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# pandas.Series.sparse.from_coo

classmethod Series.sparse.from_coo(A, dense_index=False)

  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:
    A scipy.sparse.coo_matrix

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

    dense_index bool, 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:
    s Series

      A Series with sparse values.

  See also

  `DataFrame.sparse.from_spmatrix`

    Create a new DataFrame from a scipy sparse matrix.

  `scipy.sparse.coo_matrix`

    A sparse matrix in COOrdinate format.

  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]