class_docstr: Compressed Sparse Column matrix.
  
  This can be instantiated in several ways.
  
  ``csc_matrix(D)``
      ``D`` is a rank-2 :class:`cupy.ndarray`.
  ``csc_matrix(S)``
      ``S`` is another sparse matrix. It is equivalent to ``S.tocsc()``.
  ``csc_matrix((M, N), [dtype])``
      It constructs an empty matrix whose shape is ``(M, N)``. Default dtype
      is float64.
  ``csc_matrix((data, (row, col)))``
      All ``data``, ``row`` and ``col`` are one-dimenaional
      :class:`cupy.ndarray`.
  ``csc_matrix((data, indices, indptr))``
      All ``data``, ``indices`` and ``indptr`` are one-dimenaional
      :class:`cupy.ndarray`.
  
  Args:
      arg1: Arguments for the initializer.
      shape (tuple): Shape of a matrix. Its length must be two.
      dtype: Data type. It must be an argument of :class:`numpy.dtype`.
      copy (bool): If ``True``, copies of given arrays are always used.
  
  .. seealso::
      :class:`scipy.sparse.csc_matrix`
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code: def _get_sliceXint(self, row, col):
      col = slice(col, col + 1)
      return self._major_slice(col)._minor_slice(row, copy=True)
  
imports: import cupy
  from cupy_backends.cuda.api import driver
  from cupy_backends.cuda.api import runtime
  import cupyx.scipy.sparse
  from cupyx.scipy.sparse import _base
  from cupyx.scipy.sparse import _compressed
label_desc: Use image node_id 18 for calling the csc_matrix obj's underlying member method code with example usage: obj._get_sliceXint(row, col) and returns: self