code: def _sparse_nan_min_max(X, axis):
      return (
          _sparse_min_or_max(X, axis, np.fmin),
          _sparse_min_or_max(X, axis, np.fmax),
      )
  
imports: import numpy
  import scipy.sparse
  from ..utils.validation import _check_sample_weight
  from .sparsefuncs_fast import csc_mean_variance_axis0
  from .sparsefuncs_fast import csr_mean_variance_axis0
  from .sparsefuncs_fast import incr_mean_variance_axis0
label_desc: Use image node_id 17 for calling a global function with example usage: _sparse_nan_min_max(X, axis) and returns: _sparse_min_or_max,  _sparse_min_or_max