code: def _post_ppc_arima(a):
      
      # if it's a result of making it to the end, it will
      # be a list of ARIMA models. Filter out the Nones
      # (the failed models)...
      if is_iterable(a):
          a = [m for m in a if m is not None]
  
      # if the list is empty, or if it was an ARIMA and it's None
      if not a:  # check for truthiness rather than None explicitly
          raise ValueError('Could not successfully fit ARIMA to input data. '
                           'It is likely your data is non-stationary. Please '
                           'induce stationarity or try a different '
                           'range of model order params. If your data is '
                           'seasonal, check the period (m) of the data.')
      # good to return
      return a
docs: If there are no suitable models, raise a ValueError.
      Otherwise, return ``a``. In the case that ``a`` is an iterable
      (i.e., it made it to the end of the function), this method will
      filter out the None values and assess whether the list is empty.
  
      Parameters
      ----------
      a : ARIMA or iterable
          The list or ARIMAs, or an ARIMA