sklearn.utils.shuffle(*arrays, **options)
[source]
Shuffle arrays or sparse matrices in a consistent way
This is a convenience alias to resample(*arrays, replace=False)
to do random permutations of the collections.
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See also
It is possible to mix sparse and dense arrays in the same run:
>>> X = np.array([[1., 0.], [2., 1.], [0., 0.]]) >>> y = np.array([0, 1, 2]) >>> from scipy.sparse import coo_matrix >>> X_sparse = coo_matrix(X) >>> from sklearn.utils import shuffle >>> X, X_sparse, y = shuffle(X, X_sparse, y, random_state=0) >>> X array([[0., 0.], [2., 1.], [1., 0.]]) >>> X_sparse <3x2 sparse matrix of type '<... 'numpy.float64'>' with 3 stored elements in Compressed Sparse Row format> >>> X_sparse.toarray() array([[0., 0.], [2., 1.], [1., 0.]]) >>> y array([2, 1, 0]) >>> shuffle(y, n_samples=2, random_state=0) array([0, 1])
sklearn.utils.shuffle
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Licensed under the 3-clause BSD License.
http://scikit-learn.org/stable/modules/generated/sklearn.utils.shuffle.html