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Broken axes concept in Matplotlib - Time & Space Complexity

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Time Complexity: Broken axes concept
O(n)
Understanding Time Complexity

We want to understand how the time to draw a plot with broken axes changes as the data size grows.

How does matplotlib handle the drawing steps when axes are broken?

Scenario Under Consideration

Analyze the time complexity of the following matplotlib code snippet.

import matplotlib.pyplot as plt
from brokenaxes import brokenaxes

fig = plt.figure(figsize=(6,4))
bax = brokenaxes(ylims=((0, 1), (10, 11)), fig=fig)

x = range(100)
y = [i**2 for i in x]

bax.plot(x, y)
plt.show()

This code creates a plot with two y-axis ranges broken apart and plots 100 points.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

  • Primary operation: Plotting each data point on the broken axes.
  • How many times: Once for each data point (100 times here).
  • Additional operation: Drawing two separate axis areas for the broken y-limits.
How Execution Grows With Input

As the number of points increases, the plotting work grows roughly in direct proportion.

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

Pattern observation: Doubling the data roughly doubles the drawing work.

Final Time Complexity

Time Complexity: O(n)

This means the time to draw grows linearly with the number of points plotted.

Common Mistake

[X] Wrong: "Broken axes make plotting twice as slow no matter what."

[OK] Correct: The extra axes add some fixed overhead, but the main cost depends on how many points you plot, not just the broken axes.

Interview Connect

Understanding how plotting scales helps you explain performance when visualizing large datasets, a useful skill in data science roles.

Self-Check

What if we added more broken axis sections? How would that affect the time complexity?

Practice

(1/5)
1. What is the main purpose of using broken axes in matplotlib plots?
easy
A. To skip unimportant data ranges and focus on key parts
B. To add 3D effects to the plot
C. To change the color scheme automatically
D. To animate the plot over time

Solution

  1. Step 1: Understand the concept of broken axes

    Broken axes are used to skip over parts of the axis where data is not important or has large gaps.
  2. Step 2: Identify the main purpose

    This helps to focus on important data ranges without showing the entire axis continuously.
  3. Final Answer:

    To skip unimportant data ranges and focus on key parts -> Option A
  4. Quick Check:

    Broken axes = skip gaps [OK]
Hint: Broken axes hide gaps to highlight important data [OK]
Common Mistakes:
  • Thinking broken axes add 3D or animation
  • Confusing broken axes with color changes
  • Assuming broken axes zoom in automatically
2. Which of the following is the correct way to import the brokenaxes package to use brokenaxes(...) directly for creating broken axes plots?
easy
A. from brokenaxes import BrokenAxes
B. import brokenaxes as ba
C. from brokenaxes import brokenaxes
D. import matplotlib.brokenaxes as ba

Solution

  1. Step 1: Recall the correct import syntax

    The brokenaxes package provides the brokenaxes function to create broken axes plots.
  2. Step 2: Identify the correct import statement

    The correct way is from brokenaxes import brokenaxes to access the function directly.
  3. Final Answer:

    from brokenaxes import brokenaxes -> Option C
  4. Quick Check:

    Import brokenaxes function = from brokenaxes import brokenaxes [OK]
Hint: Import brokenaxes function directly from brokenaxes [OK]
Common Mistakes:
  • Using capital 'BrokenAxes' instead of 'brokenaxes'
  • Trying to import from matplotlib instead of brokenaxes
  • Using wrong import syntax causing ImportError
3. What will the following code output?
from brokenaxes import brokenaxes
import matplotlib.pyplot as plt

bax = brokenaxes(ylims=((0, 2), (8, 10)))
bax.plot([0, 1, 2, 3], [1, 1.5, 9, 9.5])
plt.show()
medium
A. A plot with y-axis broken between 2 and 8 showing points near 1 and 9
B. A plot with continuous y-axis from 0 to 10
C. An error because ylims must be a single tuple
D. A plot with x-axis broken between 2 and 8

Solution

  1. Step 1: Analyze the ylims parameter

    The ylims=((0, 2), (8, 10)) means the y-axis is broken to show two ranges: 0 to 2 and 8 to 10, skipping 2 to 8.
  2. Step 2: Understand the plotted points

    The y-values are 1, 1.5, 9, and 9.5, which fit into the two visible y-axis ranges.
  3. Final Answer:

    A plot with y-axis broken between 2 and 8 showing points near 1 and 9 -> Option A
  4. Quick Check:

    ylims tuple of ranges = broken y-axis [OK]
Hint: ylims with tuples creates breaks on y-axis [OK]
Common Mistakes:
  • Assuming y-axis is continuous without breaks
  • Confusing x-axis and y-axis breaks
  • Expecting an error from tuple ylims
4. Identify the error in this code snippet that tries to create broken axes:
from brokenaxes import brokenaxes
import matplotlib.pyplot as plt

bax = brokenaxes(xlims=(0, 2), (5, 7))
bax.plot([1, 6], [10, 20])
plt.show()
medium
A. plt.show() must be called before plot
B. plot function requires x and y to be the same length
C. BrokenAxes cannot be used with xlims parameter
D. xlims should be a tuple of tuples, not separate tuples

Solution

  1. Step 1: Check the xlims argument syntax

    The code uses xlims=(0, 2), (5, 7) which is invalid syntax; it should be a single tuple containing tuples like xlims=((0, 2), (5, 7)).
  2. Step 2: Confirm other parts are correct

    The plot call and plt.show() are correct; the error is only in xlims syntax.
  3. Final Answer:

    xlims should be a tuple of tuples, not separate tuples -> Option D
  4. Quick Check:

    xlims syntax = tuple of tuples [OK]
Hint: Use double parentheses for xlims tuple of ranges [OK]
Common Mistakes:
  • Passing multiple tuples without enclosing in one tuple
  • Mixing up xlims and ylims syntax
  • Calling plt.show() too early
5. You have data with y-values clustered around 0-3 and 50-55, with a large gap in between. How would you create a broken y-axis to show both clusters clearly using brokenaxes?
hard
A. Plot two separate figures for each cluster
B. Use ylims=((0, 3), (50, 55)) when creating brokenaxes
C. Use xlims=((0, 3), (50, 55)) to break x-axis instead
D. Use ylims=(0, 55) to show full range without breaks

Solution

  1. Step 1: Identify the axis to break

    The gap is in y-values, so the y-axis needs to be broken to skip the large gap between 3 and 50.
  2. Step 2: Set ylims with two ranges

    Using ylims=((0, 3), (50, 55)) creates a broken y-axis showing both clusters clearly.
  3. Final Answer:

    Use ylims=((0, 3), (50, 55)) when creating brokenaxes -> Option B
  4. Quick Check:

    Broken y-axis = ylims tuple of ranges [OK]
Hint: Set ylims with two ranges to break y-axis gaps [OK]
Common Mistakes:
  • Breaking x-axis instead of y-axis
  • Using single continuous ylims hiding gap
  • Plotting separate figures unnecessarily
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