code: def _getnnz(self, axis=None):
      if axis is None or (axis == 0 and self.ndim == 1):
          nnz = len(self.data)
          if any(len(idx) != nnz for idx in self.indices):
              raise ValueError(
                  "all index and data arrays must have the "
                  "same length"
              )
  
          if self.data.ndim != 1 or any(
              idx.ndim != 1 for idx in self.indices
          ):
              raise ValueError(
                  "row, column, and data arrays must be 1-D"
              )
  
          return int(nnz)
  
      if axis < 0:
          axis += self.ndim
      if axis >= self.ndim:
          raise ValueError("axis out of bounds")
      if self.ndim > 2:
          raise NotImplementedError(
              "per-axis nnz for COO arrays with >2 "
              "dimensions is not supported"
          )
      return np.bincount(
          downcast_intp_index(self.indices[1 - axis]),
          minlength=self.shape[1 - axis],
      )
  
imports: import math
  from warnings import warn
  import numpy
  from ._matrix import spmatrix
  from ._sparsetools import coo_tocsr, coo_todense, coo_matvec
  from ._base import issparse, SparseEfficiencyWarning, _spbase, sparray
  from ._data import _data_matrix, _minmax_mixin
  from ._sputils import upcast, upcast_char, to_native, isshape, getdtype, getdata, downcast_intp_index, get_index_dtype, check_shape, check_reshape_kwargs
  import operator
label_desc: Use image node_id 7 for calling the _coo_base obj's underlying member method code with example usage: obj._getnnz(axis) and returns: np, int