docstr: ivy.Container static method variant of ivy.var. This method simply
  wraps the function, and so the docstring for ivy.var also applies to
  this method with minimal changes.
  
  Parameters
  ----------
  x
      input array. Should have a floating-point data type.
  key_chains
      The key-chains to apply or not apply the method to.
      Default is ``None``.
  to_apply
      If True, the method will be applied to key_chains,
      otherwise key_chains will be skipped. Default is ``True``.
  prune_unapplied
      Whether to prune key_chains for which the function was
      not applied. Default is ``False``.
  map_sequences
      Whether to also map method to sequences (lists, tuples).
      Default is ``False``.
  out
      optional output, for writing the result to.
      It must have a shape that the inputs broadcast to.
  
  Returns
  -------
  ret
     if the variance was computed over the entire array,
     a zero-dimensional array containing the variance;
     otherwise, a non-zero-dimensional array containing the
     variances. The returned array must have the same data
     type as x.
  
  Examples
  --------
  >>> x = ivy.Container(a=ivy.array([0.1, 0.2, 0.9]),
  ...                   b=ivy.array([0.7, 0.1, 0.9]))
  >>> y = ivy.Container.static_var(x)
  >>> print(y)
  {
      a:ivy.array(0.12666667),
      b:ivy.array(0.11555555)
  }
docstr_tok: ["ivy.Container","static","method","variant","of","ivy.var",".","This","method","simply","wraps","the","function",",","and","so","the","docstring","for","ivy.var","also","applies","to","this","method","with","minimal","changes",".","Parameters","--","--","--","--","--","x","input","array",".","Should","have","a","floating-point","data","type",".","key_chains","The","key-chains","to","apply","or","not","apply","the","method","to",".","Default","is","``","None","``",".","to_apply","If","True",",","the","method","will","be","applied","to","key_chains",",","otherwise","key_chains","will","be","skipped",".","Default","is","``","True","``",".","prune_unapplied","Whether","to","prune","key_chains","for","which","the","function","was","not","applied",".","Default","is","``","False","``",".","map_sequences","Whether","to","also","map","method","to","sequences","(","lists",",","tuples",")",".","Default","is","``","False","``",".","out","optional","output",",","for","writing","the","result","to",".","It","must","have","a","shape","that","the","inputs","broadcast","to",".","Returns","--","--","--","-","ret","if","the","variance","was","computed","over","the","entire","array",",","a","zero-dimensional","array","containing","the","variance",";","otherwise",",","a","non-zero-dimensional","array","containing","the","variances",".","The","returned","array","must","have","the","same","data","type","as","x",".","Examples","--","--","--","--",">",">",">","x","=","ivy.Container","(","a=ivy.array","(","[","0.1",",","0.2",",","0.9","]",")",",","...","b=ivy.array","(","[","0.7",",","0.1",",","0.9","]",")",")",">",">",">","y","=","ivy.Container.static_var","(","x",")",">",">",">","print","(","y",")","{","a",":","ivy.array","(","0.12666667",")",",","b",":","ivy.array","(","0.11555555",")","}"]
code: def _static_var(
      x: ivy.Container,
      /,
      *,
      axis: Optional[Union[int, Sequence[int], ivy.Container]] = None,
      correction: Union[int, float, ivy.Container] = 0.0,
      keepdims: Union[bool, ivy.Container] = False,
      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[ivy.Container] = None,
  ) -> ivy.Container:
      """ivy.Container static method variant of ivy.var. This method simply
      wraps the function, and so the docstring for ivy.var also applies to
      this method with minimal changes.
  
      Parameters
      ----------
      x
          input array. Should have a floating-point data type.
      key_chains
          The key-chains to apply or not apply the method to.
          Default is ``None``.
      to_apply
          If True, the method will be applied to key_chains,
          otherwise key_chains will be skipped. Default is ``True``.
      prune_unapplied
          Whether to prune key_chains for which the function was
          not applied. Default is ``False``.
      map_sequences
          Whether to also map method to sequences (lists, tuples).
          Default is ``False``.
      out
          optional output, for writing the result to.
          It must have a shape that the inputs broadcast to.
  
      Returns
      -------
      ret
         if the variance was computed over the entire array,
         a zero-dimensional array containing the variance;
         otherwise, a non-zero-dimensional array containing the
         variances. The returned array must have the same data
         type as x.
  
      Examples
      --------
      >>> x = ivy.Container(a=ivy.array([0.1, 0.2, 0.9]),
      ...                   b=ivy.array([0.7, 0.1, 0.9]))
      >>> y = ivy.Container.static_var(x)
      >>> print(y)
      {
          a:ivy.array(0.12666667),
          b:ivy.array(0.11555555)
      }
      """
      return ContainerBase.cont_multi_map_in_function(
          "var",
          x,
          key_chains=key_chains,
          axis=axis,
          correction=correction,
          keepdims=keepdims,
          to_apply=to_apply,
          prune_unapplied=prune_unapplied,
          map_sequences=map_sequences,
          out=out,
      )
  
imports: from typing import Optional, Union, List, Dict, Sequence
  import ivy
  from ivy.data_classes.container.base import ContainerBase
label_desc: Use image node_id 6 for calling the _ContainerWithStatistical obj's underlying member method code with example usage: obj._static_var() and returns: ContainerBase