Axes vs pyplot interface comparison in Matplotlib - Visual Side-by-Side Comparison

Concept Flow - Axes vs pyplot interface comparison

Start

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Choose Interface

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pyplot Interface

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Use plt.plot()

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Figure & Axes auto-created

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Show plot with plt.show()

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Axes Interface

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Create Figure & Axes explicitly

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Use ax.plot() on Axes object

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Show plot with plt.show()

You start by choosing either pyplot or Axes interface. Pyplot auto-creates figure and axes, while Axes requires explicit creation. Both end with showing the plot.

Execution Sample

Matplotlib

import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.plot([1, 2, 3], [4, 5, 6])
plt.show()

This code uses the Axes interface: it creates a figure and axes, plots data on the axes, then shows the plot.

Execution Table

Step	Action	Object Created/Used	Effect/Output
1	Call plt.subplots()	Figure and Axes objects	Figure and Axes created explicitly
2	Call ax.plot([1,2,3], [4,5,6])	Axes object	Line plotted on Axes
3	Call plt.show()	Figure window	Plot window displayed
4	End	-	Plotting complete

💡 Plot displayed and program ends

Variable Tracker

Variable	Start	After plt.subplots()	After ax.plot()	Final
fig	None	Figure object	Figure object	Figure object
ax	None	Axes object	Axes with line plotted	Axes with line plotted

Key Moments - 2 Insights

Why do we need to create Figure and Axes explicitly in the Axes interface?

Because unlike pyplot interface which creates them automatically, the Axes interface requires you to create Figure and Axes objects to have control over where to plot. See execution_table step 1.

Can we plot multiple lines using pyplot interface without creating Axes?

Yes, pyplot manages Figure and Axes internally, so you can call plt.plot() multiple times and it will plot on the current Axes. This is different from Axes interface where you call plot on specific Axes.

Visual Quiz - 3 Questions

Look at the execution_table, what objects are created by plt.subplots()?

A Only Figure object

B Only Axes object

C Both Figure and Axes objects

D No objects created

💡 Hint

See execution_table row 1 under 'Object Created/Used'

At which step is the line actually drawn on the plot in the execution_table?

A Step 2

B Step 1

C Step 3

D Step 4

💡 Hint

Look at execution_table row 2 under 'Effect/Output'

If you use pyplot interface and call plt.plot() twice, what happens?

A Two separate figures are created

B Two lines are plotted on the same Axes

C Only the last line is shown

D An error occurs

💡 Hint

Recall pyplot interface auto-manages Axes and plots on current Axes

Concept Snapshot

Axes vs pyplot interface comparison:
- Pyplot interface auto-creates Figure and Axes.
- Use plt.plot() to plot directly.
- Axes interface requires explicit creation: fig, ax = plt.subplots().
- Plot on Axes with ax.plot().
- Both end with plt.show() to display.
- Axes interface gives more control over plots.

Full Transcript

This lesson compares the two main ways to plot in matplotlib: the pyplot interface and the Axes interface. The pyplot interface is simple and quick. It automatically creates a figure and axes for you. You just call plt.plot() to draw lines. The Axes interface requires you to create the figure and axes objects explicitly using plt.subplots(). Then you call ax.plot() on the axes object to draw lines. Both methods end by calling plt.show() to display the plot window. The Axes interface gives you more control because you can manage multiple axes and figures easily. The execution table shows step-by-step what happens: first creating figure and axes, then plotting lines, then showing the plot. The variable tracker shows how the fig and ax variables change during execution. Key moments clarify why explicit creation is needed in the Axes interface and how pyplot manages axes automatically. The quiz tests understanding of object creation and plotting steps. The snapshot summarizes the differences clearly.