FacetGrid for multi-panel views in Data Analysis Python - Mini Project: Build & Apply

FacetGrid for multi-panel views

📖 Scenario: You work as a data analyst for a car company. You have data about different cars, including their type, fuel efficiency, and horsepower. You want to compare how horsepower relates to fuel efficiency for different types of cars.

🎯 Goal: Build a multi-panel plot using FacetGrid from the seaborn library to visualize the relationship between horsepower and fuel efficiency for each car type.

📋 What You'll Learn

Create a pandas DataFrame called cars with given data

Create a FacetGrid object with cars DataFrame, using car_type as the column facet

Map a scatter plot of horsepower vs mpg on the FacetGrid

Display the plot using plt.show()

💡 Why This Matters

🌍 Real World

Multi-panel plots help compare patterns across groups, such as car types, customer segments, or product categories.

💼 Career

Data analysts and scientists use FacetGrid to explore and present data insights clearly and efficiently.

1

Create the cars DataFrame

Create a pandas DataFrame called cars with these exact columns and values: car_type with ['Sedan', 'SUV', 'Sedan', 'SUV', 'Truck', 'Truck'], horsepower with [130, 250, 115, 300, 210, 230], and mpg with [30, 20, 35, 18, 15, 14].

Data Analysis Python

import pandas as pd
# Create the cars DataFrame with specified data
# Your code here

Hint

Use pd.DataFrame with a dictionary where keys are column names and values are lists of data.

2

Create the FacetGrid object

Import seaborn as sns and matplotlib.pyplot as plt. Then create a FacetGrid object called g using the cars DataFrame, setting col='car_type' to create one panel per car type.

Data Analysis Python

import pandas as pd
cars = pd.DataFrame({
    'car_type': ['Sedan', 'SUV', 'Sedan', 'SUV', 'Truck', 'Truck'],
    'horsepower': [130, 250, 115, 300, 210, 230],
    'mpg': [30, 20, 35, 18, 15, 14]
})

import seaborn as sns
import matplotlib.pyplot as plt
# Create FacetGrid object g with col='car_type'
# Your code here

Hint

Use sns.FacetGrid with cars and col='car_type'.

3

Map scatter plot on FacetGrid

Use the map method on the FacetGrid object g to plot a scatter plot with plt.scatter, mapping horsepower on the x-axis and mpg on the y-axis.

Data Analysis Python

import pandas as pd
cars = pd.DataFrame({
    'car_type': ['Sedan', 'SUV', 'Sedan', 'SUV', 'Truck', 'Truck'],
    'horsepower': [130, 250, 115, 300, 210, 230],
    'mpg': [30, 20, 35, 18, 15, 14]
})

import seaborn as sns
import matplotlib.pyplot as plt
g = sns.FacetGrid(cars, col='car_type')
# Map scatter plot of horsepower vs mpg on g
# Your code here

Hint

Use g.map(plt.scatter, 'horsepower', 'mpg') to plot points.

4

Display the plot

Use plt.show() to display the multi-panel scatter plot.

Data Analysis Python

import pandas as pd
cars = pd.DataFrame({
    'car_type': ['Sedan', 'SUV', 'Sedan', 'SUV', 'Truck', 'Truck'],
    'horsepower': [130, 250, 115, 300, 210, 230],
    'mpg': [30, 20, 35, 18, 15, 14]
})

import seaborn as sns
import matplotlib.pyplot as plt
g = sns.FacetGrid(cars, col='car_type')
g.map(plt.scatter, 'horsepower', 'mpg')
# Show the plot
# Your code here

Hint

Call plt.show() to display the figure window.