Labels, titles, and legends in Data Analysis Python - Mini Project: Build & Apply

Labels, titles, and legends

📖 Scenario: You are analyzing sales data for a small store. You want to create a simple bar chart to show the sales of different products. To make the chart clear, you will add labels to the axes, a title, and a legend.

🎯 Goal: Create a bar chart using Python's matplotlib library that shows product sales. Add an x-axis label, a y-axis label, a chart title, and a legend to explain the colors.

📋 What You'll Learn

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

Create a variable called colors that assigns a color to each product.

Use matplotlib to plot a bar chart with the sales data.

Add an x-axis label called Product.

Add a y-axis label called Sales.

Add a chart title called Sales by Product.

Add a legend that shows which color belongs to which product.

💡 Why This Matters

🌍 Real World

Adding labels, titles, and legends to charts helps people understand data clearly. This is important when sharing reports or presentations.

💼 Career

Data scientists and analysts often create charts to explain their findings. Knowing how to label charts properly is a key skill for clear communication.

1

Create the sales data dictionary

Create a dictionary called sales with these exact entries: 'Apples': 30, 'Bananas': 45, 'Cherries': 25, 'Dates': 40.

Data Analysis Python

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

Hint

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

2

Create the colors list

Create a list called colors with these exact values in order: 'red', 'yellow', 'pink', 'brown'.

Data Analysis Python

sales = {'Apples': 30, 'Bananas': 45, 'Cherries': 25, 'Dates': 40}
# Create the colors list matching the products order
# Your code here

Hint

Use square brackets [] to create the list with the exact colors in the order of the products.

3

Plot the bar chart with labels, title, and legend

Import matplotlib.pyplot as plt. Use plt.bar() to plot the sales data with product names on the x-axis and sales numbers on the y-axis. Use the colors list for the bar colors. Add an x-axis label 'Product', a y-axis label 'Sales', and a title 'Sales by Product'. Add a legend that shows each product with its color.

Data Analysis Python

sales = {'Apples': 30, 'Bananas': 45, 'Cherries': 25, 'Dates': 40}
colors = ['red', 'yellow', 'pink', 'brown']
# Import matplotlib.pyplot as plt
# Plot the bar chart with sales and colors
# Add x-axis label 'Product'
# Add y-axis label 'Sales'
# Add title 'Sales by Product'
# Add legend with product names and colors
# Your code here

Hint

Use plt.bar() with color=colors. Use plt.xlabel(), plt.ylabel(), and plt.title() to add labels and title. Use plt.legend() with the bars and product names.

4

Display the chart

Use plt.show() to display the bar chart with labels, title, and legend.

Data Analysis Python

import matplotlib.pyplot as plt

sales = {'Apples': 30, 'Bananas': 45, 'Cherries': 25, 'Dates': 40}
colors = ['red', 'yellow', 'pink', 'brown']

products = list(sales.keys())
sales_values = list(sales.values())

bars = plt.bar(products, sales_values, color=colors)

plt.xlabel('Product')
plt.ylabel('Sales')
plt.title('Sales by Product')

plt.legend(bars, products)
# Display the plot
# Your code here

Hint

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