Categorical plots (boxplot, violinplot) in Data Analysis Python - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of boxplot with grouped categories

What will be the output of the following code snippet that creates a boxplot grouped by category?

Data Analysis Python

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

data = pd.DataFrame({
    'Category': ['A', 'A', 'B', 'B', 'C', 'C'],
    'Value': [10, 15, 10, 20, 15, 25]
})
sns.boxplot(x='Category', y='Value', data=data)
plt.show()

A A boxplot with three boxes labeled A, B, C showing value distributions: A (10,15), B (10,20), C (15,25)

B A line plot connecting points (A,10), (A,15), (B,10), (B,20), (C,15), (C,25)

C A scatter plot with points at (A,10), (A,15), (B,10), (B,20), (C,15), (C,25)

D A bar chart showing sum of values for each category

💡 Hint

Boxplots show distribution of values grouped by categories.

The boxplot groups data by 'Category' and shows the distribution of 'Value' for each group as boxes.

❓ data_output

intermediate

Number of boxes in violinplot

Given the following data and code, how many violin shapes will appear in the plot?

Data Analysis Python

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

data = pd.DataFrame({
    'Group': ['X', 'X', 'Y', 'Y', 'Y', 'Z'],
    'Score': [5, 7, 6, 8, 7, 9]
})
sns.violinplot(x='Group', y='Score', data=data)
plt.show()

A 6

B 2

C 1

D 3

💡 Hint

Each unique category in 'Group' creates one violin shape.

There are three unique groups: X, Y, and Z, so the violinplot will have three violins.

❓ visualization

advanced

Identify the plot type from description

Which plot type best shows the distribution shape and individual data points for categories?

A Violinplot

B Boxplot

C Bar plot

D Scatter plot

💡 Hint

One plot type shows a smooth density shape and can include individual points.

Violinplots show the distribution shape as a smooth density and can overlay individual data points, unlike boxplots which show summary statistics only.

🔧 Debug

advanced

Error in boxplot code

What error will this code produce and why? import seaborn as sns import matplotlib.pyplot as plt sns.boxplot(x='Category', y='Value') plt.show()

Data Analysis Python

import seaborn as sns
import matplotlib.pyplot as plt

sns.boxplot(x='Category', y='Value')
plt.show()

A NameError: name 'Category' is not defined

B ValueError: x and y must be numeric

C TypeError: boxplot() missing 1 required positional argument: 'data'

D No error, plot shows empty figure

💡 Hint

Seaborn needs data argument to know where to find columns.

The code misses the 'data' argument, so seaborn cannot find 'Category' and 'Value' columns, causing a TypeError.

🚀 Application

expert

Choosing plot for comparing distributions with many categories

You have a dataset with 20 categories and want to compare the distribution of a numeric variable across them. Which plot is best to use and why?

A Bar plot, because it shows average values clearly for many categories

B Boxplot, because it summarizes distribution with quartiles and is compact for many categories

C Violinplot, because it shows detailed distribution shape for each category clearly even with many categories

D Scatter plot, because it shows all individual points for all categories

💡 Hint

Consider clarity and compactness when many categories exist.

Boxplots summarize distributions with quartiles and outliers, making them easier to read when many categories exist. Violinplots can become cluttered with many categories.