parameters: (a, axis=None, dtype=None, out=None, ddof=0, keepdims=False)
return_statement: return _api_internal.var(a, axis, dtype, ddof, keepdims, out)
docstring: Compute the variance along the specified axis.
      Returns the variance of the array elements, a measure of the spread of a
      distribution.  The variance is computed for the flattened array by
      default, otherwise over the specified axis.
  
      Parameters
      ----------
      a : ndarray
          Array containing numbers whose variance is desired.  If `a` is not an
          array, a conversion is attempted.
      axis : None or int or tuple of ints, optional
          Axis or axes along which the variance is computed.  The default is to
          compute the variance of the flattened array.
          .. versionadded:: 1.7.0
          If this is a tuple of ints, a variance is performed over multiple axes,
          instead of a single axis or all the axes as before.
      dtype : data-type, optional
          Type to use in computing the variance.
          For arrays of integer type the default is `float32` or 'float64',
          When npx.is_np_default_dtype() returns False, default dtype is float32,
          When npx.is_np_default_dtype() returns True, default dtype is float64;
          For arrays of float types it is the same as the array type.
      out : ndarray, optional
          Alternate output array in which to place the result.  It must have
          the same shape as the expected output, but the type is cast if
          necessary.
      ddof : int, optional
          "Delta Degrees of Freedom": the divisor used in the calculation is
          ``N - ddof``, where ``N`` represents the number of elements. By
          default `ddof` is zero.
      keepdims : bool, optional
          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 input array.
          If the default value is passed, then `keepdims` will not be
          passed through to the `var` method of sub-classes of
          `ndarray`, however any non-default value will be.  If the
          sub-class' method does not implement `keepdims` any
          exceptions will be raised.
  
      Returns
      -------
      variance : ndarray, see dtype parameter above
          If ``out=None``, returns a new array containing the variance;
          otherwise, a reference to the output array is returned.
  
      Examples
      --------
      >>> a = np.array([[1, 2], [3, 4]])
      >>> np.var(a)
      array(1.25)
      >>> np.var(a, axis=0)
      array([1.,  1.])
      >>> np.var(a, axis=1)
      array([0.25,  0.25])
  
      >>> a = np.zeros((2, 512*512), dtype=np.float32)
      >>> a[0, :] = 1.0
      >>> a[1, :] = 0.1
      >>> np.var(a)
      array(0.2025)
      >>> np.var(a, dtype=np.float64)
      array(0.2025, dtype=float64)
      >>> ((1-0.55)**2 + (0.1-0.55)**2)/2
      0.2025
docstring_summary: Compute the variance along the specified axis.
      Returns the variance of the array elements, a measure of the spread of a
      distribution.  The variance is computed for the flattened array by
      default, otherwise over the specified axis.
docstring_tokens: Compute the variance along the specified axis . Returns the variance of the array elements a measure of the spread of a distribution . The variance is computed for the flattened array by default otherwise over the specified axis .
function: def var(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False):  # pylint: disable=too-many-arguments
      """
      Compute the variance along the specified axis.
      Returns the variance of the array elements, a measure of the spread of a
      distribution.  The variance is computed for the flattened array by
      default, otherwise over the specified axis.
  
      Parameters
      ----------
      a : ndarray
          Array containing numbers whose variance is desired.  If `a` is not an
          array, a conversion is attempted.
      axis : None or int or tuple of ints, optional
          Axis or axes along which the variance is computed.  The default is to
          compute the variance of the flattened array.
          .. versionadded:: 1.7.0
          If this is a tuple of ints, a variance is performed over multiple axes,
          instead of a single axis or all the axes as before.
      dtype : data-type, optional
          Type to use in computing the variance.
          For arrays of integer type the default is `float32` or 'float64',
          When npx.is_np_default_dtype() returns False, default dtype is float32,
          When npx.is_np_default_dtype() returns True, default dtype is float64;
          For arrays of float types it is the same as the array type.
      out : ndarray, optional
          Alternate output array in which to place the result.  It must have
          the same shape as the expected output, but the type is cast if
          necessary.
      ddof : int, optional
          "Delta Degrees of Freedom": the divisor used in the calculation is
          ``N - ddof``, where ``N`` represents the number of elements. By
          default `ddof` is zero.
      keepdims : bool, optional
          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 input array.
          If the default value is passed, then `keepdims` will not be
          passed through to the `var` method of sub-classes of
          `ndarray`, however any non-default value will be.  If the
          sub-class' method does not implement `keepdims` any
          exceptions will be raised.
  
      Returns
      -------
      variance : ndarray, see dtype parameter above
          If ``out=None``, returns a new array containing the variance;
          otherwise, a reference to the output array is returned.
  
      Examples
      --------
      >>> a = np.array([[1, 2], [3, 4]])
      >>> np.var(a)
      array(1.25)
      >>> np.var(a, axis=0)
      array([1.,  1.])
      >>> np.var(a, axis=1)
      array([0.25,  0.25])
  
      >>> a = np.zeros((2, 512*512), dtype=np.float32)
      >>> a[0, :] = 1.0
      >>> a[1, :] = 0.1
      >>> np.var(a)
      array(0.2025)
      >>> np.var(a, dtype=np.float64)
      array(0.2025, dtype=float64)
      >>> ((1-0.55)**2 + (0.1-0.55)**2)/2
      0.2025
      """
      return _api_internal.var(a, axis, dtype, ddof, keepdims, out)
function_tokens: def var ( a , axis = None , dtype = None , out = None , ddof = 0 , keepdims = False ) : # pylint: disable=too-many-arguments return _api_internal . var ( a , axis , dtype , ddof , keepdims , out )