Text annotations in Matplotlib - Mini Project: Build & Apply

Text Annotations with Matplotlib

📖 Scenario: Imagine you are analyzing sales data for a small store. You want to create a simple line chart showing sales over a week and add notes to highlight important days.

🎯 Goal: Build a line chart using matplotlib that shows sales data for 7 days. Add text annotations to highlight the highest and lowest sales days.

📋 What You'll Learn

Create a list called sales with exact values for 7 days

Create a list called days with day names from Monday to Sunday

Add a variable called max_sales to store the highest sales value

Add a variable called min_sales to store the lowest sales value

Use plt.plot() to draw the sales line chart

Use plt.annotate() to add text annotations for highest and lowest sales

Print the plot with plt.show()

💡 Why This Matters

🌍 Real World

Text annotations help highlight key points in charts, making data easier to understand for reports or presentations.

💼 Career

Data analysts and scientists often use annotations to explain trends or outliers in their visualizations.

1

Create sales and days data

Create a list called sales with these exact values: [150, 200, 170, 220, 180, 160, 210]. Also create a list called days with these exact strings: ["Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday"].

Matplotlib

# Create the sales and days lists below
# Your code here

Hint

Use square brackets to create lists. Make sure the values and strings match exactly.

2

Find highest and lowest sales values

Create a variable called max_sales and set it to the maximum value in the sales list. Create another variable called min_sales and set it to the minimum value in the sales list.

Matplotlib

sales = [150, 200, 170, 220, 180, 160, 210]
days = ["Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday"]
# Find max_sales and min_sales below
# Your code here

Hint

Use the max() and min() functions on the sales list.

3

Plot sales data and add annotations

Import matplotlib.pyplot as plt. Use plt.plot() to plot days on the x-axis and sales on the y-axis. Use plt.annotate() twice: once to label the highest sales point with text 'Highest Sales' and once to label the lowest sales point with text 'Lowest Sales'. Use the exact variables max_sales and min_sales to find the y-values. Use sales.index(max_sales) and sales.index(min_sales) to find the x positions.

Matplotlib

import matplotlib.pyplot as plt

sales = [150, 200, 170, 220, 180, 160, 210]
days = ["Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday"]
max_sales = max(sales)
min_sales = min(sales)

# Plot the sales line chart
# Add annotations for highest and lowest sales
# Your code here

Hint

Use plt.plot() with days and sales. Use plt.annotate() with xy for the point and xytext for the label position. Add arrows with arrowprops.

4

Display the plot

Use plt.show() to display the plot with the sales line and annotations.

Matplotlib

import matplotlib.pyplot as plt

sales = [150, 200, 170, 220, 180, 160, 210]
days = ["Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday"]
max_sales = max(sales)
min_sales = min(sales)

plt.plot(days, sales, marker='o')
plt.annotate('Highest Sales', xy=(days[sales.index(max_sales)], max_sales), xytext=(days[sales.index(max_sales)], max_sales + 10), arrowprops=dict(facecolor='green', shrink=0.05))
plt.annotate('Lowest Sales', xy=(days[sales.index(min_sales)], min_sales), xytext=(days[sales.index(min_sales)], min_sales - 20), arrowprops=dict(facecolor='red', shrink=0.05))

# Display the plot below
# Your code here

Hint

Just call plt.show() to display the plot window.

Practice

1. What is the main purpose of adding text annotations in a matplotlib plot?

easy

A. To add labels or notes that explain or highlight data points

B. To change the color of the plot lines

C. To increase the size of the plot window

D. To save the plot as an image file

Solution

1. Step 1: Understand what text annotations do

   Text annotations add extra information like labels or notes on specific parts of a plot.

2. Step 2: Identify the correct purpose

   Changing colors or saving files are unrelated to annotations, which focus on explaining or highlighting data points.

3. Final Answer:

   To add labels or notes that explain or highlight data points -> Option A

4. Quick Check:

   Annotations = labels/notes [OK]

Hint: Annotations explain data points clearly on plots [OK]

Common Mistakes:

• Confusing annotations with plot styling
• Thinking annotations save or export plots
• Assuming annotations change plot size

2. Which of the following is the correct syntax to add a text annotation at point (2, 3) with the text 'Peak' in matplotlib?

easy

A. plt.annotate(xy=(2, 3), text='Peak')

B. plt.text('Peak', xy=(2, 3))

C. plt.annotate('Peak', xy=(2, 3))

D. plt.text(x=2, y=3, label='Peak')

Solution

1. Step 1: Recall the correct function and parameter order

   The function plt.annotate takes the text first, then the xy coordinate as a tuple.

