3D scatter plots in Matplotlib - Mini Project: Build & Apply

3D Scatter Plots

📖 Scenario: You are a data analyst working with a dataset of points in 3D space. You want to visualize these points to understand their distribution and relationships.

🎯 Goal: Create a 3D scatter plot using matplotlib to visualize the points in three dimensions.

📋 What You'll Learn

Create three lists named x, y, and z with the exact values provided.

Create a variable color to specify the color of the points.

Use matplotlib to create a 3D scatter plot with the given data and color.

Display the plot using plt.show().

💡 Why This Matters

🌍 Real World

3D scatter plots help scientists and engineers visualize data points in three dimensions, such as geographic locations, sensor data, or experimental results.

💼 Career

Data analysts and data scientists use 3D scatter plots to explore complex datasets and communicate insights visually to teams and stakeholders.

1

Create the 3D data points

Create three lists called x, y, and z with these exact values: x = [5, 7, 8, 7, 2, 17, 2, 9, 4, 11], y = [99, 86, 87, 88, 100, 86, 103, 87, 94, 78], and z = [10, 15, 13, 15, 10, 15, 10, 15, 10, 15].

Matplotlib

# Create lists x, y, and z with the given values
# Your code here

Need a hint?

Use square brackets to create lists and separate numbers with commas.

2

Set the color for the points

Create a variable called color and set it to the string 'green' to specify the color of the scatter points.

Matplotlib

x = [5, 7, 8, 7, 2, 17, 2, 9, 4, 11]
y = [99, 86, 87, 88, 100, 86, 103, 87, 94, 78]
z = [10, 15, 13, 15, 10, 15, 10, 15, 10, 15]
# Create a variable color and set it to 'green'
# Your code here

Need a hint?

Assign the string 'green' to the variable color using the equals sign.

3

Create the 3D scatter plot

Import matplotlib.pyplot as plt and Axes3D from mpl_toolkits.mplot3d. Then create a figure and add a 3D subplot. Use ax.scatter(x, y, z, c=color) to create the 3D scatter plot with the data and color.

Matplotlib

x = [5, 7, 8, 7, 2, 17, 2, 9, 4, 11]
y = [99, 86, 87, 88, 100, 86, 103, 87, 94, 78]
z = [10, 15, 13, 15, 10, 15, 10, 15, 10, 15]
color = 'green'
# Import matplotlib.pyplot as plt and Axes3D
# Create a figure and add a 3D subplot
# Use ax.scatter(x, y, z, c=color) to plot
# Your code here

Need a hint?

Use plt.figure() to create a figure and fig.add_subplot(111, projection='3d') to add a 3D plot.

4

Display the 3D scatter plot

Use plt.show() to display the 3D scatter plot.

Matplotlib

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

x = [5, 7, 8, 7, 2, 17, 2, 9, 4, 11]
y = [99, 86, 87, 88, 100, 86, 103, 87, 94, 78]
z = [10, 15, 13, 15, 10, 15, 10, 15, 10, 15]
color = 'green'

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.scatter(x, y, z, c=color)
# Display the plot
# Your code here

Need a hint?

Call plt.show() to open the plot window.