Percentage labels in Matplotlib - Time & Space Complexity

Time Complexity: Percentage labels

O(n)

Understanding Time Complexity

We want to understand how the time needed to add percentage labels in a matplotlib chart changes as the data size grows.

How does the work increase when we add more slices to a pie chart with percentage labels?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

import matplotlib.pyplot as plt

sizes = [10, 20, 30, 40]
labels = ['A', 'B', 'C', 'D']

plt.pie(sizes, labels=labels, autopct='%1.1f%%')
plt.show()

This code creates a pie chart with four slices and shows percentage labels on each slice.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Drawing each slice and calculating its percentage label.
• How many times: Once for each slice in the data list.

How Execution Grows With Input

As the number of slices increases, the work to draw and label each slice grows directly with it.

Input Size (n)	Approx. Operations
10	10 slice drawings and 10 percentage calculations
100	100 slice drawings and 100 percentage calculations
1000	1000 slice drawings and 1000 percentage calculations

Pattern observation: The work grows in a straight line as the number of slices increases.

Final Time Complexity

Time Complexity: O(n)

This means the time to add percentage labels grows directly with the number of slices.

Common Mistake

[X] Wrong: "Adding percentage labels takes the same time no matter how many slices there are."

[OK] Correct: Each slice needs its own label calculated and drawn, so more slices mean more work.

Interview Connect

Understanding how labeling scales helps you explain performance when visualizing larger datasets clearly and confidently.

Self-Check

"What if we added custom labels with complex formatting instead of simple percentages? How would the time complexity change?"

Practice

1. What does the autopct parameter do in plt.pie() when creating a pie chart?

easy

A. It adds percentage labels to each slice of the pie chart.

B. It changes the colors of the pie slices.

C. It sets the title of the pie chart.

D. It adjusts the size of the pie chart.

Solution

1. Step 1: Understand the role of autopct in plt.pie()

   The autopct parameter is used to display the percentage value on each slice of the pie chart.

2. Step 2: Compare with other parameters

   Other parameters like colors or title do not control percentage labels; only autopct does.

3. Final Answer:

   It adds percentage labels to each slice of the pie chart. -> Option A

4. Quick Check:

   autopct = percentage labels [OK]

Hint: Remember autopct shows percentages on pie slices [OK]

Common Mistakes:

• Confusing autopct with color or title parameters
• Thinking autopct changes chart size
• Ignoring autopct and missing percentage labels

2. Which of the following is the correct syntax to show percentages with one decimal place in a pie chart using plt.pie()?

easy

A. plt.pie(data, autopct='%.1f%')

B. plt.pie(data, autopct='%f1.1%')

C. plt.pie(data, autopct='%1.1f%%')

D. plt.pie(data, autopct='%1.f%%')

Solution

1. Step 1: Recall the format string for percentages

   The correct format for one decimal place is '%1.1f%%' where '%1.1f' formats the float and '%%' prints the percent sign.

2. Step 2: Check each option's format

   plt.pie(data, autopct='%1.1f%%') matches the correct format. Options A, B, and D have misplaced or missing percent signs or incorrect format specifiers.

3. Final Answer:

   plt.pie(data, autopct='%1.1f%%') -> Option C

4. Quick Check:

   Format string '%1.1f%%' = correct percentage format [OK]

Hint: Use '%1.1f%%' to show one decimal percent [OK]

Common Mistakes:

• Forgetting to double the percent sign '%%'
• Misplacing the decimal point in format
• Using incorrect format specifiers like '%f1.1%'

3. What will be the output percentages shown on the pie chart slices for the following code?

import matplotlib.pyplot as plt
sizes = [10, 20, 30]
plt.pie(sizes, autopct='%1.0f%%')
plt.show()

medium

A. 10%, 20%, 30%

B. 17%, 33%, 50%

C. 25%, 50%, 75%

D. 33%, 33%, 33%

Solution

1. Step 1: Calculate total and percentages

   Total = 10 + 20 + 30 = 60. Percentages: 10/60=16.67%, 20/60=33.33%, 30/60=50%.

2. Step 2: Apply autopct format '%1.0f%%'

   This rounds percentages to nearest whole number: 17%, 33%, 50%.

3. Final Answer:

   17%, 33%, 50% -> Option B

4. Quick Check:

   Rounded percentages = 17%, 33%, 50% [OK]

Hint: Sum slices, divide each, round with autopct [OK]

Common Mistakes:

• Using raw values instead of percentages
• Not rounding percentages correctly
• Assuming equal slices without calculation

4. Identify the error in this code snippet that tries to add percentage labels to a pie chart:

import matplotlib.pyplot as plt
sizes = [40, 60]
plt.pie(sizes, autopct='%1.1f%')
plt.show()

medium

A. The format string '%1.1f%' is missing an extra percent sign.

B. The sizes list should be a numpy array.

C. plt.show() is missing parentheses.

D. autopct should be set to True instead of a format string.

Solution

1. Step 1: Check the autopct format string

   The format string '%1.1f%' is incorrect because a single '%' is interpreted as a format specifier start, so to print a percent sign, '%%' is needed.

2. Step 2: Verify other parts of the code

   The sizes list can be a list, plt.show() has parentheses, and autopct expects a format string, not True.

3. Final Answer:

   The format string '%1.1f%' is missing an extra percent sign. -> Option A

4. Quick Check:

   Use '%%' to print percent sign in autopct [OK]

Hint: Double percent signs '%%' to show % in autopct [OK]

Common Mistakes:

• Using single '%' instead of '%%' in format string
• Thinking autopct accepts boolean True
• Assuming list must be numpy array

5. You want to create a pie chart with slices labeled by percentage, but only show percentages for slices larger than 20%. Which autopct function below correctly implements this?

hard

A. lambda p: f'{p:.1f}%'

B. lambda p: f'{p:.1f}%' if p < 20 else ''

C. lambda p: f'{p:.0f}%' if p >= 20 else '0%'

D. lambda p: f'{p:.1f}%' if p > 20 else ''

Solution

1. Step 1: Understand the requirement

   Show percentage labels only if slice percentage is greater than 20%, else show nothing.

2. Step 2: Analyze each lambda function

   lambda p: f'{p:.1f}%' if p > 20 else '' returns formatted percentage if p > 20, else empty string. lambda p: f'{p:.1f}%' if p < 20 else '' does the opposite. lambda p: f'{p:.0f}%' if p >= 20 else '0%' shows '0%' for smaller slices, which is not desired. lambda p: f'{p:.1f}%' shows all percentages.

3. Final Answer:

   lambda p: f'{p:.1f}%' if p > 20 else '' -> Option D

4. Quick Check:

   Show label only if p > 20% = lambda p: f'{p:.1f}%' if p > 20 else '' [OK]

Hint: Use lambda with condition to filter percentages [OK]

Common Mistakes:

• Showing percentages for all slices
• Using wrong comparison operator (< instead of >)
• Returning '0%' instead of empty string for small slices