3D axes with projection='3d' in Matplotlib - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of 3D scatter plot code

What will be the output of this code snippet that creates a 3D scatter plot using matplotlib?

Matplotlib

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

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

x = np.array([1, 2, 3])
y = np.array([4, 5, 6])
z = np.array([7, 8, 9])

ax.scatter(x, y, z)
plt.show()

A A 2D scatter plot with points at (1,4), (2,5), and (3,6) ignoring z values

B A 3D scatter plot with points at coordinates (1,4,7), (2,5,8), and (3,6,9) displayed

C SyntaxError due to incorrect import of Axes3D

D RuntimeError because projection='3d' is not supported

💡 Hint

Check how the projection='3d' argument affects the plot type.

The code creates a 3D scatter plot with the given x, y, z coordinates. The projection='3d' enables 3D plotting in matplotlib.

❓ data_output

intermediate

Number of plotted points in 3D line plot

How many points will be connected by the line in this 3D plot code?

Matplotlib

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

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

x = np.linspace(0, 1, 5)
y = np.linspace(0, 1, 5)
z = np.linspace(0, 1, 5)

ax.plot(x, y, z)
plt.show()

A 5

B 3

C 1

D 0

💡 Hint

Count the number of points generated by np.linspace.

np.linspace(0,1,5) generates 5 points evenly spaced between 0 and 1. The plot connects these 5 points in 3D space.

🔧 Debug

advanced

Identify the error in 3D scatter plot code

What error will this code produce when run?

Matplotlib

import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

x = [1, 2, 3]
y = [4, 5]
z = [7, 8, 9]

ax.scatter(x, y, z)
plt.show()

A No error; plot displays correctly

B TypeError because lists cannot be used in scatter

C NameError because 'projection' is not a valid argument

D ValueError due to mismatched array lengths

💡 Hint

Check if all coordinate arrays have the same length.

The y list has length 2, while x and z have length 3. This mismatch causes a ValueError when plotting.

❓ visualization

advanced

Effect of changing projection parameter

What visual difference occurs when changing projection='3d' to projection='2d' in this code?

Matplotlib

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

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

x = np.arange(3)
y = np.arange(3)
z = np.arange(3)

ax.plot(x, y, z)
plt.show()

A Changing to projection='2d' causes a TypeError because '2d' is invalid

B Changing to projection='2d' creates a scatter plot instead of a line plot

C Changing to projection='2d' creates a 2D line plot ignoring z values

D Changing to projection='2d' creates a 3D plot with default projection

💡 Hint

Consider how matplotlib handles 2D vs 3D axes.

projection='2d' is not a valid argument; matplotlib defaults to 2D plotting ignoring z values, so the plot is 2D line connecting (x,y).

🧠 Conceptual

expert

Understanding 3D axes creation in matplotlib

Which statement correctly describes how matplotlib creates 3D axes with projection='3d'?

A projection='3d' creates a special Axes3D object that supports 3D plotting methods

B projection='3d' is a style setting that changes colors but keeps 2D axes

C projection='3d' automatically imports mpl_toolkits.mplot3d and adds 3D data support

D projection='3d' converts 2D plots into 3D by adding a z-axis with zeros

💡 Hint

Think about what kind of object is created with projection='3d'.

Setting projection='3d' creates an Axes3D object that has methods for 3D plotting, different from regular 2D axes.