Figure creation with plt.figure in Matplotlib - Time & Space Complexity

Time Complexity: Figure creation with plt.figure

O(n)

Understanding Time Complexity

When we create a figure using plt.figure(), it takes some time to set up the drawing space.

We want to know how this setup time changes as we create more figures.

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

import matplotlib.pyplot as plt

for i in range(n):
    fig = plt.figure()
    plt.close(fig)

This code creates and closes n figures one after another.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Creating a figure with plt.figure() inside a loop.
• How many times: Exactly n times, once per loop iteration.

How Execution Grows With Input

Each figure creation takes roughly the same time, so total time grows directly with n.

Input Size (n)	Approx. Operations
10	10 figure creations
100	100 figure creations
1000	1000 figure creations

Pattern observation: Doubling n doubles the total work.

Final Time Complexity

Time Complexity: O(n)

This means the time to create n figures grows in a straight line as n increases.

Common Mistake

[X] Wrong: "Creating multiple figures at once is instant and does not add up."

[OK] Correct: Each figure requires setup, so time adds up linearly with the number of figures.

Interview Connect

Understanding how repeated figure creation scales helps you reason about performance in data visualization tasks.

Self-Check

What if we reused the same figure instead of creating a new one each time? How would the time complexity change?