2. Step 2: Check each option

   plt.annotate('Peak', xy=(2, 3)) uses plt.annotate('Peak', xy=(2, 3)) which is correct. Others misuse parameter names or functions.

3. Final Answer:

   plt.annotate('Peak', xy=(2, 3)) -> Option C

4. Quick Check:

   annotate(text, xy=point) = correct syntax [OK]

Hint: Use plt.annotate('text', xy=(x,y)) for annotations [OK]

Common Mistakes:

• Swapping text and xy parameters
• Using plt.text with wrong arguments
• Incorrect parameter names like label or text=

3. What will the following code display?

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

medium

A. A line plot with an annotation 'Max' at point (3,6) with an arrow pointing from (2,5)

B. A line plot with text 'Max' at (2,5) but no arrow

C. A line plot with an annotation 'Max' at (2,5) without arrow

D. Syntax error due to incorrect arrowprops usage

Solution

1. Step 1: Understand plt.annotate parameters

   xy is the point to annotate (3,6), xytext is where the text appears (2,5), arrowprops adds an arrow from text to point.

2. Step 2: Analyze the code output

   The plot shows a line, with 'Max' text at (2,5) and an arrow pointing to (3,6).

3. Final Answer:

   A line plot with an annotation 'Max' at point (3,6) with an arrow pointing from (2,5) -> Option A

4. Quick Check:

   annotate with xy, xytext, arrowprops = arrowed label [OK]

Hint: xy=point, xytext=text location, arrowprops=arrow [OK]

Common Mistakes:

• Confusing xy and xytext roles
• Expecting arrow without arrowprops
• Thinking arrowprops causes syntax error

4. Identify the error in this code snippet:

import matplotlib.pyplot as plt
plt.plot([1, 2, 3], [4, 5, 6])
plt.annotate('High', (3, 6), xytext=(2, 5), arrowprops='black')
plt.show()

medium

A. plt.plot arguments are incorrect

B. arrowprops should be a dictionary, not a string

C. The text 'High' should be passed as xytext

D. xytext parameter is missing

Solution

1. Step 1: Check arrowprops usage

   arrowprops must be a dictionary specifying arrow style, not a string.

2. Step 2: Verify other parameters

   xytext is present, text is first argument, plot args are correct.

3. Final Answer:

   arrowprops should be a dictionary, not a string -> Option B

4. Quick Check:

   arrowprops = dict(...) not string [OK]

Hint: arrowprops needs dict with arrow style, not string [OK]

Common Mistakes:

• Passing arrowprops as string
• Confusing text and xytext parameters
• Incorrect plot data format

5. You want to highlight the lowest point on a plot with an annotation that includes an arrow and custom text offset. Which code snippet correctly achieves this for data points x=[1,2,3], y=[5,3,6]?

hard

A. plt.annotate('Lowest', xy=(2, 3), xytext=(2, 3), arrowprops=dict(color='blue'))

B. plt.annotate('Lowest', xytext=(2, 3), xy=(1, 4), arrowprops='red')

C. plt.text('Lowest', xy=(2, 3), xytext=(1, 4), arrowprops=dict(facecolor='red'))

D. plt.annotate('Lowest', xy=(2, 3), xytext=(1, 4), arrowprops=dict(facecolor='red'))

Solution

1. Step 1: Identify the lowest point coordinates

   Lowest y is 3 at x=2, so xy=(2,3) is correct.

2. Step 2: Check annotation parameters

   xytext=(1,4) offsets text for clarity, arrowprops uses dict with facecolor for arrow color.

3. Step 3: Validate options

   plt.annotate('Lowest', xy=(2, 3), xytext=(1, 4), arrowprops=dict(facecolor='red')) matches correct syntax and logic. Others misuse parameters or functions.

4. Final Answer:

   plt.annotate('Lowest', xy=(2, 3), xytext=(1, 4), arrowprops=dict(facecolor='red')) -> Option D

5. Quick Check:

   Correct xy, xytext, arrowprops dict = plt.annotate('Lowest', xy=(2, 3), xytext=(1, 4), arrowprops=dict(facecolor='red')) [OK]

Hint: Use xy for point, xytext for label offset, arrowprops dict [OK]

Common Mistakes:

• Swapping xy and xytext
• Using plt.text instead of plt.annotate
• Passing arrowprops as string