3D axes with projection='3d' in Matplotlib - Step-by-Step Execution

Concept Flow - 3D axes with projection='3d'

Import matplotlib and mpl_toolkits

↓

Create figure object

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Add 3D subplot with projection='3d'

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Plot 3D data points or lines

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Show the 3D plot window

This flow shows how to create a 3D plot by importing libraries, creating a figure, adding a 3D axis, plotting data, and displaying the plot.

Execution Sample

Matplotlib

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.scatter([1,2,3], [4,5,6], [7,8,9])
plt.show()

This code creates a 3D scatter plot with three points in 3D space and displays it.

Execution Table

Step	Action	Evaluation	Result
1	Import matplotlib.pyplot as plt	Success	plt module ready
2	Import Axes3D from mpl_toolkits.mplot3d	Success	3D plotting tools ready
3	Create figure object with plt.figure()	Success	Figure object created
4	Add 3D subplot with fig.add_subplot(111, projection='3d')	Success	3D Axes object created
5	Plot points with ax.scatter([1,2,3], [4,5,6], [7,8,9])	Success	3D scatter points added
6	Call plt.show()	Success	3D plot window displayed
7	End of script	No more code	Execution stops

💡 All steps completed, 3D plot displayed and script ends

Variable Tracker

Variable	Start	After Step 3	After Step 4	After Step 5	Final
plt	Not imported	Imported	Imported	Imported	Imported
fig	None	Figure object	Figure object	Figure object	Figure object
ax	None	None	3D Axes object	3D Axes with scatter points	3D Axes with scatter points

Key Moments - 2 Insights

Why do we need to specify projection='3d' when adding the subplot?

Without projection='3d', matplotlib creates a 2D axis. The execution_table row 4 shows that adding the subplot with projection='3d' creates a 3D Axes object needed for 3D plotting.

What does ax.scatter do in 3D plotting?

In execution_table row 5, ax.scatter plots points in 3D space using x, y, z coordinates. It adds these points to the 3D Axes object for visualization.

Visual Quiz - 3 Questions

Look at the execution_table at step 4, what type of object is 'ax'?

A Figure object

B 2D Axes object

C 3D Axes object

D Scatter plot object

💡 Hint

Check the 'Result' column at step 4 in execution_table

At which step are the 3D points actually added to the plot?

A Step 3

B Step 5

C Step 4

D Step 6

💡 Hint

Look for the action involving ax.scatter in execution_table

If we omit projection='3d' in step 4, what will happen?

A A 2D plot will be created instead

B A 3D plot will still be created

C An error will occur immediately

D The figure object will not be created

💡 Hint

Refer to key_moments explanation about projection='3d' necessity

Concept Snapshot

Create 3D plots by adding subplot with projection='3d'.
Use ax.scatter(x, y, z) to plot points in 3D.
Always import Axes3D from mpl_toolkits.mplot3d.
Call plt.show() to display the 3D plot window.

Full Transcript

This example shows how to create a 3D plot using matplotlib. First, we import the necessary modules including Axes3D for 3D plotting. Then, we create a figure object. Next, we add a subplot to the figure with projection='3d' to enable 3D plotting. We plot points in 3D space using ax.scatter with x, y, and z coordinates. Finally, we call plt.show() to display the plot window. The key step is specifying projection='3d' when adding the subplot, otherwise the plot will be 2D. The variables plt, fig, and ax change as the code runs, with ax becoming a 3D axes object after step 4 and holding the scatter points after step 5.