watex.utils.random_sampling#

watex.utils.random_sampling(d, /, samples=None, replace=False, random_state=None, shuffle=True)[source]#

Sampling data.

Parameters

  • d ({array-like, sparse matrix} of shape (n_samples, n_features)) – Data for sampling, where n_samples is the number of samples and n_features is the number of features.

  • samples (int,optional) – Ratio or number of items from axis to return. Default = 1 if samples is None.

  • replace (bool, default=False) – Allow or disallow sampling of the same row more than once.

  • random_state (int, array-like, BitGenerator, np.random.RandomState, np.random.Generator, optional) – If int, array-like, or BitGenerator, seed for random number generator. If np.random.RandomState or np.random.Generator, use as given.

  • shuffle (bool, default=True) – Shuffle the data before sampling

Returns

  • d ({array-like, sparse matrix} of shape (n_samples, n_features))

  • samples data based on the given samples.

Examples

>>> from watex.utils.funcutils import random_sampling
>>> from watex.datasets import load_hlogs
>>> data= load_hlogs().frame
>>> random_sampling( data, samples = 7 ).shape
(7, 27)