vanilla': 45, 'Strawberry': 25, 'Lemon': 20.

Data Analysis Python

# Create the cake_sales dictionary with the exact cake types and sales numbers
# Your code here

Hint

Use curly braces {} to create a dictionary. Separate keys and values with a colon : and items with commas.

2

Prepare lists for the bar chart

Create a list called cake_types containing the keys of cake_sales. Create another list called sales_numbers containing the values of cake_sales.

Data Analysis Python

cake_sales = {'Chocolate': 30, 'Vanilla': 45, 'Strawberry': 25, 'Lemon': 20}
# Create cake_types list from cake_sales keys
# Create sales_numbers list from cake_sales values
# Your code here

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 cake_types and sales_numbers to create the bar chart. Add x-axis label 'Cake Types', y-axis label 'Number Sold', and title 'Cake Sales Last Week' using plt.xlabel(), plt.ylabel(), and plt.title().

Data Analysis Python

cake_sales = {'Chocolate': 30, 'Vanilla': 45, 'Strawberry': 25, 'Lemon': 20}
cake_types = list(cake_sales.keys())
sales_numbers = list(cake_sales.values())
# Import matplotlib.pyplot as plt
# Create bar chart with cake_types and sales_numbers
# Add x-axis label 'Cake Types'
# Add y-axis label 'Number Sold'
# Add title 'Cake Sales Last Week'
# Your code here

Hint

Use plt.bar(x, y) to create bars. Use plt.xlabel(), plt.ylabel(), and plt.title() to add labels and title.

4

Display the bar chart

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

Data Analysis Python

import matplotlib.pyplot as plt

cake_sales = {'Chocolate': 30, 'Vanilla': 45, 'Strawberry': 25, 'Lemon': 20}
cake_types = list(cake_sales.keys())
sales_numbers = list(cake_sales.values())

plt.bar(cake_types, sales_numbers)
plt.xlabel('Cake Types')
plt.ylabel('Number Sold')
plt.title('Cake Sales Last Week')
# Display the bar chart
# Your code here

Hint

Call plt.show() to open a window with the bar chart.