Seaborn.FacetGrid() method

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The Seaborn.FacetGrid() method is useful when you want to visualize the distribution of a variable or the relationship between multiple variables separately within subsets of your dataset. Row, Col, and Hue are the three possible dimensions that can be used to draw a FacetGrid. The first two clearly correspond to the array of axes that is produced.

With the hue parameter, which depicts several data subsets in various colors, it can also express levels of a third variable. In contrast to axes-level functions that receive hue, this just draws subsets on top of one another and does not tailor the hue parameter for the particular display. It uses color to resolve components on a third dimension.

Syntax

Following is the syntax of the seaborn.FacetGrid() method −

class seaborn.FacetGrid(**kwargs)
Multi-plot grid for plotting conditional relationships.
__init__(self, data, *, row=None, col=None, hue=None, col_wrap=None, sharex=True, sharey=True, height=3, aspect=1, palette=None, row_order=None, col_order=None, hue_order=None, hue_kws=None, dropna=False, legend_out=True, despine=True, margin_titles=False, xlim=None, ylim=None, subplot_kws=None, gridspec_kws=None, size=None)

Parameters

Some of the parameters of the seaborn.FacetGrid() method are discussed below.

let us load the seaborn library and the dataset before moving on to the developing the plots.

Loading the seaborn library

To load or import the seaborn library the following line of code can be used.

Import seaborn as sns

Loading the dataset

in this article, we will make use of the Titanic dataset inbuilt in the seaborn library. the following command is used to load the dataset.

titanic=sns.load_dataset("titanic")

The below mentioned command is used to view the first 5 rows in the dataset. This enables us to understand what variables can be used to plot a graph.

titanic.head()

the below is the output for the above piece of code.

index,survived,pclass,sex,age,sibsp,parch,fare,embarked,class,who,adult_male,deck,embark_town,alive,alone
0,0,3,male,22.0,1,0,7.25,S,Third,man,true,NaN,Southampton,no,false
1,1,1,female,38.0,1,0,71.2833,C,First,woman,false,C,Cherbourg,yes,false
2,1,3,female,26.0,0,0,7.925,S,Third,woman,false,NaN,Southampton,yes,true

Now that we have loaded the dataset, we will explore a few examples.

Example 1

In this example, we will see how to produce a simple facet grid by passing the dataset, and col and row parameters to the FacetGrid() method.

import seaborn as sns
import matplotlib.pyplot as plt
titanic=sns.load_dataset("titanic")
titanic.head()
sns.FacetGrid(titanic, col="sex", row="class")
plt.show()

Output

The output obtained is as follows −

Example 2

In order to draw a plot on every facet, pass a function and the name of one or more columns in the data frame to FacetGrid.map(). In this example, we will do the same. We are using the titanic dataset and we will plot scatterplots in all the facets.

import seaborn as sns
import matplotlib.pyplot as plt
titanic=sns.load_dataset("titanic")
titanic.head()
grid = sns.FacetGrid(titanic, col="sex", row="class")
grid.map(sns.scatterplot, "age", "fare")
plt.show()

the above lines of code can be used to implement the scenario explained and the output obtained is given below.

Output

Example 3

Now we will plot a histogram using the hsitplot() method in all the facets and also use the add_legend to all the legend to the plots displayed. This can be done using the below lines of code. Firstly, we will draw facets and draw histplot in those facets. Then we will add the legend to the facet. In order to do this the facetgrid will be stored in a variable called grid.

import seaborn as sns
import matplotlib.pyplot as plt
titanic=sns.load_dataset("titanic")
titanic.head()
grid = sns.FacetGrid(titanic, col="class", hue="sex")
grid.map_dataframe(sns.histplot, x="age", y="fare")
grid.add_legend()
plt.show()

Output

The output obtained is as follows −

Example 4

We will understand the use of savefig() method in python. This can be used to save any plot obtained as an image for your personal use. Your plot must be saved in a variable such as grid just like in the above example, then we will apply the savefig() method on it and obtain the image. The savefig() method takes an argument which is the name of the file to save the plot as. In the below code, the plot is being saved as “facetplot.png”.

import seaborn as sns
import matplotlib.pyplot as plt
titanic=sns.load_dataset("titanic")
titanic.head()
grid.savefig("facetplot.png")
plt.show()