3D scatter plots in Matplotlib - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of 3D scatter plot with color mapping

What will be the color of the point at coordinates (2, 3, 4) in the 3D scatter plot generated by the code below?

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 = [1, 2, 3]
y = [2, 3, 4]
z = [3, 4, 5]
colors = ['red', 'green', 'blue']

scatter = ax.scatter(x, y, z, c=colors)
plt.show()

A Yellow

B Green

C Blue

D Red

💡 Hint

Colors are assigned in order to the points based on the list provided.

The second point has coordinates (2, 3, 4) and the color list assigns 'green' to the second point.

❓ data_output

intermediate

Number of points plotted in 3D scatter plot

How many points will be plotted by the following 3D scatter 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, 10)
y = np.linspace(0, 1, 10)
z = np.linspace(0, 1, 10)

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

A 1

B 1000

C 30

D 10

💡 Hint

The scatter plot plots points for each index in the arrays.

Each array has 10 points, and scatter plots points pairwise by index, so 10 points are plotted.

❓ visualization

advanced

Effect of marker size on 3D scatter plot

Which option shows the correct effect of changing marker size in a 3D scatter plot?

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([2, 3, 4])
z = np.array([3, 4, 5])

ax.scatter(x, y, z, s=100)
plt.show()

A Points appear larger than default size

B Points are connected by lines

C Points are invisible

D Points appear smaller than default size

💡 Hint

The 's' parameter controls marker size in scatter plots.

Setting s=100 increases marker size making points larger than default.

🔧 Debug

advanced

Identify the error in 3D scatter plot code

What error will the following code produce when run?

Matplotlib

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

fig = plt.figure()
ax = fig.add_subplot(111)

x = [1, 2, 3]
y = [4, 5, 6]
z = [7, 8, 9]

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

A No error, plot displays correctly

B AttributeError: 'AxesSubplot' object has no attribute 'scatter'

C TypeError: scatter() missing 1 required positional argument: 'zs'

D ValueError: x, y, and z must be the same length

💡 Hint

Check if the subplot is created with 3D projection.

The subplot is created without 3D projection, so scatter expects only x and y, but z is given causing TypeError.

🚀 Application

expert

Interpreting clustering from 3D scatter plot data

Given the 3D scatter plot data below, which cluster center is closest to the point (5, 5, 5)?

Matplotlib

import numpy as np

points = np.array([[1, 2, 3], [5, 5, 5], [9, 8, 7]])
cluster_centers = np.array([[0, 0, 0], [5, 5, 6], [10, 10, 10]])

# Calculate distances from point (5,5,5) to each cluster center
point = np.array([5, 5, 5])
distances = np.linalg.norm(cluster_centers - point, axis=1)
closest_index = np.argmin(distances)
closest_center = cluster_centers[closest_index]
closest_center

A [5 5 6]

B [0 0 0]

C [10 10 10]

D [1 2 3]

💡 Hint

Distance is shortest between points closest in all three dimensions.

The cluster center [5, 5, 6] is closest to point [5, 5, 5] with distance 1, less than others.