code: def nanmean(
      a: ivy.Array,
      /,
      *,
      axis: Optional[Union[Tuple[int], int]] = None,
      keepdims: bool = False,
      dtype: Optional[Union[ivy.Dtype, ivy.NativeDtype]] = None,
      out: Optional[ivy.Array] = None,
  ) -> ivy.Array:
      """Compute the mean of all non-NaN elements along the specified dimensions.
  
      Parameters
      ----------
      a
          Input array.
      axis
          Axis or axes along which the means are computed.
          The default is to compute the mean of the flattened array.
      keepdims
          If this is set to True, the axes which are reduced are left in the result
          as dimensions with size one. With this option, the result will broadcast
          correctly against the original a. If the value is anything but the default,
          then keepdims will be passed through to the mean or sum methods of sub-classes
          of ndarray. If the sub-classes methods does not implement keepdims any
          exceptions will be raised.
      dtype
          The desired data type of returned tensor. Default is None.
      out
          optional output array, for writing the result to.
  
      Returns
      -------
      ret
          The nanmean of the array elements.
  
      Examples
      --------
      >>> a = ivy.array([[1, ivy.nan], [3, 4]])
      >>> ivy.nanmean(a)
      2.6666666666666665
      >>> ivy.nanmean(a, axis=0)
      ivy.array([2.,  4.])
      """
      return ivy.current_backend(a).nanmean(
          a, axis=axis, keepdims=keepdims, dtype=dtype, out=out
      )
  
file_path: ivy/ivy/functional/ivy/experimental/statistical.py
imports: from typing import Optional, Union, Tuple, Sequence
  import ivy
  from ivy.func_wrapper import handle_array_function, handle_out_argument, to_native_arrays_and_back, handle_array_like_without_promotion, handle_nestable, infer_dtype, handle_device, handle_backend_invalid
  from ivy.utils.exceptions import handle_exceptions
label_desc: Use image node_id 3 for calling a global function with example usage: nanmean() and returns: ivy