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

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

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

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

Hint

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

Practice

1. What does a 3D bar chart in matplotlib primarily represent?

easy

A. Data with two position dimensions and one height dimension

B. Only two-dimensional data with color coding

C. A line graph with three lines

D. A pie chart with depth effect

Solution

1. Step 1: Understand the axes in 3D bar charts

   3D bar charts use two axes for position (x and y) and one axis for height (z).

2. Step 2: Identify the data representation

   The height of each bar shows the value, while the base position shows categories or coordinates.

3. Final Answer:

   Data with two position dimensions and one height dimension -> Option A

4. Quick Check:

   3D bar chart = 2D position + height [OK]

Hint: Remember: 3D bars have x, y positions and z height [OK]

Common Mistakes:

• Confusing 3D bars with 2D bar charts
• Thinking 3D bars only show color differences
• Assuming 3D bars are line graphs

2. Which of the following is the correct way to create 3D axes in matplotlib before plotting a 3D bar chart?

easy

A. ax = plt.axes3d()

B. ax = plt.subplots(projection='3d')

C. ax = plt.subplot(projection='3d')

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

Solution

1. Step 1: Recall how to create 3D axes in matplotlib

   The common method is to create a figure and add a 3D subplot using add_subplot(111, projection='3d').

2. Step 2: Check each option

   ax = plt.subplot(projection='3d') uses subplot instead of add_subplot, which is incorrect. ax = plt.subplots(projection='3d') returns a tuple (figure, axes), so assigning directly to ax is incorrect. ax = plt.axes3d() is not a valid matplotlib function.

3. Final Answer:

   ax = plt.figure().add_subplot(111, projection='3d') -> Option D

4. Quick Check:

   Use figure().add_subplot with projection='3d' [OK]

Hint: Use figure().add_subplot(111, projection='3d') to get 3D axes [OK]

Common Mistakes:

• Using plt.subplot instead of plt.figure().add_subplot
• Trying to call non-existent plt.axes3d()
• Confusing subplots() with subplot()

3. What will be the output of the following code snippet?

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
x = [1, 2]
y = [3, 4]
z = [0, 0]
dx = dy = dz = [1, 1]
ax.bar3d(x, y, z, dx, dy, dz, color='red')
plt.show()

medium

A. Two red bars at positions (1,3) and (2,4) with height 1

B. Two red bars at positions (0,0) and (1,1) with height 1

C. Error because dx, dy, dz should be scalars, not lists

D. Empty plot with no bars

Solution

1. Step 1: Understand the parameters of ax.bar3d

   Parameters x, y, z are the positions of bars. dx, dy, dz are the sizes along each axis. Here, x=[1,2], y=[3,4], z=[0,0], and dx=dy=dz=[1,1].

2. Step 2: Analyze the plot output

   Two bars will appear at (1,3,0) and (2,4,0) with width=1, depth=1, height=1, colored red.

3. Final Answer:

   Two red bars at positions (1,3) and (2,4) with height 1 -> Option A

4. Quick Check:

   Positions and sizes match bars at (1,3) and (2,4) [OK]

Hint: Check x,y,z positions and dx,dy,dz sizes carefully [OK]

Common Mistakes:

• Assuming dx, dy, dz must be scalars only
• Confusing bar positions with sizes
• Expecting bars at (0,0) instead of given x,y

4. Identify the error in this code for plotting a 3D bar chart:

import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
x = [1, 2, 3]
y = [4, 5]
z = [0, 0, 0]
dx = dy = dz = 1
ax.bar3d(x, y, z, dx, dy, dz)
plt.show()

medium

A. Missing import for Axes3D

B. Length of y does not match length of x and z

C. dx, dy, dz must be lists, not scalars

D. ax.bar3d does not accept scalar sizes

Solution

1. Step 1: Check lengths of position arrays

   x has length 3, y has length 2, z has length 3. They must all be the same length for bar3d.

2. Step 2: Verify size parameters

   dx, dy, dz can be scalars or lists matching length of bars, so scalars are allowed.

3. Final Answer:

   Length of y does not match length of x and z -> Option B

4. Quick Check:

   All position arrays must have equal length [OK]

Hint: Check all position lists have same length [OK]

Common Mistakes:

• Assuming dx, dy, dz must be lists
• Ignoring mismatch in array lengths
• Forgetting to import mpl_toolkits.mplot3d (not needed here)

5. You want to plot a 3D bar chart showing sales data for 3 products over 4 months. Which approach correctly sets up the data for ax.bar3d()?

hard

A. Use x, y, z all as sales values, dz as zeros

B. Use x as months, y as products, z as sales values, and dz as ones

C. Use x as product indices repeated for each month, y as month indices tiled for each product, z as zeros, and dz as sales values

D. Use x and y as sales values, z as product indices, dz as month indices

Solution

1. Step 1: Understand the data layout for 3D bars

   x and y represent positions (product and month), z is the base height (usually zero), dz is the height of bars (sales values).

2. Step 2: Arrange data correctly

   Repeat product indices for each month (x), tile month indices for each product (y), set z to zero, and use sales data as dz.

3. Final Answer:

   Use x as product indices repeated for each month, y as month indices tiled for each product, z as zeros, and dz as sales values -> Option C

4. Quick Check:

   Positions = product/month, height = sales [OK]

Hint: Map x,y to categories, dz to values for bar height [OK]

Common Mistakes:

• Mixing sales values as positions instead of heights
• Using z as sales height instead of dz
• Not repeating/tiling indices properly for grid