Basic pie chart with plt.pie in Matplotlib - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the purpose of the plt.pie() function in matplotlib?

The plt.pie() function creates a pie chart, which is a circular graph divided into slices to show proportions of different categories.

beginner

Which parameter in plt.pie() specifies the sizes of each slice?

The first parameter, usually a list or array, specifies the sizes (values) of each slice in the pie chart.

beginner

How can you add labels to each slice in a pie chart using plt.pie()?

Use the labels parameter and pass a list of strings to name each slice.

intermediate

What does the autopct parameter do in plt.pie()?

The autopct parameter formats and displays the percentage value on each slice, e.g., '%.1f%%' shows one decimal place.

intermediate

Why is it important to call plt.axis('equal') after plt.pie()?

Calling plt.axis('equal') makes sure the pie chart is drawn as a circle instead of an ellipse, keeping proportions accurate.

What type of chart does plt.pie() create?

A Pie chart

B Bar chart

C Line chart

D Scatter plot

plt.pie() creates a pie chart, which shows parts of a whole as slices.

Which parameter adds labels to pie chart slices?

A explode

B sizes

C colors

D labels

The labels parameter adds names to each slice.

How do you show percentage values on pie slices?

A Use <code>labels</code>

B Use <code>autopct</code>

C Use <code>colors</code>

D Use <code>explode</code>

The autopct parameter formats and shows percentages on slices.

What does plt.axis('equal') do after plotting a pie chart?

A Changes colors

B Explodes slices

C Makes pie circular

D Adds labels

It ensures the pie chart is a perfect circle, not an ellipse.

Which of these is NOT a parameter of plt.pie()?

A xlabel

B sizes

C autopct

D labels

xlabel is for axis labels, not used in pie charts.

Explain how to create a basic pie chart using plt.pie() including how to add labels and percentages.

Think about the main inputs needed to show parts of a whole clearly.

Why is it important to use plt.axis('equal') after plotting a pie chart?

Consider the shape of the pie chart and how it affects visual accuracy.

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