Drawing a rugplot using Python and seaborn

Overview:

The rugplot() function of seaborn helps visualising data points by providing one more visual aid through ticks in X, Y axes and through the hue semantics of the ticks.

Example:

# Example Python program that creates a seaborn plot with
# a rugplot
# Data Courtesy: https://archive.ics.uci.edu/ml/datasets/Automobile
import pandas as pds
import seaborn as sns
import matplotlib.pyplot as plt

# Import the Automobile Data Set into a DataFrame
carData = pds.read_csv('/Users/selvamvinod/Downloads/cardata.csv');
print(carData);

# Create a scatter plot
sns.scatterplot(x="length", y="price", data=carData, hue="fuel-type");

# Add ticks to the scatter plot axes
sns.rugplot(x="length", y="price", data=carData, hue="fuel-type");

plt.title("Scatterplot between the variables: length and price of cars");
plt.show();

Output:

symboling normalized-losses make ... city-mpg highway-mpg price

0 3 ? alfa-romero ... 21 27 13495

1 3 ? alfa-romero ... 21 27 16500

2 1 ? alfa-romero ... 19 26 16500

3 2 164 audi ... 24 30 13950

4 2 164 audi ... 18 22 17450

.. ... ... ... ... ... ... ...

196 -1 95 volvo ... 23 28 16845

197 -1 95 volvo ... 19 25 19045

198 -1 95 volvo ... 18 23 21485

199 -1 95 volvo ... 26 27 22470

200 -1 95 volvo ... 19 25 22625

Drawing a rugplot using Python and seaborn