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

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

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

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

Hint

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

Practice

1. What is the main purpose of using plt.annotate() with arrow annotations in matplotlib?

easy

A. To create a new figure window

B. To change the color of the plot lines

C. To save the plot as an image file

D. To highlight and point to specific data points on a plot

Solution

1. Step 1: Understand the role of plt.annotate()

   This function is used to add text annotations to plots, often with arrows pointing to data points.

2. Step 2: Identify the purpose of arrow annotations

   Arrow annotations help visually highlight and point to specific points or areas on the plot for clarity.

3. Final Answer:

   To highlight and point to specific data points on a plot -> Option D

4. Quick Check:

   Arrow annotations = highlight points [OK]

Hint: Annotations with arrows point to important plot spots [OK]

Common Mistakes:

• Confusing annotation with changing plot colors
• Thinking annotation creates new figures
• Assuming annotation saves files

2. Which of the following is the correct syntax to add an arrow annotation pointing to point (2, 3) with text at (3, 4)?

easy

A. plt.annotate('Note', xy=(2, 3), xytext=(3, 4), arrowprops=dict(arrowstyle='->'))

B. plt.annotate('Note', xytext=(2, 3), xy=(3, 4), arrowprops=dict(arrowstyle='->'))

C. plt.annotate('Note', xy=(3, 4), xytext=(2, 3), arrowprops=dict(arrowstyle='->'))

D. plt.annotate('Note', xytext=(3, 4), xy=(2, 3))

Solution

1. Step 1: Recall plt.annotate() parameters

   xy is the point to annotate, xytext is the text location, and arrowprops defines the arrow style.

2. Step 2: Match parameters to the question

   Text at (3,4) means xytext=(3,4), arrow points to (2,3) means xy=(2,3). Arrow style '->' is correct.

3. Final Answer:

   plt.annotate('Note', xy=(2, 3), xytext=(3, 4), arrowprops=dict(arrowstyle='->')) -> Option A

4. Quick Check:

   xy = point, xytext = text [OK]

Hint: Remember: xy=arrow tip, xytext=text location [OK]

Common Mistakes:

• Swapping xy and xytext values
• Omitting arrowprops for arrow display
• Using wrong arrowstyle syntax

3. What will the following code display?

import matplotlib.pyplot as plt
plt.plot([1, 2, 3], [4, 5, 6])
plt.annotate('Peak', xy=(2, 5), xytext=(3, 6), arrowprops=dict(facecolor='red'))
plt.show()

medium

A. Syntax error due to missing arrowstyle in arrowprops

B. A line plot with a red arrow pointing from text at (3,6) to point (2,5) labeled 'Peak'

C. A line plot with no arrows, only text 'Peak' at (2,5)

D. A line plot with a blue arrow pointing from (2,5) to (3,6) labeled 'Peak'

Solution

1. Step 1: Understand the plot and annotation

   The plot draws points (1,4), (2,5), (3,6). Annotation places text at (3,6) with an arrow pointing to (2,5).

2. Step 2: Analyze arrowprops

   Arrow has facecolor='red', so arrow will be red. Arrowstyle defaults to '->' if not specified.

3. Final Answer:

   A line plot with a red arrow pointing from text at (3,6) to point (2,5) labeled 'Peak' -> Option B

4. Quick Check:

   Arrow color red, arrow points to xy [OK]

Hint: Arrow points from xytext to xy with given facecolor [OK]

Common Mistakes:

• Thinking arrow points from xy to xytext
• Assuming default arrow color is blue
• Expecting syntax error without arrowstyle

4. Identify the error in this code snippet:

plt.plot([1, 2, 3], [4, 5, 6])
plt.annotate('Max', xy=(2, 5), xytext=(3, 6), arrowprops={'arrowstyle': '->'})
plt.show()

medium

A. arrowprops should be a dict, but it is given as a list

B. The code is correct and will run without errors

C. Missing import statement for matplotlib.pyplot

D. xy and xytext coordinates are reversed

Solution

1. Step 1: Check code completeness

   The snippet uses plt but does not import matplotlib.pyplot as plt, which causes a NameError.

2. Step 2: Verify arrowprops and coordinates

   arrowprops is correctly a dict, and coordinates are in correct order (xy=point, xytext=text).

3. Final Answer:

   Missing import statement for matplotlib.pyplot -> Option C

4. Quick Check:

   Import missing = error [OK]

Hint: Always import matplotlib.pyplot as plt before plotting [OK]

Common Mistakes:

• Assuming arrowprops must be a list
• Swapping xy and xytext
• Ignoring missing imports

5. You want to annotate multiple points on a scatter plot with arrows pointing from text labels offset by (0.5, 0.5). Which code snippet correctly applies this for points in points = [(1,2), (3,4), (5,6)]?

hard

A. for x, y in points:
plt.annotate(f'({x},{y})', xy=(x, y), xytext=(x+0.5, y+0.5), arrowprops=dict(arrowstyle='->'))

B. for x, y in points:
plt.annotate(f'({x},{y})', xytext=(x, y), xy=(x+0.5, y+0.5), arrowprops=dict(arrowstyle='->'))

C. for x, y in points:
plt.annotate(f'({x},{y})', xy=(x+0.5, y+0.5), xytext=(x, y), arrowprops=dict(arrowstyle='->'))

D. for x, y in points:
plt.annotate(f'({x},{y})', xytext=(x+0.5, y+0.5), xy=(x, y))

Solution

1. Step 1: Understand annotation parameters for multiple points

   Text should be offset by (0.5, 0.5) from each point, so xytext=(x+0.5, y+0.5) and arrow points to xy=(x, y).

2. Step 2: Check arrowprops and loop structure

   Arrow style '->' is correct, and loop correctly iterates over points unpacking x and y.

3. Final Answer:

   for x, y in points: plt.annotate(f'({x},{y})', xy=(x, y), xytext=(x+0.5, y+0.5), arrowprops=dict(arrowstyle='->')) -> Option A

4. Quick Check:

   xy = point, xytext = offset text [OK]

Hint: xy is point, xytext is offset text location [OK]

Common Mistakes:

• Swapping xy and xytext causing arrows to point wrong way
• Omitting arrowprops so no arrow appears
• Not unpacking points correctly in loop