Published Nov 28, 2022
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The load_dataset() function returns a new pandas DataFrame object that represents a sample dataset (in CSV format) from this GitHub repository.

Note: A network connection is needed to run this function since it gets information from a live URL.


seaborn.load_dataset(name, cache=True, data_home=None, **kws)

The name parameter is required while the others are optional and have default values. They are usually passed as keyword arguments.

Some of the more significant parameters are listed here:

Parameter Name Data Type Usage
name str Name of the dataset (in CSV format) from examples repository.
cache (optional) boolean Initially loads the dataset from a local cache directory, after which it saves to this cache directory if a download is needed.
data_home (optional) str Specifies the local directory where the cache data is stored; can be viewed with seaborn.get_data_home().
kws (optional) dict (keys & values) Extra keyword arguments that are passed to the pandas .read_csv() function.


The following example accesses, loads, and prints the contents of the flights.csv file via the .load_dataset() function:

import seaborn as sns
data = sns.load_dataset("flights")

This will output the following:

year month passengers
0 1949 Jan 112
1 1949 Feb 118
2 1949 Mar 132
3 1949 Apr 129
4 1949 May 121
.. ... ... ...
139 1960 Aug 606
140 1960 Sep 508
141 1960 Oct 461
142 1960 Nov 390
143 1960 Dec 432

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