Arrow annotations in Matplotlib - Mini Project: Build & Apply

Arrow Annotations with Matplotlib

📖 Scenario: You are creating a simple plot to show the sales trend of a product over four months. You want to highlight the highest sales point using an arrow annotation to make it clear to your audience.

🎯 Goal: Build a line plot of monthly sales and add an arrow annotation pointing to the highest sales value with a label.

📋 What You'll Learn

Create a list called months with values: 'Jan', 'Feb', 'Mar', 'Apr'

Create a list called sales with values: 150, 200, 250, 225

Create a variable called max_sales that stores the highest sales value

Create a variable called max_month that stores the month with the highest sales

Plot the sales data as a line plot with markers

Add an arrow annotation pointing to the highest sales point with the text 'Highest Sales'

Display the plot

💡 Why This Matters

🌍 Real World

Arrow annotations help highlight important data points in charts, making reports and presentations clearer and more engaging.

💼 Career

Data analysts and scientists often use annotations in visualizations to communicate insights effectively to stakeholders.

1

Create the sales data lists

Create a list called months with the values 'Jan', 'Feb', 'Mar', 'Apr'. Then create a list called sales with the values 150, 200, 250, 225.

Matplotlib

# Create the months list and sales list
# Your code here

Need a hint?

Use square brackets to create lists. Separate items with commas.

2

Find the highest sales and corresponding month

Create a variable called max_sales that stores the highest value in the sales list. Create a variable called max_month that stores the month from months that corresponds to max_sales.

Matplotlib

months = ['Jan', 'Feb', 'Mar', 'Apr']
sales = [150, 200, 250, 225]
# Find max_sales and max_month
# Your code here

Need a hint?

Use the max() function to find the highest sales. Use list.index() to find the position of that value.

3

Plot the sales data with markers

Import matplotlib.pyplot as plt. Use plt.plot() to plot months on the x-axis and sales on the y-axis with markers. Use marker='o' to show points.

Matplotlib

import matplotlib.pyplot as plt

months = ['Jan', 'Feb', 'Mar', 'Apr']
sales = [150, 200, 250, 225]
max_sales = max(sales)
max_month = months[sales.index(max_sales)]

# Plot months vs sales with markers
# Your code here

Need a hint?

Use plt.plot() with marker='o' to show dots on the line.

4

Add arrow annotation and display the plot

Use plt.annotate() to add the text 'Highest Sales' pointing to the highest sales point. Use xy=(max_month, max_sales) for the arrow tip and xytext=('Mar', 180) for the text position. Use arrowprops=dict(arrowstyle='->') to draw the arrow. Finally, use plt.show() to display the plot.

Matplotlib

import matplotlib.pyplot as plt

months = ['Jan', 'Feb', 'Mar', 'Apr']
sales = [150, 200, 250, 225]
max_sales = max(sales)
max_month = months[sales.index(max_sales)]

plt.plot(months, sales, marker='o')

# Add arrow annotation pointing to highest sales
# Display the plot
# Your code here

Need a hint?

Use plt.annotate() with xy for the arrow tip and xytext for the label position. Use arrowprops to draw the arrow.