Understanding the Swarm Plot
Before we dive into how to display counts, let’s first understand what a swarm plot is and how it works. A swarm plot is a type of categorical scatterplot that is used to visualize the distribution of a categorical variable. It is similar to a strip plot, but with the points adjusted to be non-overlapping, making it easier to visualize the distribution of the data.
The Problem: Counts are Not Displayed by Default
By default, the swarm plot in seaborn does not display the counts of observations in each category. This can make it difficult to interpret the plot, especially when working with large datasets. For example, consider the following code:
import seaborn as sns
import matplotlib.pyplot as plt
tips = sns.load_dataset("tips")
# Create a swarm plot
sns.swarmplot(x="day", y="total_bill", data=tips)
plt.show()
Output:
Swarm plot
This code will create a swarm plot showing the distribution of the total_bill variable by day. However, the plot does not display the counts of observations in each day.
How To Make Counts Appear In Swarm Plot For Seaborn?
Swarm plots, a type of dot plot, effectively visualize data distribution within categories. Unlike standard dot plots, swarm plots avoid overlapping points, making it easier to see individual values. However, including the count of data points in each category can further enhance the plot’s clarity. This article will guide you through the process of adding counts to a swarm plot using Seaborn.
Table of Content
- Understanding the Swarm Plot
- Steps for Adding Counts to Swarm Plot
- Step 1: Create the Swarm Plot
- Step 2: Calculate Data Point Counts
- Step 3: Annotate the Plot with Counts
- Full Implementation Code- Make Counts Appear In Swarm Plot For Seaborn