Seaborn Cheat Sheet

Introduction

Seaborn is a popular data visualization library in Python that is used to create beautiful and informative statistical graphics. It is built on top of the Matplotlib library and provides a high-level interface for creating attractive and informative visualizations. Seaborn is widely used in data science, machine learning, and statistical analysis.

To help users get started with Seaborn, we’ve created cheat sheet that provides a quick reference guide to the most commonly used functions and methods in Seaborn. The cheat sheet is designed to be a handy reference guide for users who are new to Seaborn or who need a quick reminder of the syntax and parameters of various functions.

This Seaborn cheat sheet covers a wide range of topics, including data visualization, statistical plotting, color palettes, and data manipulation. It includes examples of how to create various types of plots, such as scatter plots, line plots, bar plots, and heatmaps.

Importing Seaborn

import seaborn as sns

Setting the Style

sns.set_style(style=None, rc=None)

Parameter	Description
style	Name of style to use, or None to reset to default
rc	Dictionary of parameter values to set

Loading Datasets

sns.load_dataset(name, cache=True, data_home=None, **kws)

Parameter	Description
name	Name of dataset to load
cache	Whether to cache downloaded file
data_home	Directory to cache downloaded files
kws	Additional keyword arguments to pass to pandas.read_csv()

Plotting Functions

Relational Plots

sns.relplot(x=None, y=None, hue=None, size=None, style=None, data=None, kind='scatter', **kwargs)

Parameter	Description
x	Column name for x-axis
y	Column name for y-axis
hue	Column name for color grouping
size	Column name for size grouping
style	Column name for style grouping
data	DataFrame to use
kind	Type of plot to draw
kwargs	Additional keyword arguments to pass to the plotting function

Categorical Plots

sns.catplot(x=None, y=None, hue=None, data=None, kind='strip', **kwargs)

Parameter	Description
x	Column name for x-axis
y	Column name for y-axis
hue	Column name for color grouping
data	DataFrame to use
kind	Type of plot to draw
kwargs	Additional keyword arguments to pass to the plotting function

Distribution Plots

sns.displot(x=None, y=None, hue=None, data=None, kind='hist', **kwargs)

Parameter	Description
x	Column name for x-axis
y	Column name for y-axis
hue	Column name for color grouping
data	DataFrame to use
kind	Type of plot to draw
kwargs	Additional keyword arguments to pass to the plotting function

Regression Plots

sns.lmplot(x=None, y=None, hue=None, data=None, **kwargs)

Parameter	Description
x	Column name for x-axis
y	Column name for y-axis
hue	Column name for color grouping
data	DataFrame to use
kwargs	Additional keyword arguments to pass to the plotting function

Matrix Plots

sns.heatmap(data=None, **kwargs)

Parameter	Description
data	DataFrame to use
kwargs	Additional keyword arguments to pass to the plotting function

Customizing Plots

Color Palettes

sns.color_palette(palette=None, n_colors=None, desat=None)

Parameter	Description
palette	Name of palette to use
n_colors	Number of colors in the palette
desat	Saturation factor for colors

Color Maps

sns.color_palette(palette=None, n_colors=None, desat=None)

Parameter	Description
palette	Name of palette to use
n_colors	Number of colors in the palette
desat	Saturation factor for colors

Axis Labels

ax.set(xlabel=None, ylabel=None)

Parameter	Description
xlabel	Label for x-axis
ylabel	Label for y-axis

Titles

ax.set_title(label=None, fontdict=None, loc=None, pad=None, **kwargs)

Parameter	Description
label	Text for title
fontdict	Dictionary of font properties
loc	Location of title
pad	Padding between title and plot
kwargs	Additional keyword arguments to pass to matplotlib.text.Text()

Legends

ax.legend(*args, **kwargs)

Parameter	Description
args	Artist objects to include in legend
kwargs	Additional keyword arguments to pass to matplotlib.legend.Legend()

Conclusion

This cheat sheet provides an overview of the most commonly used functions and parameters in Seaborn. For more information, please refer to the official Seaborn documentation.

Reference:

https://seaborn.pydata.org/