Seaborn Dot Plot Hue - Python

Seaborn is a popular data visualization library for Python, which helps to create beautiful and informative plots easily. One of the key features of Seaborn is the ability to create dot plots with hue, which allows you to visualize the relationship between two variables, while highlighting a third categorical variable.

Dot Plot with Hue

A dot plot is a simple yet effective way to display the frequency or distribution of a set of data values. Seaborn dot plot with hue is an enhanced version of the standard dot plot, which separates the data by a categorical variable.

Here's an example of how to create a dot plot with Seaborn using the .stripplot() function:

import seaborn as sns
import matplotlib.pyplot as plt

# Load data
tips = sns.load_dataset("tips")

# Create dot plot with hue
sns.stripplot(x="day", y="total_bill", hue="sex", data=tips, jitter=True)

# Show plot
plt.show()

In this example, we're using the tips dataset that comes with Seaborn. We're creating a dot plot with day on the x-axis, total_bill on the y-axis, and sex as the hue variable. The jitter parameter is used to add some random noise to the plot, which helps to display overlapping dots.

As you can see from the plot, the dots are separated by gender, and we can see the distribution of total bills over each day of the week.

Conclusion

Seaborn dot plot with hue is a powerful way to visualize the relationship between two variables while highlighting a categorical variable. By using Seaborn's built-in functions, we can create stunning and informative dot plots in just a few lines of code.