Home - News ( United States | United Kingdom | Italy | Germany ) - Football scores

Showing content from https://www.geeksforgeeks.org/python/python-seaborn-swarmplot-method/ below:

Python - seaborn.swarmplot() method - GeeksforGeeks

Last Updated : 15 Jul, 2025

Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. There is just something extraordinary about a well-designed visualization. The colors stand out, the layers blend nicely together, the contours flow throughout, and the overall package not only has a nice aesthetic quality, but it provides meaningful insights to us as well.

Draw a categorical scatterplot with non-overlapping points. A swarm plot can be drawn on its own, but it is also a good complement to a box or violin plot in cases where you want to show all observations along with some representation of the underlying distribution. Arranging the points properly requires an accurate transformation between data and point coordinates. This means that non-default axis limits must be set *before* drawing the plot.

Syntax : seaborn.swarmplot(parameters) Parameters :

• x, y, hue : Inputs for plotting long-form data.
• data : Dataset for plotting.
• order, hue_order : Order to plot the categorical levels in, otherwise the levels are inferred from the data objects.
• dodge : To separate the strips for different hue levels along the categorical axis
• orient : Orientation of the plot (vertical or horizontal).
• color : Color for all of the elements, or seed for a gradient palette.
• palette : Colors to use for the different levels of the hue variable.
• size : Radius of the markers, in points.
• edgecolor : Color of the lines around each point.
• linewidth : Width of the gray lines that frame the plot elements.
• ax : Axes object to draw the plot onto, otherwise uses the current Axes.
• kwargs : Other keyword arguments

Returns : Returns the Axes object with the plot drawn onto it.

Below is the implementation of above method with some examples :

# importing packages
import seaborn as sns
import matplotlib.pyplot as plt

# loading dataset
data = sns.load_dataset("tips")

# plot the swarmplot
# size set to 5
sns.swarmplot(x ="day", y = "total_bill", 
              data = data, size = 5)
plt.show()

# importing packages
import seaborn as sns
import matplotlib.pyplot as plt

# loading dataset
data = sns.load_dataset("tips")

# plot the swarmplot
# hue by size
# oriented to horizontal
sns.swarmplot(y = "day", x = "total_bill", hue = "size", 
              orient = "h", data = data)
plt.show()

# importing packages
import seaborn as sns
import matplotlib.pyplot as plt

# loading dataset
data = sns.load_dataset("tips")

# plot the swarmplot
# hue by smoker
# dodge = True
sns.swarmplot(x = "sex", y = "total_bill", hue = "smoker", 
              data = data, dodge = True)
plt.show()

RetroSearch is an open source project built by @garambo | Open a GitHub Issue

Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo

HTML: 3.2 | Encoding: UTF-8 | Version: 0.7.4