Seaborn

⏱ Quick start

seaborn offers some specific functions for almost every kind of charts. For instance, regplot() can be used to build a scatterplot.

Note that no additional code is needed to get the nice grey background with grid and some good defaults for the dots 😍. That's 4 lines of code for a pretty decent chart 🔥!

Scatterplot section

Basic boxplot with Python and Seaborn from various data input formats.

# library & dataset
import seaborn as sns
df = sns.load_dataset('iris')

# use the function regplot to make a scatterplot
sns.regplot(x=df["sepal_length"], y=df["sepal_width"])

Basic vocabulary

Since seaborn is built on top of matplotlib, most of its concepts and vocabulary are still correct. The figure below describes the anatomy of a matplotlib charts. It names all the main components, names that you need to know to understand the documentation properly.

⚠️ Disclaimer: this figure comes from the very complete matplotlib documentation. Have a look at it for a thorough explanation on how this library works.

Anatomy of a matplotlib chart: all the basic vocabulary you need to know to understand the documentation properly

🧐 Main seaborn functions

Here is an overview of the most common seaborn functions. It provides a glimpse of they're made for, what are their parameters and links to their official doc.

Todo 😞

Customizing titles with Seaborn

Since Seaborn is built on top of Matplotlib, title customization works pretty much the same. A seaborn chart (like the one you get with sns.boxplot()) actually returns a matplotlib axes instance.

This means that you will not be able to use the usual pyplot method plt.title(), but will have to use the corresponding argument for an axes which is ax.set_title(). This is described more in depth in this dedicated post:

Add a title on a seaborn chart

Once you've understood how to add a title, customizing it should work the same as for matplotlib:

Python chart with subtitle and custom color

Add a math formula in title with Matplotlib

Control the height of the matplotlib title

Customizing axis

The exact same concept than explained for titles above applies for axes. So please read the following blogpost about axis customization with matplotlib and apply it to your seaborn chart.

Change the axis title and its appearance

Control axis labels and ticks look

Control axis limit with the xlim() function

🌈 Seaborn built-in themes

Seaborn comes with a few built-in themes. Those themes are available through the set_style() function. Here is an overview of what is offered.

Todo 😞

⭐ Seaborn graph gallery

If you're interested in a specific type of chart like boxplot or heatmap, I suggest to visit the dedicated section of the gallery. In case you're interested in what seaborn can do, here is a glimpse of what's offered in the gallery 🧐.

Histogram can be added around a scatterplot to show each variable distributions

Density chart with several displayed groups

Color dots according to a group

Show the number of observations per group

Changed the bandwidth used to compute the density

Seaborn heatmap customization: show numbers in cell

Compare the distribution of several groups on the same chart

Basic contourplot with seaborn.

Apply colors to each group and customized the scatterplot

Basic 2d density chart.

Use small multiple to compare the distribution of several groups

Histogram can be added around a 2d density chart to show x and y variable distributions

Make your violin chart horizontal to make labels more readable

Basic connected scatterplot with Python and Seaborn.

Color customization: how to select other color palettes and more