code: def append(self, to_append, ignore_index=False, verify_integrity=False):
          
          from pandas.core.reshape.concat import concat
  
          if isinstance(to_append, (list, tuple)):
              to_concat = [self] + to_append
          else:
              to_concat = [self, to_append]
          return concat(to_concat, ignore_index=ignore_index,
                        verify_integrity=verify_integrity)
docs: Concatenate two or more Series.
  
          Parameters
          ----------
          to_append : Series or list/tuple of Series
              Series to append with self.
          ignore_index : bool, default False
              If True, do not use the index labels.
  
              .. versionadded:: 0.19.0
  
          verify_integrity : bool, default False
              If True, raise Exception on creating index with duplicates.
  
          Returns
          -------
          Series
              Concatenated Series.
  
          See Also
          --------
          concat : General function to concatenate DataFrame, Series
              or Panel objects.
  
          Notes
          -----
          Iteratively appending to a Series can be more computationally intensive
          than a single concatenate. A better solution is to append values to a
          list and then concatenate the list with the original Series all at
          once.
  
          Examples
          --------
          >>> s1 = pd.Series([1, 2, 3])
          >>> s2 = pd.Series([4, 5, 6])
          >>> s3 = pd.Series([4, 5, 6], index=[3, 4, 5])
          >>> s1.append(s2)
          0    1
          1    2
          2    3
          0    4
          1    5
          2    6
          dtype: int64
  
          >>> s1.append(s3)
          0    1
          1    2
          2    3
          3    4
          4    5
          5    6
          dtype: int64
  
          With `ignore_index` set to True:
  
          >>> s1.append(s2, ignore_index=True)
          0    1
          1    2
          2    3
          3    4
          4    5
          5    6
          dtype: int64
  
          With `verify_integrity` set to True:
  
          >>> s1.append(s2, verify_integrity=True)
          Traceback (most recent call last):
          ...
          ValueError: Indexes have overlapping values: [0, 1, 2]