Data Visualization of Car Fuel Efficiency

What is the relationship between the power of a car's engine ("horsepower") and its fuel efficiency ("mpg")? And how does this relationship vary by the number of cylinders ("cylinders") the car has? Let's find out.

In this project, we'll explore mpg dataset, which contains one row per car model and includes information such as the year the car was made, the number of miles per gallon ("M.P.G.") it achieves, the power of its engine (measured in "horsepower"), and its country of origin.

Import Libraries and data

# Import Matplotlib and Seaborn
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd

mpg = pd.read_csv('mpg.csv')

print(mpg.head())

Plot Style

sns.set_style("whitegrid")
sns.set_palette("Spectral")

Horsepower vs. mpg

# Create scatter plot of horsepower vs. mpg
g = sns.relplot(x='horsepower', y='mpg', style='origin', data=mpg, size='cylinders', hue='cylinders')

# Add a title
g.fig.suptitle("Car Horsepower vs. mpg")
plt.show()

Year vs. mpg

# Create line plot
g = sns.relplot(x='model_year', y='mpg', style="origin",
            hue="origin", data=mpg, kind='line')

# Add a title
g.fig.suptitle("Model year vs. mpg")

# Show plot
plt.show()

Model year vs. Horsepower

# Add markers and make each line have the same style
g = sns.relplot(x="model_year", y="horsepower",
            data=mpg, kind="line",
            ci=None, style="origin",
            hue="origin", markers=True, dashes=False)

# Add a title
g.fig.suptitle("Model year vs. Horsepower")

# Show plot
plt.show()

Reference:

https://www.datacamp.com/