Seaborn.get_dataset_names() method

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Seaborn.get_dataset_names() method is used to view the names of all the in built datasets from the seaborn library. For the purpose of describing seaborn or creating reproducible examples for bug complaints, this function offers rapid access to a few example datasets.

It is not required for everyday use. To create an appropriate ordering for categorical variables, a minor amount of preprocessing has been conducted to some of the datasets.

Syntax

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

seaborn.get_dataset_names()

Parameters

This method takes no parameter

Return value

This method returns a list of all the names of the datasets inbuilt in Seaborn.

Seaborn.get_dataset_names() method

In order to plot graphs, we require data and in case, data is not available readily for your use in the required format and containing desired data, you can use the datasets present in the Seaborn library.

Seaborn contains various default datasets in addition to being a statistical charting toolkit. We'll use the one of the in-built datasets as an example of a default dataset.

In order to view all the datasets available in the Seaborn library, the following method can be used to do so.

Example 1

The get_dataset_names() method helps to retrieve all the names of the in-built datasets available in Seaborn.

import seaborn as sns
list = sns.get_dataset_names()
print(list)

Output

Upon, executing this example, the following list is obtained.

['anagrams', 'anscombe', 'attention', 'brain_networks', 'car_crashes', 'diamonds', 'dots', 'exercise', 'flights', 'fmri', 'gammas', 'geyser', 'iris', 'mpg', 'penguins', 'planets', 'taxis', 'tips', 'titanic']

Using any one of these in built datasets, graphs can be plotted. To load datasets, the seaborn.load_dataset() method can be used to do so.

The load_dataset() method helps to load the dataset with the name into a data structure. For the purpose of this example, we will load the tips dataset.

Tips=seaborn.load_dataset('tips')

The above line of code helps to load the dataset with the name 'tips' into a data structure called tips. Thus, this method helps in loading the datasets from the library.

Example 2

Following is an example which loads the titanic dataset using get_dataset_names() method −

import seaborn as sns
import matplotlib.pyplot as plt
list = sns.get_dataset_names()
name = list[21]
dts= sns.load_dataset(name)
dts.head()
sns.relplot(data=dts, x="age", y="fare")
plt.show()

Output

Following is the output of the above example −

Example 3

Following is an example which loads the tips dataset using get_dataset_names() method −

import seaborn as sns
import matplotlib.pyplot as plt
list = sns.get_dataset_names()
name = list[20]
tips=sns.load_dataset(name)
tips.head()
sns.catplot(data=tips,x="sex",y="tip",hue="time",height=5, aspect=.8)
plt.show()

Output

This generates the following output −

Example 4

Let us see another example −

import seaborn as sns
import matplotlib.pyplot as plt
list = sns.get_dataset_names()
name = list[11]
print(name)
exercise=sns.load_dataset("exercise")
exercise.head()
g=sns.PairGrid(exercise)
g.map_upper(sns.scatterplot)
g.map_lower(sns.kdeplot)
g.map_diag(sns.ecdfplot)
plt.show()

Output

On executing, the above example generates the following example −