3D bar charts in Matplotlib - Mini Project: Build & Apply

3D Bar Charts

📖 Scenario: You work in a small store that sells three types of fruits: apples, bananas, and oranges. You want to show how many fruits were sold in three different months using a 3D bar chart. This will help your team quickly see which fruit sold the most each month.

🎯 Goal: Create a 3D bar chart using matplotlib to display the sales of apples, bananas, and oranges over three months.

📋 What You'll Learn

Create lists for fruit names and months

Create a list of sales numbers for each fruit in each month

Use matplotlib to create a 3D bar chart

Label the axes with fruit names, months, and sales numbers

Display the 3D bar chart

💡 Why This Matters

🌍 Real World

3D bar charts help visualize data with two categories and one numeric value, such as sales over time for different products.

💼 Career

Data analysts and scientists use 3D bar charts to present complex data clearly to stakeholders and decision makers.

1

Create the sales data lists

Create a list called fruits with these exact values: 'Apples', 'Bananas', 'Oranges'. Create a list called months with these exact values: 'January', 'February', 'March'. Create a list called sales with these exact values: [20, 35, 30] for January, [25, 32, 34] for February, and [22, 30, 35] for March. Store these three lists in a variable called sales as a list of lists, where each inner list corresponds to a month.

Matplotlib

# Create the lists fruits, months, and sales with the exact values
# Your code here

Need a hint?

Use three separate lists. The sales list should be a list of lists, each inner list for one month.

2

Set up the 3D plot

Import matplotlib.pyplot as plt and import Axes3D from mpl_toolkits.mplot3d. Create a figure called fig using plt.figure(). Add a 3D subplot to fig and store it in a variable called ax.

Matplotlib

fruits = ['Apples', 'Bananas', 'Oranges']
months = ['January', 'February', 'March']
sales = [[20, 35, 30], [25, 32, 34], [22, 30, 35]]

# Import matplotlib and create a 3D subplot
# Your code here

Need a hint?

Use fig.add_subplot(111, projection='3d') to create the 3D axes.

3

Plot the 3D bars

Use range(len(months)) and range(len(fruits)) to loop over months and fruits. For each month and fruit, use ax.bar3d() to draw a bar. Use the month index for the x position, the fruit index for the y position, and 0 for the z position. Use 0.5 for the width and depth of each bar. Use the sales number for the height. Store the x positions in xpos, y positions in ypos, z positions in zpos, widths in dx, depths in dy, and heights in dz. Use nested for loops with variables i for months and j for fruits.

Matplotlib

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

fruits = ['Apples', 'Bananas', 'Oranges']
months = ['January', 'February', 'March']
sales = [[20, 35, 30], [25, 32, 34], [22, 30, 35]]

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

# Use nested for loops with i for months and j for fruits
# Use ax.bar3d() to plot bars
# Your code here

Need a hint?

Use ax.bar3d() inside nested loops. The height dz is the sales number for month i and fruit j.

4

Label axes and show the plot

Set the x-axis ticks to the month indices and labels to the months list using ax.set_xticks() and ax.set_xticklabels(). Set the y-axis ticks to the fruit indices and labels to the fruits list using ax.set_yticks() and ax.set_yticklabels(). Set the z-axis label to 'Sales' using ax.set_zlabel(). Finally, call plt.show() to display the 3D bar chart.

Matplotlib

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

fruits = ['Apples', 'Bananas', 'Oranges']
months = ['January', 'February', 'March']
sales = [[20, 35, 30], [25, 32, 34], [22, 30, 35]]

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

for i in range(len(months)):
    for j in range(len(fruits)):
        xpos = i
        ypos = j
        zpos = 0
        dx = 0.5
        dy = 0.5
        dz = sales[i][j]
        ax.bar3d(xpos, ypos, zpos, dx, dy, dz)

# Label the axes and show the plot
# Your code here

Need a hint?

Use ax.set_xticks(), ax.set_xticklabels(), ax.set_yticks(), ax.set_yticklabels(), and ax.set_zlabel(). Then call plt.show().