Stacked area chart in Matplotlib - Mini Project: Build & Apply

Stacked Area Chart

📖 Scenario: You work as a data analyst for a small company. You have sales data for three products over four quarters. Your manager wants to see how the total sales and individual product sales changed over time in a clear visual format.

🎯 Goal: Create a stacked area chart using matplotlib to show the sales trends of three products over four quarters.

📋 What You'll Learn

Create a dictionary called sales_data with keys 'Q1', 'Q2', 'Q3', 'Q4' and values as lists of sales numbers for three products.

Create a list called quarters with the values 'Q1', 'Q2', 'Q3', 'Q4'.

Use matplotlib.pyplot to create a stacked area chart.

Label the x-axis as 'Quarter' and y-axis as 'Sales'.

Add a legend with product names 'Product A', 'Product B', and 'Product C'.

💡 Why This Matters

🌍 Real World

Stacked area charts are useful to visualize how different parts contribute to a whole over time, such as sales of multiple products across quarters.

💼 Career

Data analysts and scientists often create stacked area charts to present trends and comparisons clearly to stakeholders.

1

Create the sales data dictionary

Create a dictionary called sales_data with keys 'Q1', 'Q2', 'Q3', 'Q4'. Each key should have a list of three sales numbers: [100, 150, 200] for 'Q1', [120, 160, 210] for 'Q2', [130, 170, 220] for 'Q3', and [140, 180, 230] for 'Q4'.

Matplotlib

# Create the sales_data dictionary with exact values
# Your code here

Hint

Use curly braces {} to create the dictionary. Each key is a quarter string, and the value is a list of three numbers.

2

Create the quarters list

Create a list called quarters with the values 'Q1', 'Q2', 'Q3', and 'Q4' in this order.

Matplotlib

sales_data = {
    'Q1': [100, 150, 200],
    'Q2': [120, 160, 210],
    'Q3': [130, 170, 220],
    'Q4': [140, 180, 230]
}
# Create the quarters list with exact values
# Your code here

Hint

Use square brackets [] to create the list with the quarter strings in order.

3

Prepare data and plot the stacked area chart

Import matplotlib.pyplot as plt. Extract the sales lists for each quarter from sales_data in the order of quarters. Create three lists: product_a, product_b, and product_c containing sales for each product across quarters. Use plt.stackplot with quarters and these three lists to create a stacked area chart. Add a legend with labels 'Product A', 'Product B', and 'Product C'. Label the x-axis as 'Quarter' and y-axis as 'Sales'.

Matplotlib

sales_data = {
    'Q1': [100, 150, 200],
    'Q2': [120, 160, 210],
    'Q3': [130, 170, 220],
    'Q4': [140, 180, 230]
}
quarters = ['Q1', 'Q2', 'Q3', 'Q4']

# Import matplotlib.pyplot as plt
# Create product_a, product_b, product_c lists from sales_data
# Use plt.stackplot with quarters and product lists
# Add legend and axis labels
# Your code here

Hint

Use list comprehension to get sales for each product. Use plt.stackplot with the quarters and product lists. Add labels and legend for clarity.

4

Display the stacked area chart

Use plt.show() to display the stacked area chart.

Matplotlib

import matplotlib.pyplot as plt

sales_data = {
    'Q1': [100, 150, 200],
    'Q2': [120, 160, 210],
    'Q3': [130, 170, 220],
    'Q4': [140, 180, 230]
}
quarters = ['Q1', 'Q2', 'Q3', 'Q4']

product_a = [sales_data[q][0] for q in quarters]
product_b = [sales_data[q][1] for q in quarters]
product_c = [sales_data[q][2] for q in quarters]

plt.stackplot(quarters, product_a, product_b, product_c, labels=['Product A', 'Product B', 'Product C'])
plt.xlabel('Quarter')
plt.ylabel('Sales')
plt.legend(loc='upper left')

# Display the plot
# Your code here

Hint

Use plt.show() to display the chart window.

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