Seaborn.set_context() method

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The Seaborn.set_context() method is used to set the parameters that control the scaling of plot elements. By using this the general style is unaffected, although it does influence things like the size of the labels, lines, and other plot points. The rcParams system in matplotlib is used to achieve this.

The terms "paper," "talk," and "poster" are versions of the notebook parameters scaled by different values, while "notebook" serves as the base context. Additionally, font elements may be scaled separately from the other values.

Syntax

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

seaborn.set_context(context=None, font_scale=1, rc=None)

Parameters

The parameters of the set_context() 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 Tips dataset inbuilt in the seaborn library. the following command is used to load the dataset.

tips=sns.load_dataset("tips")

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.

tips.head()

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

index,total_bill,tip,sex,smoker,day,time,size
0,16.99,1.01,Female,No,Sun,Dinner,2
1,10.34,1.66,Male,No,Sun,Dinner,3
2,21.01,3.5,Male,No,Sun,Dinner,3
3,23.68,3.31,Male,No,Sun,Dinner,2
4,24.59,3.61,Female,No,Sun,Dinner,4

Now that we have loaded the data, we will move onto understanding how the method works in the following examples.

Example 1

We will plot a graph after setting the context. The context can have values paper, notebook, talk and poster. In this example, we are setting the context to paper and then a bar plot is generated by passing lists to the x,y parameters of bar plot.

import seaborn as sns
import matplotlib.pyplot as plt
tips=sns.load_dataset("tips")
tips.head()
sns.set_context("paper")
sns.barplot(x=[0, 1, 2], y=[0.5, 3.6, 9.4])
plt.show()

Output

the output generated is as follows,

Example 2

In this example, we will use the font_scale parameter. This parameter is used to increase or decrease the font size in the plot. In this example, 1.5 is passed to the font_scale.

import seaborn as sns
import matplotlib.pyplot as plt
tips=sns.load_dataset("tips")
tips.head()
sns.set_context("poster", font_scale=1.5)
sns.barplot(x=[0, 1, 2], y=[0.5, 3.6, 9.4])
plt.show()

Output

The output is as follows,

Example 3

In this example, we will use the tips dataset and set a context and later plot a line plot for the dataset using the context. The context is set to notebook and one of the rc parameters, lines.linewidth is set to 3 to show how rc parameters can be used.

Then tips dataset and columns from this dataset are passed to the lineplot.

import seaborn as sns
import matplotlib.pyplot as plt
tips=sns.load_dataset("tips")
tips.head()
sns.set_context("notebook", rc={"lines.linewidth": 3})
sns.lineplot(data=tips,x="tip",y="total_bill")
plt.show()

Output

The output obtained is as follows −