parameters: (self, axis=None, dtype=None, out=None, ddof=0,
              keepdims=np._NoValue)
return_statement: return dvar
docstring: Returns the standard deviation of the array elements along given axis.
  
          Masked entries are ignored.
  
          Refer to `numpy.std` for full documentation.
  
          See Also
          --------
          numpy.ndarray.std : corresponding function for ndarrays
          numpy.std : Equivalent function
docstring_summary: Returns the standard deviation of the array elements along given axis.
docstring_tokens: Returns the standard deviation of the array elements along given axis .
function: def std(self, axis=None, dtype=None, out=None, ddof=0,
              keepdims=np._NoValue):
          """
          Returns the standard deviation of the array elements along given axis.
  
          Masked entries are ignored.
  
          Refer to `numpy.std` for full documentation.
  
          See Also
          --------
          numpy.ndarray.std : corresponding function for ndarrays
          numpy.std : Equivalent function
          """
          kwargs = {} if keepdims is np._NoValue else {'keepdims': keepdims}
  
          dvar = self.var(axis, dtype, out, ddof, **kwargs)
          if dvar is not masked:
              if out is not None:
                  np.power(out, 0.5, out=out, casting='unsafe')
                  return out
              dvar = sqrt(dvar)
          return dvar
function_tokens: def std ( self , axis = None , dtype = None , out = None , ddof = 0 , keepdims = np . _NoValue ) : kwargs = { } if keepdims is np . _NoValue else { 'keepdims' : keepdims } dvar = self . var ( axis , dtype , out , ddof , * * kwargs ) if dvar is not masked : if out is not None : np . power ( out , 0.5 , out = out , casting = 'unsafe' ) return out dvar = sqrt ( dvar ) return dvar