Stacked bar charts in Matplotlib - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of a basic stacked bar chart code

What will be the output of this code snippet that creates a stacked bar chart using matplotlib?

Matplotlib

import matplotlib.pyplot as plt

labels = ['A', 'B', 'C']
values1 = [3, 5, 1]
values2 = [2, 3, 4]

plt.bar(labels, values1, label='Group 1')
plt.bar(labels, values2, bottom=values1, label='Group 2')
plt.legend()
plt.show()

A A bar chart with three bars labeled A, B, C, each bar split into two stacked segments representing Group 1 and Group 2 values.

B A line chart connecting points for Group 1 and Group 2 values over labels A, B, C.

C A bar chart with bars for Group 1 and Group 2 side by side for each label A, B, C.

D A scatter plot showing points for Group 1 and Group 2 values at labels A, B, C.

💡 Hint

Stacked bars use the 'bottom' parameter to stack one bar on top of another.

The code uses plt.bar twice with the same labels. The second bar uses 'bottom=values1' to stack on top of the first bars, creating a stacked bar chart.

❓ data_output

intermediate

Resulting heights of stacked bars

Given these data arrays for two groups, what is the total height of the stacked bars for each label after stacking?

Matplotlib

values1 = [4, 2, 7]
values2 = [1, 3, 2]
# Total height is values1 + values2 element-wise

A [1, 3, 2]

B [3, 5, 9]

C [4, 3, 7]

D [5, 5, 9]

💡 Hint

Add the values from both groups for each label.

The total height of each stacked bar is the sum of the corresponding values from values1 and values2.

🔧 Debug

advanced

Identify the error in this stacked bar chart code

What error will this code produce when run?

Matplotlib

import matplotlib.pyplot as plt
labels = ['X', 'Y']
values1 = [3, 4]
values2 = [2, 5, 1]
plt.bar(labels, values1, label='First')
plt.bar(labels, values2, bottom=values1, label='Second')
plt.legend()
plt.show()

A No error, the plot will display correctly

B TypeError because bottom parameter must be a single number

C ValueError due to mismatched lengths of values2 and labels

D IndexError because values1 is shorter than values2

💡 Hint

Check if the lengths of values arrays match the labels.

values2 has 3 elements but labels has 2, so matplotlib raises a ValueError about mismatched lengths.

❓ visualization

advanced

Interpreting a stacked bar chart visualization

You see a stacked bar chart with three bars labeled Jan, Feb, Mar. Each bar has two colors: blue on bottom and orange on top. The blue segments are 5, 3, 4 units tall respectively. The orange segments are 2, 6, 1 units tall respectively. What is the total height of the bar for February?

A 3 units

B 9 units

C 6 units

D 5 units

💡 Hint

Add the heights of the stacked segments for February.

February's total height is blue segment (3) plus orange segment (6) = 9 units.

🚀 Application

expert

Calculate percentage contribution in stacked bars

Given these data for three categories over two groups, calculate the percentage contribution of Group 2 to the total stacked bar height for category 'B'. Category labels: ['A', 'B', 'C'] Group 1 values: [10, 20, 30] Group 2 values: [5, 15, 10] What is the percentage contribution of Group 2 in category 'B'?

A 42.86%

B 60.00%

C 33.33%

D 75.00%

💡 Hint

Percentage = (Group 2 value / (Group 1 value + Group 2 value)) * 100

For category B, Group 1 is 20 and Group 2 is 15. Total is 35. Percentage = (15/35)*100 = 42.86%.

Practice

1. What is the main purpose of using a stacked bar chart in data visualization?

easy

A. To create a pie chart with multiple slices

B. To display data points as individual dots on a graph

C. To plot a line connecting data points over time

D. To show how different parts contribute to the total within each group

Solution

1. Step 1: Understand the concept of stacked bar charts

   Stacked bar charts combine multiple data parts into one bar to show totals and parts.

2. Step 2: Identify the purpose of stacking

   Stacking helps visualize how each part contributes to the total for each group.

3. Final Answer:

   To show how different parts contribute to the total within each group -> Option D

4. Quick Check:

   Stacked bars = parts + total [OK]

Hint: Stacked bars add parts vertically to show totals [OK]

Common Mistakes:

• Confusing stacked bars with line charts
• Thinking stacked bars show individual points only
• Mixing stacked bars with pie charts

2. Which matplotlib parameter is used to stack bars on top of each other in a bar chart?

easy

A. height

B. bottom

C. width

D. align

Solution

1. Step 1: Recall bar chart parameters

   In matplotlib, height sets bar size, width sets bar thickness, align controls bar alignment.

