Visualization with Swarm Plots
Explore how to use Seaborn's swarm plots to visualize the distribution of categorical data points without overlap. Learn to customize plots by adding multiple variables, adjusting orientation, colors, and combining swarm plots with violin and box plots for enriched data insights.
Overview
The swarm plot represents the distribution of data in the form of data points. It’s sometimes called a bee swarm plot, because if we visualize the plots with each data point connected, they seem like a swarm of bees. The data is sorted first, and then we have an entry in the plot for each data point. The key feature is that none of the points overlap with each other.
Plotting swarm plots
We’ll use the penguins dataset in this lesson—it’s been loaded into the variable penguins_df (after removing the null values). Let’s begin our visualizations. We create a swarm plot using the sns.swarmplot() function and pass x='body_mass_g' and data= penguins_df in the function. ...