Basic pie chart with plt.pie in Matplotlib - Mini Project: Build & Apply

Basic pie chart with plt.pie

📖 Scenario: You work in a small bakery and want to show which types of bread sell the most. You have the sales numbers for different bread types.

🎯 Goal: Create a pie chart using plt.pie to show the sales distribution of bread types.

📋 What You'll Learn

Create a dictionary called bread_sales with exact keys and values

Create a list called labels from the dictionary keys

Create a list called sizes from the dictionary values

Use plt.pie with sizes and labels to make the pie chart

Display the pie chart with plt.show()

💡 Why This Matters

🌍 Real World

Pie charts help businesses quickly see how parts contribute to a whole, like sales of different products.

💼 Career

Data analysts and scientists often use pie charts to present categorical data visually to stakeholders.

1

Create the bread sales data

Create a dictionary called bread_sales with these exact entries: 'White': 40, 'Wheat': 25, 'Rye': 20, 'Sourdough': 15.

Matplotlib

# Your code here

Hint

Use curly braces {} to create a dictionary with the given keys and values.

2

Prepare labels and sizes lists

Create a list called labels from the keys of bread_sales and a list called sizes from the values of bread_sales.

Matplotlib

bread_sales = {'White': 40, 'Wheat': 25, 'Rye': 20, 'Sourdough': 15}
# Your code here

Hint

Use list() with bread_sales.keys() and bread_sales.values() to get the lists.

3

Create the pie chart

Import matplotlib.pyplot as plt and use plt.pie with sizes and labels to create the pie chart.

Matplotlib

bread_sales = {'White': 40, 'Wheat': 25, 'Rye': 20, 'Sourdough': 15}
labels = list(bread_sales.keys())
sizes = list(bread_sales.values())
# Your code here

Hint

Use import matplotlib.pyplot as plt and then plt.pie() with the right arguments.

4

Show the pie chart

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

Matplotlib

import matplotlib.pyplot as plt

bread_sales = {'White': 40, 'Wheat': 25, 'Rye': 20, 'Sourdough': 15}
labels = list(bread_sales.keys())
sizes = list(bread_sales.values())

plt.pie(sizes, labels=labels)
# Your code here

Hint

Call plt.show() to open the pie chart window.

Practice

1. What does the plt.pie() function in matplotlib do?

easy

A. It creates a line chart to show trends over time.

B. It creates a pie chart to show parts of a whole.

C. It creates a bar chart to compare categories.

D. It creates a scatter plot to show data points.

Solution

1. Step 1: Understand the purpose of plt.pie()

   The function plt.pie() is designed to create pie charts, which visually represent parts of a whole as slices of a circle.

2. Step 2: Compare with other chart types

   Line charts, bar charts, and scatter plots are created with different functions like plt.plot(), plt.bar(), and plt.scatter(), not plt.pie().

3. Final Answer:

   It creates a pie chart to show parts of a whole. -> Option B

4. Quick Check:

   Pie chart = plt.pie() [OK]

Hint: Pie chart = parts of whole, use plt.pie() [OK]

Common Mistakes:

• Confusing pie chart with bar or line charts
• Thinking plt.pie() creates scatter plots
• Mixing up chart functions in matplotlib

2. Which of the following is the correct syntax to create a basic pie chart with labels using matplotlib?

easy

A. plt.pie(sizes, labels=labels)

B. plt.pie(labels, sizes=sizes)

C. plt.pie(labels=sizes, sizes=labels)

D. plt.pie(sizes, labels)

Solution

1. Step 1: Check the order of arguments in plt.pie()

   The first argument to plt.pie() is the sizes (values) of slices, and labels are passed as a keyword argument labels=.

2. Step 2: Validate correct keyword usage

   plt.pie(sizes, labels=labels) correctly uses plt.pie(sizes, labels=labels). Options B and C misuse argument order or keywords, and D misses the keyword for labels.

