Broken axes concept in Matplotlib - Step-by-Step Execution

Concept Flow - Broken axes concept

Start: Prepare data

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Create figure and axes

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Plot data on first axis

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Plot data on second axis

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Hide spines and ticks between axes

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Add diagonal lines to show break

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Show combined plot with broken axes

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End

This flow shows how to create a plot with broken axes by preparing data, plotting on two axes, hiding the break area, and adding diagonal lines to indicate the break.

Execution Sample

Matplotlib

import matplotlib.pyplot as plt
fig, (ax1, ax2) = plt.subplots(1, 2, sharey=True)
ax1.plot([1, 2, 3], [10, 20, 30])
ax2.plot([1, 2, 3], [100, 200, 300])
plt.show()

This code creates two side-by-side plots sharing the y-axis to simulate broken axes.

Execution Table

Step	Action	Axes State	Plot Data	Visual Result
1	Import matplotlib.pyplot as plt	No axes created	No data plotted	No plot yet
2	Create figure and two subplots sharing y-axis	Two axes: ax1 and ax2 created side by side	No data plotted	Empty figure with two axes
3	Plot data [10,20,30] on ax1	ax1 ready	Line plot on ax1 with y=[10,20,30]	Left plot shows small y values
4	Plot data [100,200,300] on ax2	ax2 ready	Line plot on ax2 with y=[100,200,300]	Right plot shows large y values
5	Hide spines and ticks between ax1 and ax2	Axes spines adjusted	No new data	Gap between plots looks like broken axis
6	Add diagonal lines on break	Decorations added	No new data	Visual break lines appear between axes
7	Show plot	Final state	Both plots visible	Combined plot with broken y-axis shown
8	End	Plot window open	Data displayed	User sees broken axes plot

💡 Plot displayed with two axes showing different y ranges to simulate broken axes.

Variable Tracker

Variable	Start	After Step 2	After Step 3	After Step 4	After Step 5	After Step 6	Final
fig	None	Figure object created	Figure unchanged	Figure unchanged	Figure unchanged	Figure unchanged	Figure unchanged
ax1	None	Axes object created	Line plotted with y=[10,20,30]	Line plotted	Spines hidden on right	Diagonal lines added	Final broken axes left plot
ax2	None	Axes object created	No plot	Line plotted with y=[100,200,300]	Spines hidden on left	Diagonal lines added	Final broken axes right plot

Key Moments - 3 Insights

Why do we create two separate axes instead of one?

We create two axes to show different y-axis ranges side by side, which simulates a broken axis effect. This is shown in execution_table steps 2, 3, and 4 where each axis plots different y data.

How do diagonal lines indicate the axis break?

Diagonal lines are drawn between the two axes to visually signal the break in the axis scale. This is done after hiding spines (step 6) and helps users understand the axis is discontinuous.

Why do we share the y-axis between the two plots?

Sharing the y-axis aligns the two plots vertically so the broken axis looks continuous except for the break. This is set in step 2 with sharey=True.

Visual Quiz - 3 Questions

Look at the execution table at step 4. What data is plotted on ax2?

A [10, 20, 30]

B [100, 200, 300]

C [1, 2, 3]

D No data plotted yet

💡 Hint

Check the 'Plot Data' column in row for step 4 in execution_table.

At which step do we add diagonal lines to show the axis break?

A Step 6

B Step 5

C Step 3

D Step 7

💡 Hint

Look at the 'Action' column for the step mentioning diagonal lines in execution_table.

If we do not share the y-axis (remove sharey=True), what changes in the plot?

A Plots will merge into one

B Diagonal lines will not appear

C Axes will not align vertically, making the broken axis effect less clear

D Data will not plot

💡 Hint

Refer to key_moments about why sharey=True is used.

Concept Snapshot

Broken axes concept in matplotlib:
- Create two subplots side by side with sharey=True
- Plot different y ranges on each axis
- Hide spines and ticks between axes
- Add diagonal lines to indicate axis break
- Show combined plot simulating a broken axis

Full Transcript

This visual execution shows how to create a broken axes plot in matplotlib. First, we import matplotlib and create a figure with two subplots side by side sharing the y-axis. We plot smaller y values on the left axis and larger y values on the right axis. Then, we hide the spines and ticks between the two axes to create a visual gap. Diagonal lines are added between the axes to indicate the break in the axis scale. Finally, the combined plot is shown, allowing viewers to see data with a discontinuous y-axis. This technique helps display data with very different scales clearly.