Stacked area chart in Matplotlib - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of a basic stacked area chart code

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

Matplotlib

import matplotlib.pyplot as plt

labels = ['A', 'B', 'C']
data = [[1, 2, 3], [2, 3, 4], [3, 4, 5]]
plt.stackplot(range(3), *data, labels=labels)
plt.legend(loc='upper left')
plt.show()

A A line chart with three lines labeled A, B, and C

B A stacked area chart with three layers increasing from left to right, labeled A, B, and C

C A bar chart with three bars labeled A, B, and C

D A scatter plot with points labeled A, B, and C

💡 Hint

Stacked area charts fill areas between lines stacked on top of each other.

The plt.stackplot function creates a stacked area chart where each data series is stacked vertically. The labels appear in the legend.

❓ data_output

intermediate

Number of layers in stacked area chart

Given the data below used in a stacked area chart, how many layers will the chart have?

Matplotlib

data = [[5, 3, 6, 2], [1, 4, 2, 3], [3, 2, 1, 5], [4, 1, 3, 4]]

A 3

B 2

C 4

D 5

💡 Hint

Each inner list represents one layer in the stacked area chart.

The data list has 4 inner lists, so the stacked area chart will have 4 layers stacked on top of each other.

🔧 Debug

advanced

Identify the error in stacked area chart code

What error will this code raise when trying to plot a stacked area chart?

Matplotlib

import matplotlib.pyplot as plt

x = [0, 1, 2]
y = [[1, 2], [3, 4], [5, 6]]
plt.stackplot(x, *y)
plt.show()

A ValueError: x and y must have same length

B IndexError: list index out of range

C TypeError: unhashable type: 'list'

D No error, chart displays correctly

💡 Hint

Check if x and y data lengths match for plotting.

The x list has length 3, but y is a list of 3 lists each of length 2, so y's shape does not match x's length, causing a ValueError.

❓ visualization

advanced

Effect of alpha parameter in stacked area chart

What visual effect does setting alpha=0.5 have on a stacked area chart in matplotlib?

Matplotlib

import matplotlib.pyplot as plt

x = [0, 1, 2, 3]
y = [[1, 2, 3, 4], [2, 1, 2, 1]]
plt.stackplot(x, *y, alpha=0.5)
plt.show()

A The stacked areas become semi-transparent, allowing background or overlapping colors to show through

B The stacked areas become fully opaque and brighter

C The stacked areas disappear completely

D The stacked areas change to dashed outlines without fill

💡 Hint

Alpha controls transparency in matplotlib plots.

Setting alpha to 0.5 makes the colors half transparent, so you can see layers beneath or background grid lines.

🧠 Conceptual

expert

Interpreting stacked area chart data trends

In a stacked area chart showing sales of three products over time, if the total height of the stack increases but the bottom layer's area stays the same, what does this indicate?

A Sales of the bottom product increased and others decreased

B Sales of all products increased equally

C Sales of the bottom product decreased while others increased

D Sales of the bottom product stayed constant while sales of other products increased

💡 Hint

The bottom layer's area represents its absolute value over time.

If the bottom layer's area stays the same, its sales did not change. The total stack height increasing means other products' sales increased.

Practice

1. What does a stacked area chart in matplotlib primarily show?

easy

A. How different parts add up to a whole over categories or time

B. Only the total sum of all data points

C. The relationship between two unrelated variables

D. The frequency distribution of a single variable

Solution

1. Step 1: Understand the purpose of stacked area charts

   Stacked area charts display multiple data series stacked on top of each other to show how each part contributes to the total over time or categories.

2. Step 2: Compare options with this purpose

   How different parts add up to a whole over categories or time correctly describes this purpose. Options A, B, and C describe other chart types or incorrect uses.

3. Final Answer:

   How different parts add up to a whole over categories or time -> Option A

4. Quick Check:

   Stacked area chart = parts adding to whole [OK]

Hint: Stacked area charts show parts stacked to form a whole [OK]

Common Mistakes:

• Confusing stacked area chart with line chart
• Thinking it shows only totals, not parts
• Mixing it up with scatter plots

2. Which of the following is the correct way to create a stacked area chart using matplotlib.pyplot?

easy

A. plt.stackplot(x, y1, y2, labels=['A', 'B'])

B. plt.area(x, y1, y2)

C. plt.plot_area(x, y1, y2)

D. plt.stack(x, y1, y2)

Solution

1. Step 1: Recall the correct function name

   The correct function to create stacked area charts in matplotlib is stackplot from matplotlib.pyplot.

