pandas.Series.sparse.from_coo — pandas 3.0.0.dev0+2103.g41968a550a documentation (original) (raw)

classmethod Series.sparse.from_coo(A, dense_index=False)[source]#

Create a Series with sparse values from a scipy.sparse.coo_matrix.

This method takes a scipy.sparse.coo_matrix (coordinate format) as input and returns a pandas Series where the non-zero elements are represented as sparse values. The index of the Series can either include only the coordinates of non-zero elements (default behavior) or the full sorted set of coordinates from the matrix if dense_index is set to True.

Parameters:

Ascipy.sparse.coo_matrix

The sparse matrix in coordinate format from which the sparse Series will be created.

dense_indexbool, default False

If False (default), the index consists of only the coords of the non-null entries of the original coo_matrix. If True, the index consists of the full sorted (row, col) coordinates of the coo_matrix.

Returns:

sSeries

A Series with sparse values.

Examples

from scipy import sparse

A = sparse.coo_matrix( ... ([3.0, 1.0, 2.0], ([1, 0, 0], [0, 2, 3])), shape=(3, 4) ... ) A <COOrdinate sparse matrix of dtype 'float64' with 3 stored elements and shape (3, 4)>

A.todense() matrix([[0., 0., 1., 2.], [3., 0., 0., 0.], [0., 0., 0., 0.]])

ss = pd.Series.sparse.from_coo(A) ss 0 2 1.0 3 2.0 1 0 3.0 dtype: Sparse[float64, nan]