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

Concept Flow - Axes vs pyplot interface comparison

Start

↓

Choose Interface

↓

pyplot Interface

↓

Use plt.plot()

↓

Figure & Axes auto-created

↓

Show plot with plt.show()

↓

Axes Interface

↓

Create Figure & Axes explicitly

↓

Use ax.plot() on Axes object

↓

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.

Practice

1. Which statement best describes the difference between the pyplot interface and the Axes interface in matplotlib?

easy

A. Axes is simpler and good for quick plots, while pyplot offers more control for complex figures.

B. pyplot is simpler and good for quick plots, while Axes offers more control for complex figures.

C. Both pyplot and Axes interfaces are equally simple and offer the same control.

D. pyplot is only used for 3D plots, while Axes is for 2D plots.

Solution

1. Step 1: Understand pyplot interface

   The pyplot interface is designed for quick and easy plotting with simple commands.

2. Step 2: Understand Axes interface

   The Axes interface provides detailed control over plot elements, useful for complex figures.

3. Final Answer:

   pyplot is simpler and good for quick plots, while Axes offers more control for complex figures. -> Option B

4. Quick Check:

   Interface complexity = pyplot simple, Axes detailed [OK]

Hint: Remember: pyplot = quick, Axes = control [OK]

Common Mistakes:

• Confusing which interface is simpler
• Thinking both interfaces have same control level
• Assuming pyplot is only for 3D plots

2. Which of the following is the correct way to create a figure and axes using the Axes interface?

easy

A. fig, ax = plt.subplots()

B. ax = plt.figure()

C. fig = plt.axes()

D. plt.plot(), ax = plt.figure()

Solution

1. Step 1: Recall syntax for creating figure and axes

   The correct syntax to create a figure and axes object is fig, ax = plt.subplots().

2. Step 2: Check other options

   plt.figure() creates only a figure, plt.axes() creates axes but not figure, and plt.plot() is for plotting, not creating axes.

3. Final Answer:

   fig, ax = plt.subplots() -> Option A

4. Quick Check:

   Correct Axes creation = plt.subplots() [OK]

Hint: Use plt.subplots() to get figure and axes together [OK]

Common Mistakes:

• Using plt.figure() expecting axes returned
• Confusing plt.axes() with plt.figure()
• Trying to assign plt.plot() to axes

3. What will be the output of this code snippet?

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

medium

A. A plot without title because plt.title() affects only pyplot interface.

B. An error because plt.title() cannot be used with Axes interface.

C. A blank figure with no plot or title.

D. A plot with line connecting points (1,4), (2,5), (3,6) and title 'My Plot'.

Solution

1. Step 1: Understand plotting with Axes

   The ax.plot() draws the line on the axes object.

2. Step 2: Understand plt.title() effect

   plt.title() sets the title on the current axes, so it works here.

3. Final Answer:

   A plot with line connecting points (1,4), (2,5), (3,6) and title 'My Plot'. -> Option D

4. Quick Check:

   Axes plot + plt.title() = plot with title [OK]

Hint: plt.title() sets title on current axes even with Axes interface [OK]

Common Mistakes:

• Thinking plt.title() won't work with Axes interface
• Expecting error due to mixing interfaces
• Assuming no plot will show

4. Identify the error in this code using the Axes interface:

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

medium

A. fig, ax = plt.subplots() is incorrect syntax.

B. ax.set_title() is invalid; should use plt.title() instead.

C. Using plt.plot() instead of ax.plot() causes the plot to appear on a different axes.

D. plt.show() is missing and causes no output.

Solution

1. Step 1: Check plotting method

   plt.plot() plots on the current pyplot axes, not the ax created by plt.subplots().

2. Step 2: Check title setting

   ax.set_title() correctly sets the title on the ax axes.

3. Final Answer:

   Using plt.plot() instead of ax.plot() causes the plot to appear on a different axes. -> Option C

4. Quick Check:

   Plotting on wrong axes = plt.plot() vs ax.plot() [OK]

Hint: Use ax.plot() to plot on specific axes, not plt.plot() [OK]

Common Mistakes:

• Confusing plt.plot() and ax.plot()
• Thinking ax.set_title() is invalid
• Missing plt.show() causing no output

5. You want to create a figure with two side-by-side plots sharing the same y-axis. Which approach using the Axes interface is best?

hard

A. Use fig, (ax1, ax2) = plt.subplots(1, 2, sharey=True) and plot on ax1 and ax2.

B. Call plt.plot() twice and then set plt.sharey(True).

C. Create two separate figures with plt.figure() and plot independently.

D. Use fig, ax = plt.subplots() and plot both lines on the same axes.

Solution

1. Step 1: Understand subplot creation with shared axis

   plt.subplots(1, 2, sharey=True) creates two axes side-by-side sharing the y-axis.

2. Step 2: Plot on each axes separately

   Plotting on ax1 and ax2 allows independent x-data but shared y-axis.

3. Final Answer:

   Use fig, (ax1, ax2) = plt.subplots(1, 2, sharey=True) and plot on ax1 and ax2. -> Option A

4. Quick Check:

   Shared y-axis subplots = plt.subplots with sharey=True [OK]

Hint: Use plt.subplots with sharey=True for shared y-axis plots [OK]

Common Mistakes:

• Trying to share axis with plt.plot() only
• Creating separate figures instead of subplots
• Plotting both lines on one axes when separate plots needed