Why Donut chart variation in Matplotlib? - Purpose & Use Cases

The Big Idea

Discover how a simple hole in a pie chart can make your data story clearer and more engaging!

The Scenario

Imagine you have a pie chart showing sales by product, but you want to highlight the total sales in the center for better clarity.

The Problem

Manually drawing a circle on top of a pie chart to create a donut effect is tricky and can cause misalignment or inconsistent sizes, making the chart look unprofessional and confusing.

The Solution

The donut chart variation lets you easily create a clear, attractive chart with a hole in the center, improving readability and focus without extra manual drawing steps.

Before vs After

✗ Before

plt.pie(sizes)
plt.gca().add_artist(plt.Circle((0,0), 0.5, color='white'))

✓ After

plt.pie(sizes, wedgeprops=dict(width=0.5))

What It Enables

This lets you present data in a visually appealing way that highlights key information right in the center of the chart.

Real Life Example

A marketing team uses a donut chart to show market share by brand, with the total market size displayed clearly in the center for quick understanding.

Key Takeaways

Manual overlay of circles is hard and error-prone.

Donut charts simplify creating a hole in pie charts.

They improve data clarity and visual appeal.

Practice

1.

What is the main difference between a donut chart and a pie chart in matplotlib?

easy

A. A donut chart has a hole in the center, a pie chart does not.

B. A donut chart uses bars, a pie chart uses slices.

C. A donut chart shows data over time, a pie chart shows categories.

D. A donut chart is 3D, a pie chart is 2D.

Solution

1. Step 1: Understand pie chart basics

   A pie chart divides a circle into slices representing parts of a whole.

2. Step 2: Identify donut chart feature

   A donut chart is a pie chart with a hole in the center, making it look like a donut.

3. Final Answer:

   A donut chart has a hole in the center, a pie chart does not. -> Option A

4. Quick Check:

   Donut chart = pie chart + hole [OK]

Hint: Donut chart = pie chart with center hole [OK]

Common Mistakes:

• Thinking donut charts use bars
• Confusing donut charts with 3D charts
• Believing donut charts show time series

2.

Which matplotlib code snippet correctly creates a donut chart with a hole size controlled by wedgeprops?

import matplotlib.pyplot as plt
sizes = [30, 40, 30]
plt.pie(sizes, wedgeprops=???)
plt.show()

easy

A. wedgeprops={'height': 0.5}

B. wedgeprops={'radius': 0.5}

C. wedgeprops={'width': 0.5}

D. wedgeprops={'size': 0.5}

Solution

1. Step 1: Recall donut hole control

   The hole size in a donut chart is set by the 'width' key inside wedgeprops.

2. Step 2: Match correct syntax

   Using wedgeprops={'width': 0.5} creates a hole half the radius size.

3. Final Answer:

   wedgeprops={'width': 0.5} -> Option C

4. Quick Check:

   wedgeprops width controls hole size [OK]

Hint: Use wedgeprops={'width': value} for donut hole [OK]

Common Mistakes:

• Using 'radius' instead of 'width'
• Using 'height' or 'size' keys incorrectly
• Omitting wedgeprops entirely

3.

What will be the visual output of this code?

import matplotlib.pyplot as plt
sizes = [10, 20, 30]
plt.pie(sizes, wedgeprops={'width': 0.3})
plt.show()

medium

A. A donut chart with a thin ring shape

B. A pie chart with no hole in the center

C. A donut chart with a very large hole

D. A bar chart instead of a pie chart

Solution

1. Step 1: Analyze wedgeprops width value

   The width is set to 0.3, meaning the donut hole is 70% of the radius.

2. Step 2: Visualize the chart shape

   This creates a donut chart with a thin ring shape because the hole is large but not full radius.

3. Final Answer:

   A donut chart with a thin ring shape -> Option A

4. Quick Check:

   width=0.3 means thin donut ring [OK]

Hint: Smaller width = thinner donut ring [OK]

Common Mistakes:

• Thinking width=0.3 means no hole
• Confusing hole size with radius
• Expecting a bar chart output

4.

Identify the error in this donut chart code and select the fix:

import matplotlib.pyplot as plt
sizes = [25, 35, 40]
plt.pie(sizes, wedgeprops={'width': '0.5'})
plt.show()

medium

A. Add labels parameter

B. Remove wedgeprops entirely

C. Change 'width' to 'radius'

D. Change '0.5' to 0.5 (string to float)

Solution

1. Step 1: Check wedgeprops value type

   The width value is given as a string '0.5', but it must be a number (float).

2. Step 2: Correct the data type

   Changing '0.5' to 0.5 fixes the type error and creates the donut hole properly.

3. Final Answer:

   Change '0.5' to 0.5 (string to float) -> Option D

4. Quick Check:

   width must be float, not string [OK]

Hint: Use numbers, not strings, for wedgeprops values [OK]

Common Mistakes:

• Using string instead of float for width
• Changing width key incorrectly
• Ignoring type errors

5.

You want to create a donut chart showing sales distribution with a hole size that leaves 40% thickness for the slices. Which wedgeprops value should you use?

hard

A. wedgeprops={'width': 0.4}

B. wedgeprops={'width': 0.6}

C. wedgeprops={'width': 0.2}

D. wedgeprops={'width': 1.0}

Solution

1. Step 1: Understand width meaning

   The 'width' value is the thickness of the slices as a fraction of the radius.

2. Step 2: Calculate width for 40% thickness

   For 40% thickness for the slices, set width=0.6 (leaving a hole size of 40%).

3. Final Answer:

   wedgeprops={'width': 0.6} -> Option B

4. Quick Check:

   width=0.6 gives 40% slice thickness [OK]

Hint: Width = slice thickness fraction (1 - hole size) [OK]

Common Mistakes:

• Confusing width with hole size
• Using width less than hole thickness
• Setting width to 1 (no hole)