Line plots in Data Analysis Python - Mini Project: Build & Apply

Line plots

📖 Scenario: You are a data analyst working with monthly sales data for a small store. You want to visualize how sales changed over the first six months of the year.

🎯 Goal: Create a line plot to show monthly sales trends from January to June.

📋 What You'll Learn

Create a dictionary with months as keys and sales numbers as values

Create a list of months in order

Use matplotlib to plot sales data as a line plot

Label the x-axis as 'Month' and y-axis as 'Sales'

Display the plot

💡 Why This Matters

🌍 Real World

Line plots are used to show trends over time, like sales, temperature, or stock prices.

💼 Career

Data analysts and scientists use line plots to communicate patterns and changes clearly to others.

1

Create the sales data dictionary

Create a dictionary called sales_data with these exact entries: 'Jan': 150, 'Feb': 200, 'Mar': 180, 'Apr': 220, 'May': 210, 'Jun': 230.

Data Analysis Python

# Your code here

Hint

Use curly braces {} to create a dictionary with month names as keys and sales numbers as values.

2

Create the list of months in order

Create a list called months with these exact values in order: 'Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun'.

Data Analysis Python

sales_data = {'Jan': 150, 'Feb': 200, 'Mar': 180, 'Apr': 220, 'May': 210, 'Jun': 230}
# Your code here

Hint

Use square brackets [] to create a list of months in the correct order.

3

Plot the sales data as a line plot

Import matplotlib.pyplot as plt. Create a list called sales that contains the sales numbers from sales_data in the order of months. Use plt.plot(months, sales) to create a line plot.

Data Analysis Python

sales_data = {'Jan': 150, 'Feb': 200, 'Mar': 180, 'Apr': 220, 'May': 210, 'Jun': 230}
months = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun']
# Your code here

Hint

Use a list comprehension to get sales numbers in order. Then use plt.plot() to draw the line plot.

4

Add labels and display the plot

Use plt.xlabel('Month') and plt.ylabel('Sales') to label the axes. Then use plt.show() to display the plot.

Data Analysis Python

import matplotlib.pyplot as plt

sales_data = {'Jan': 150, 'Feb': 200, 'Mar': 180, 'Apr': 220, 'May': 210, 'Jun': 230}
months = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun']
sales = [sales_data[month] for month in months]
plt.plot(months, sales)
# Your code here

Hint

Use plt.xlabel() and plt.ylabel() to add axis labels. Then call plt.show() to display the plot window.