3. Final Answer:

   plt.pie(sizes, labels=labels) -> Option A

4. Quick Check:

   Sizes first, labels keyword [OK]

Hint: Sizes first, labels with labels= keyword [OK]

Common Mistakes:

• Passing labels as first argument instead of sizes
• Omitting labels= keyword
• Swapping sizes and labels arguments

3. What will be the output of this code?

import matplotlib.pyplot as plt
sizes = [30, 20, 50]
labels = ['A', 'B', 'C']
plt.pie(sizes, labels=labels, autopct='%1.1f%%')
plt.show()

medium

A. A pie chart with three slices labeled A, B, C showing percentages 30.0%, 20.0%, 50.0%

B. A bar chart with bars labeled A, B, C

C. A pie chart with slices but no labels or percentages

D. Syntax error due to autopct usage

Solution

1. Step 1: Understand plt.pie() parameters

   The sizes list defines slice sizes, labels assign names, and autopct='%1.1f%%' adds percentage text on slices.

2. Step 2: Predict the visual output

   The code will produce a pie chart with three slices labeled A, B, C, each showing their percentage values 30.0%, 20.0%, and 50.0% respectively.

3. Final Answer:

   A pie chart with three slices labeled A, B, C showing percentages 30.0%, 20.0%, 50.0% -> Option A

4. Quick Check:

   autopct adds percentages [OK]

Hint: autopct='%1.1f%%' shows slice percentages [OK]

Common Mistakes:

• Thinking autopct causes errors
• Expecting bar chart instead of pie chart
• Ignoring labels or percentages on chart

4. Identify the error in this code snippet that tries to create a pie chart:

import matplotlib.pyplot as plt
sizes = [40, 30, 30]
labels = ['X', 'Y', 'Z']
plt.pie(labels, sizes=sizes)
plt.show()

medium

A. The sizes list must be strings, not numbers.

B. The labels list is missing a keyword argument.

C. plt.show() is missing parentheses.

D. The sizes argument should be the first positional argument, not labels.

Solution

1. Step 1: Check argument order in plt.pie()

   The first argument must be sizes (numbers), but the code passes labels first, which is incorrect.

2. Step 2: Correct argument usage

   Sizes should be the first positional argument, and labels should be passed with labels=labels keyword.

3. Final Answer:

   The sizes argument should be the first positional argument, not labels. -> Option D

4. Quick Check:

   Sizes first, labels keyword [OK]

Hint: Sizes first, labels with labels= keyword [OK]

Common Mistakes:

• Passing labels as first argument
• Forgetting labels= keyword
• Confusing argument order

5. You want to create a pie chart showing sales distribution for 4 products with sizes [15, 25, 35, 25] and labels ['P1', 'P2', 'P3', 'P4']. You also want to highlight the largest slice by "exploding" it out. Which code correctly does this?

hard

A. plt.pie([15,25,35,25], labels=['P1','P2','P3','P4'], explode=[0,0,0,0.1], autopct='%1.1f%%')

B. plt.pie([15,25,35,25], labels=['P1','P2','P3','P4'], explode=[0.1,0,0,0], autopct='%1.1f%%')

C. plt.pie([15,25,35,25], labels=['P1','P2','P3','P4'], explode=[0,0,0.1,0], autopct='%1.1f%%')

D. plt.pie([15,25,35,25], labels=['P1','P2','P3','P4'], explode=[0,0.1,0,0], autopct='%1.1f%%')

Solution

1. Step 1: Identify the largest slice

   The sizes are [15, 25, 35, 25]. The largest value is 35 at index 2 (third element).

2. Step 2: Set explode to highlight largest slice

   The explode list should have 0.1 at index 2 and 0 elsewhere: [0, 0, 0.1, 0]. plt.pie([15,25,35,25], labels=['P1','P2','P3','P4'], explode=[0,0,0.1,0], autopct='%1.1f%%') matches this.

3. Final Answer:

   plt.pie([15,25,35,25], labels=['P1','P2','P3','P4'], explode=[0,0,0.1,0], autopct='%1.1f%%') -> Option C

4. Quick Check:

   Explode largest slice index 2 [OK]

Hint: Explode list: 0.1 at largest slice index [OK]

Common Mistakes:

• Exploding wrong slice index
• Using explode without matching list length
• Forgetting autopct for percentages