load_dataset()

Load a dataset from the library as a specified table type.

Usage

Source

load_dataset(
    dataset="exibble",
    tbl_type="pandas",
)

The Great Tables library includes several datasets that can be loaded using the load_dataset() function. The datasets can be loaded as either a Pandas DataFrame or a Polars DataFrame. These datasets are used throughout the documentation’s examples and are useful for experimenting with the library’s functionality.

Parameters

dataset: _DatasetNames = "exibble"

The name of the dataset to load. Available datasets are: "countrypops", "sza", "gtcars", "sp500", "pizzaplace", "exibble", "towny", "peeps", "films", "metro", "gibraltar", "constants", "illness", "reactions", "photolysis", and "nuclides".

tbl_type: _TblTypes = "pandas"

The type of table to generate from the dataset. Options are "pandas" (the default) and "polars".

Returns

Any

A Pandas DataFrame or Polars DataFrame, depending on the value of tbl_type.

Examples

Load the "exibble" dataset as a Pandas DataFrame (the default):

from great_tables.data import load_dataset

exibble_pd = load_dataset(dataset="exibble", tbl_type="pandas")

Load the "gtcars" dataset as a Polars DataFrame:

gtcars_pl = load_dataset(dataset="gtcars", tbl_type="polars")