FacetGrid for multi-panel views in Data Analysis Python - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of FacetGrid with hue and col

What is the output of the following code snippet using seaborn's FacetGrid?

Data Analysis Python

import seaborn as sns
import matplotlib.pyplot as plt

penguins = sns.load_dataset('penguins')
g = sns.FacetGrid(penguins, col='species', hue='sex')
g.map(plt.scatter, 'bill_length_mm', 'bill_depth_mm').add_legend()
plt.close()  # Prevent plot display in test environment
print(len(g.axes.flatten()))

A 3

B 2

C 1

D 4

💡 Hint

Think about how many unique species are in the penguins dataset.

FacetGrid with col='species' creates one panel per unique species. The penguins dataset has 3 species, so 3 panels are created.

❓ data_output

intermediate

Number of panels in FacetGrid with row and col

Given the following code, how many total panels will the FacetGrid create?

Data Analysis Python

import seaborn as sns
penguins = sns.load_dataset('penguins')
g = sns.FacetGrid(penguins, row='island', col='species')
print(len(g.axes.flatten()))

A 3

B 9

C 6

D 12

💡 Hint

Count unique values in 'island' and 'species' columns.

There are 3 unique islands and 3 unique species, so total panels = 3 * 3 = 9.

❓ visualization

advanced

Identify the FacetGrid layout from the plot description

You create a FacetGrid with parameters row='sex', col='island', and hue='species'. Which layout best describes the resulting grid?

A Rows represent species; columns represent sex; colors represent islands.

B Rows represent islands; columns represent species; colors represent sex.

C Rows represent species; columns represent islands; colors represent sex.

D Rows represent male and female; columns represent islands; colors represent species.

💡 Hint

Remember the parameters row, col, and hue correspond to rows, columns, and colors respectively.

The FacetGrid parameters map directly: row='sex' means rows are sex categories, col='island' means columns are islands, and hue='species' means colors show species.

🔧 Debug

advanced

Why does this FacetGrid code raise an error?

Consider this code snippet: import seaborn as sns import matplotlib.pyplot as plt penguins = sns.load_dataset('penguins') g = sns.FacetGrid(penguins, col='species', row='sex') g.map(sns.histplot, 'flipper_length_mm') plt.show() Why does this code raise an error?

A sns.histplot cannot be used with FacetGrid.map because it expects a DataFrame, not arrays.

B The 'sex' column contains missing values causing the FacetGrid to fail.

C The map function requires matplotlib.pyplot functions, not seaborn functions.

D FacetGrid requires numeric columns for row and col parameters, but 'sex' is categorical.

💡 Hint

Check the expected input types for functions used with FacetGrid.map.

FacetGrid.map passes arrays to the plotting function, but sns.histplot expects a DataFrame or Series, causing a TypeError.

🚀 Application

expert

Create a FacetGrid showing mean body mass per species and island

You want to create a FacetGrid that shows the mean body mass (in grams) for each species on each island. Which approach correctly prepares the data and creates the FacetGrid?

A Use sns.FacetGrid(penguins, col='species', row='island').map(sns.barplot, 'species', 'body_mass_g') directly on raw data.

B Use penguins.pivot_table(index='species', columns='island', values='body_mass_g', aggfunc='mean') and plot with FacetGrid using col='species'.

C Use penguins.groupby(['species', 'island'])['body_mass_g'].mean().reset_index() and then sns.FacetGrid with col='species', row='island' mapping sns.barplot with x='island', y='body_mass_g'.

D Use sns.FacetGrid(penguins, col='species').map(sns.barplot, 'island', 'body_mass_g') without aggregation.

💡 Hint

FacetGrid works best with pre-aggregated data for bar plots when grouping by multiple variables.

Option C correctly aggregates mean body mass by species and island, resets index for DataFrame format, and uses FacetGrid with appropriate row and col to show bars.