indexable (original) (raw)

sklearn.utils.indexable(*iterables)[source]#

Make arrays indexable for cross-validation.

Checks consistent length, passes through None, and ensures that everything can be indexed by converting sparse matrices to csr and converting non-iterable objects to arrays.

Parameters:

*iterables{lists, dataframes, ndarrays, sparse matrices}

List of objects to ensure sliceability.

Returns:

resultlist of {ndarray, sparse matrix, dataframe} or None

Returns a list containing indexable arrays (i.e. NumPy array, sparse matrix, or dataframe) or None.

Examples

from sklearn.utils import indexable from scipy.sparse import csr_matrix import numpy as np iterables = [ ... [1, 2, 3], np.array([2, 3, 4]), None, csr_matrix([[5], [6], [7]]) ... ] indexable(*iterables) [[1, 2, 3], array([2, 3, 4]), None, <...Sparse...dtype 'int64'...shape (3, 1)>]