framex.load#

load(name: str, *, lazy: bool = False, check_local: bool = True, cache: bool = True) → DataFrame | LazyFrame#

Loads dataset by with the given name if available.

Parameters:

name (str) – Name of the dataset to load.
lazy (bool, optional) – Lazy loading, Default is False
check_local (bool, optional) – Whether to check if the dataset is available locally Default is True
cache (bool, optional) – Whether to cache the dataset locally. Default is True

Returns:

polars.DataFrame or polars.LazyFrame

Examples

import framex as fx

iris = fx.load('iris')
iris.head()

shape: (5, 5)

sepal_length	sepal_width	petal_length	petal_width	species
f64	f64	f64	f64	str
5.1	3.5	1.4	0.2	"setosa"
4.9	3.0	1.4	0.2	"setosa"
4.7	3.2	1.3	0.2	"setosa"
4.6	3.1	1.5	0.2	"setosa"
5.0	3.6	1.4	0.2	"setosa"

Which is equivalent to direct imports.

from framex import iris

iris.head()

shape: (5, 5)

sepal_length	sepal_width	petal_length	petal_width	species
f64	f64	f64	f64	str
5.1	3.5	1.4	0.2	"setosa"
4.9	3.0	1.4	0.2	"setosa"
4.7	3.2	1.3	0.2	"setosa"
4.6	3.1	1.5	0.2	"setosa"
5.0	3.6	1.4	0.2	"setosa"

Any datasets available can be loaded via direct imports.

import framex as fx

fx.available()

{'remote': ['abortion',
  'absentee',
  'airlines',
  'airports',
  'Alligator',
  'anorexia',
  'Arrests',
  'arthritis',
  'auto',
  'avocado',
  'babies',
  'BeeStings',
  'BirdCalcium',
  'BirdNest',
  'birds',
  'Births',
  'Caterpillars',
  'cherry',
  'Chicago',
  'Chile',
  'Cholera',
  'coffee_price',
  'College',
  'CollegeDistance',
  'comics',
  'commodity_prices',
  'concrete',
  'constants',
  'Contraceptives',
  'country_codes',
  'covid_testing',
  'cpu',
  'crabs',
  'Credit',
  'defects',
  'Diabetes',
  'diamonds',
  'earthquakes',
  'epilepsy',
  'films',
  'fishing',
  'Fitch',
  'flights',
  'Forbes2000',
  'FruitFlies',
  'Gasoline',
  'Gestation',
  'gpa',
  'HealthInsurance',
  'iris',
  'Journals',
  'Ketchup',
  'london_murders',
  'Mortgage',
  'mpg',
  'Municipalities',
  'murders',
  'nba_finals',
  'nba_heights',
  'netflix',
  'oils',
  'olive',
  'oscars',
  'paris2024',
  'penguins',
  'planes',
  'pokemon',
  'population',
  'PorscheJaguar',
  'Pottery',
  'president',
  'Salaries',
  'species',
  'starbucks',
  'stars',
  'storms',
  'titanic',
  'Train',
  'UN',
  'usa_migration',
  'usa_states',
  'Utilities',
  'water',
  'weather',
  'Wells',
  'wine',
  'Yogurt'],
 'local': ['birds', 'diamonds', 'iris', 'mpg', 'penguins', 'titanic']}