![]() ![]() This can be done using the set_style() and set_palette() functions, respectively. Seaborn makes it easy to apply a style and a color palette to our visualizations. In the following section, you’ll learn how to modify the styling of your plot. We can see that by using just two lines of code, we were able to create and display a boxplot! Because Seaborn is designed to handle Pandas DataFrames easily, we can simply refer to the column names directly, as long as we pass the DataFrame into the data parameter.īy default, the styling of a Seaborn boxplot is a little uninspiring. Sns.boxplot(data=df, x='day', y='total_bill')Ī basic Seaborn boxplot created with the sns.boxplot() function Let’s see how we’d do this in Python: # Creating our first boxplot Let’s start by creating a boxplot that breaks the data out by day column on the x-axis and shows the total_bill column on the y-axis. How to Create a Boxplot in SeabornĬreating a boxplot in Seaborn is made easy by using the sns.boxplot() function. Now that we have a dataset loaded, let’s dive into how to use Seaborn to create a boxplot. # total_bill tip sex smoker day time size Let’s load the dataset using the Seaborn load_dataset() function and take a quick look at it: # Loading a Sample Dataset Seaborn comes with a number of built-in datasets, including a valuable tips dataset that shows tips given to restaurant workers. To follow along with this tutorial, let’s load a sample dataset that we can use throughout this tutorial.
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