Basic pie chart with plt.pie in Matplotlib - Time & Space Complexity

Time Complexity: Basic pie chart with plt.pie

O(n)

Understanding Time Complexity

We want to understand how the time to draw a pie chart changes as the data size grows.

How does the number of slices affect the work matplotlib does?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

import matplotlib.pyplot as plt

sizes = [10, 20, 30, 40]
plt.pie(sizes)
plt.show()

This code creates a pie chart with 4 slices representing the sizes given.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Drawing each slice of the pie chart.
• How many times: Once for each slice in the sizes list.

How Execution Grows With Input

As the number of slices increases, matplotlib draws more pieces, so the work grows with the number of slices.

Input Size (n)	Approx. Operations
10	10 drawing steps
100	100 drawing steps
1000	1000 drawing steps

Pattern observation: The work grows directly with the number of slices.

Final Time Complexity

Time Complexity: O(n)

This means the time to draw the pie chart grows linearly with the number of slices.

Common Mistake

[X] Wrong: "Drawing a pie chart always takes the same time no matter how many slices there are."

[OK] Correct: Each slice requires separate drawing work, so more slices mean more work and more time.

Interview Connect

Understanding how drawing steps grow with data size helps you reason about performance in data visualization tasks.

Self-Check

"What if we added labels and exploded slices? How would the time complexity change?"