2. Step 2: Check the syntax

   plt.stackplot(x, y1, y2, labels=['A', 'B']) uses plt.stackplot(x, y1, y2, labels=['A', 'B']), which is correct. Other options use non-existent functions.

3. Final Answer:

   plt.stackplot(x, y1, y2, labels=['A', 'B']) -> Option A

4. Quick Check:

   Function name is stackplot [OK]

Hint: Use plt.stackplot for stacked area charts [OK]

Common Mistakes:

• Using plt.area which does not exist
• Trying plt.plot_area instead of stackplot
• Forgetting to pass x and multiple y arrays

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

import matplotlib.pyplot as plt
x = [1, 2, 3]
y1 = [1, 2, 3]
y2 = [2, 1, 2]
plt.stackplot(x, y1, y2, labels=['A', 'B'])
plt.legend()
plt.show()

medium

A. An error because y arrays have different lengths

B. A line chart with two lines labeled 'A' and 'B'

C. A bar chart with two bars for each x value

D. A stacked area chart with two layers labeled 'A' and 'B' over x=1 to 3

Solution

1. Step 1: Analyze the data lengths and function

   Both y1 and y2 have length 3 matching x. The function plt.stackplot creates a stacked area chart.

2. Step 2: Understand the output

   The code plots two stacked areas labeled 'A' and 'B' over x values 1 to 3, then shows a legend.

3. Final Answer:

   A stacked area chart with two layers labeled 'A' and 'B' over x=1 to 3 -> Option D

4. Quick Check:

   Stackplot with matching lengths = stacked area chart [OK]

Hint: Check lengths of x and y arrays match for stackplot [OK]

Common Mistakes:

• Thinking stackplot creates line or bar charts
• Assuming error due to lengths when they match
• Ignoring legend labels

4. Identify the error in this code that tries to plot a stacked area chart:

import matplotlib.pyplot as plt
x = [1, 2, 3]
y1 = [1, 2]
y2 = [2, 1, 2]
plt.stackplot(x, y1, y2)
plt.show()

medium

A. Missing labels argument causes the plot to fail

B. plt.stackplot does not accept multiple y arrays

C. x and y1 have different lengths causing a ValueError

D. plt.show() is missing parentheses

Solution

1. Step 1: Check lengths of x and y arrays

   x has length 3, y1 has length 2, y2 has length 3. Length mismatch causes error.

2. Step 2: Understand stackplot requirements

   All y arrays must have the same length as x. This mismatch causes a ValueError.

3. Final Answer:

   x and y1 have different lengths causing a ValueError -> Option C

4. Quick Check:

   Length mismatch in stackplot = error [OK]

Hint: Ensure all y arrays match x length in stackplot [OK]

Common Mistakes:

• Assuming labels are required to avoid errors
• Thinking stackplot accepts different length arrays
• Forgetting to call plt.show() with parentheses

5. You have monthly sales data for three products over 6 months:

months = [1, 2, 3, 4, 5, 6]
product_a = [5, 7, 8, 6, 7, 9]
product_b = [3, 4, 2, 5, 6, 4]
product_c = [2, 3, 4, 3, 2, 3]

How would you create a stacked area chart showing each product's contribution over time with a legend?

hard

A. plt.plot(months, product_a + product_b + product_c)
plt.legend(['Total'])
plt.show()

B. plt.stackplot(months, product_a, product_b, product_c, labels=['A', 'B', 'C'])
plt.legend()
plt.show()

C. plt.bar(months, product_a, bottom=product_b)
plt.show()

D. plt.stackplot(product_a, product_b, product_c, labels=['A', 'B', 'C'])
plt.legend()
plt.show()

Solution

1. Step 1: Use plt.stackplot with x and multiple y arrays

   Pass months as x and product sales as y arrays with labels for legend.

2. Step 2: Add legend and show plot

   Call plt.legend() to show labels and plt.show() to display the chart.

3. Final Answer:

   plt.stackplot(months, product_a, product_b, product_c, labels=['A', 'B', 'C']) plt.legend() plt.show() -> Option B

4. Quick Check:

   Stackplot with labels + legend = stacked area chart [OK]

Hint: Pass x, multiple y arrays, labels, then call plt.legend() [OK]

Common Mistakes:

• Adding y arrays instead of stacking
• Using bar chart with wrong bottom parameter
• Forgetting to pass x as first argument