# numpy.polynomial.polyutils.as_series

polynomial.polyutils.as_series(alist, trim=True)

  Return argument as a list of 1-d arrays.

  The returned list contains array(s) of dtype double, complex double, or object. A 1-d argument of shape `(N,)` is parsed into `N` arrays of size one; a 2-d argument of shape `(M,N)` is parsed into `M` arrays of size `N` (i.e., is “parsed by row”); and a higher dimensional array raises a Value Error if it is not first reshaped into either a 1-d or 2-d array.

  Parameters
    alist array_like

      A 1- or 2-d array_like

    trim boolean, optional

      When True, trailing zeros are removed from the inputs. When False, the inputs are passed through intact.

  Returns
    [a1, a2,…]list of 1-D arrays

      A copy of the input data as a list of 1-d arrays.

  Raises
    ValueError

      Raised when `as_series` cannot convert its input to 1-d arrays, or at least one of the resulting arrays is empty.

  Examples

      >>> from numpy.polynomial import polyutils as pu
      >>> a = np.arange(4)
      >>> pu.as_series(a)
      [array([0.]), array([1.]), array([2.]), array([3.])]
      >>> b = np.arange(6).reshape((2,3))
      >>> pu.as_series(b)
      [array([0., 1., 2.]), array([3., 4., 5.])]

      >>> pu.as_series((1, np.arange(3), np.arange(2, dtype=np.float16)))
      [array([1.]), array([0., 1., 2.]), array([0., 1.])]

      >>> pu.as_series([2, [1.1, 0.]])
      [array([2.]), array([1.1])]

      >>> pu.as_series([2, [1.1, 0.]], trim=False)
      [array([2.]), array([1.1, 0. ])]

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