2. Step 2: Identify stacking parameter

   The bottom parameter sets where the bar starts vertically, allowing stacking on previous bars.

3. Final Answer:

   bottom -> Option B

4. Quick Check:

   Stack bars use bottom parameter [OK]

Hint: Use bottom to place bars on top of others [OK]

Common Mistakes:

• Using height to stack bars (it sets bar size)
• Confusing width with stacking
• Using align which only shifts bars horizontally

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

import matplotlib.pyplot as plt

labels = ['A', 'B']
values1 = [3, 5]
values2 = [2, 4]

plt.bar(labels, values1)
plt.bar(labels, values2, bottom=values1)
plt.show()

medium

A. Two bars per label, stacked vertically

B. Error because bottom parameter is incorrect

C. Only one bar per label showing values2

D. Two bars per label, side by side

Solution

1. Step 1: Analyze the first bar call

   The first plt.bar draws bars of height 3 and 5 for labels 'A' and 'B'.

2. Step 2: Analyze the second bar call with bottom

   The second plt.bar draws bars of height 2 and 4 stacked on top of the first bars using bottom=values1.

3. Final Answer:

   Two bars per label, stacked vertically -> Option A

4. Quick Check:

   bottom stacks bars vertically [OK]

Hint: bottom stacks bars vertically on previous bars [OK]

Common Mistakes:

• Thinking bars appear side by side without bottom
• Assuming only one bar per label is drawn
• Believing bottom parameter causes error

4. Identify the error in this code for creating a stacked bar chart:

import matplotlib.pyplot as plt

labels = ['X', 'Y']
values1 = [4, 6]
values2 = [3, 5]

plt.bar(labels, values1)
plt.bar(labels, values2, bottom=values2)
plt.show()

medium

A. Labels list is missing an element

B. plt.bar cannot be called twice

C. Using bottom=values2 instead of bottom=values1 causes incorrect stacking

D. values1 and values2 must be the same length

Solution

1. Step 1: Check the bottom parameter usage

   The second bar uses bottom=values2, which stacks bars on themselves, not on the first bars.

2. Step 2: Correct stacking requires bottom=values1

   To stack bars correctly, the second bars should start at the height of the first bars, so bottom=values1 is needed.

3. Final Answer:

   Using bottom=values2 instead of bottom=values1 causes incorrect stacking -> Option C

4. Quick Check:

   bottom must be previous bar heights [OK]

Hint: Stack bars using bottom=previous bar heights [OK]

Common Mistakes:

• Setting bottom to current bar heights instead of previous
• Thinking plt.bar can only be called once
• Ignoring length matching of values

5. You have three categories of sales data for two stores:

store_labels = ['Store1', 'Store2']
sales_A = [10, 15]
sales_B = [5, 7]
sales_C = [3, 4]

How do you create a stacked bar chart showing all three sales categories stacked for each store?

hard

A. Plot sales_A, then sales_B with bottom=sales_A, then sales_C with bottom=sales_A + sales_B

B. Plot sales_A, sales_B, sales_C all with bottom=0

C. Plot sales_A, then sales_B with bottom=sales_A, then sales_C with bottom=sales_B

D. Plot sales_A with bottom=sales_B, sales_B with bottom=sales_C, sales_C with bottom=sales_A

Solution

1. Step 1: Plot the first category normally

   Plot sales_A bars starting at zero (default).

2. Step 2: Stack second category on first

   Plot sales_B bars with bottom=sales_A to stack on top of sales_A.

3. Step 3: Stack third category on sum of first two

   Plot sales_C bars with bottom=[a+b for a,b in zip(sales_A, sales_B)] to stack on top of both.

4. Final Answer:

   Plot sales_A, then sales_B with bottom=sales_A, then sales_C with bottom=sales_A + sales_B -> Option A

5. Quick Check:

   Stack each bar on sum of all below [OK]

Hint: Stack bars using cumulative sums for bottom [OK]

Common Mistakes:

• Stacking third category only on second, ignoring first
• Plotting all bars at bottom=0 causing overlap
• Using wrong bottom values causing incorrect stacking