docstr: ivy.Container static method variant of ivy.nanmean. This method
  simply wraps the function, and so the docstring for ivy.nanmean also
  applies to this method with minimal changes.
  
  Parameters
  ----------
  input
      Input container including arrays.
  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 in the container.
  
  Examples
  --------
  >>> a = ivy.Container(x=ivy.array([[1, ivy.nan], [3, 4]]),                                y=ivy.array([[ivy.nan, 1, 2], [1, 2, 3]])
  >>> ivy.Container.static_moveaxis(a)
  {
      x: 2.6666666666666665
      y: 1.8
  }
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code: def static_nanmean(
      input: ivy.Container,
      /,
      *,
      axis: Optional[Union[Tuple[int], int, ivy.Container]] = None,
      keepdims: Union[bool, ivy.Container] = False,
      dtype: Optional[
          Union[ivy.Dtype, ivy.NativeDtype, ivy.Container]
      ] = None,
      key_chains: Optional[
          Union[List[str], Dict[str, str], ivy.Container]
      ] = None,
      to_apply: Union[bool, ivy.Container] = True,
      prune_unapplied: Union[bool, ivy.Container] = False,
      map_sequences: Union[bool, ivy.Container] = False,
      out: Optional[Union[ivy.Array, ivy.Container]] = None,
  ) -> ivy.Container:
      """ivy.Container static method variant of ivy.nanmean. This method
          simply wraps the function, and so the docstring for ivy.nanmean also
          applies to this method with minimal changes.
  
          Parameters
          ----------
          input
              Input container including arrays.
          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 in the container.
  
          Examples
          --------
          >>> a = ivy.Container(x=ivy.array([[1, ivy.nan], [3, 4]]),\
                                  y=ivy.array([[ivy.nan, 1, 2], [1, 2, 3]])
          >>> ivy.Container.static_moveaxis(a)
          {
              x: 2.6666666666666665
              y: 1.8
          }
          """
      return ContainerBase.cont_multi_map_in_function(
          "nanmean",
          input,
          axis=axis,
          keepdims=keepdims,
          dtype=dtype,
          key_chains=key_chains,
          to_apply=to_apply,
          prune_unapplied=prune_unapplied,
          map_sequences=map_sequences,
          out=out,
      )
  
imports: from typing import Optional, Union, List, Dict, Tuple, Sequence
  import ivy
  from ivy.data_classes.container.base import ContainerBase
label_desc: Use image node_id 5 for calling the _ContainerWithStatisticalExperimental obj's underlying member method code with example usage: obj.static_nanmean() and returns: ContainerBase