code: def unnest(self, data, fit=False):
          
          with timer('unnest %s' % self.name, logging.DEBUG):
              raw = self.series(data)
              # lengths of every sequence
              lengths = [0 if x is None or (isinstance(x, float) and numpy.isnan(x)) else len(x) for x in raw.values]
              if fit and self.sequence_length is None:
                  self.sequence_length = numpy.max(lengths)
              # Make them all the same size
              def fill_x(x, length):
                  x_new = numpy.empty(length, dtype='float')
                  x_new[:] = numpy.nan
                  if x is None or (isinstance(x, float) and numpy.isnan(x)):
                      return x_new
                  fill_length = min(len(x), length)
                  x_new[0:fill_length] = x[0:fill_length]
                  return x_new
              same_size = [fill_x(x, self.sequence_length) for x in raw.values]
              # Flatten
              flattened = [item for sublist in same_size for item in sublist]
              return pandas.DataFrame({self.column: flattened})
docs: :param data: a dataframe containing a column to be unnested
          :param fit: if True, self.sequence_length will exactly accomodate the largest sequence length
          :return: 1D array of values with length = rows * sequence_length