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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def append(self, to_append, ignore_index=False, verify_integrity=False):
 """ 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 -------- 0 1 1 2 2 3 0 4 1 5 2 6 dtype: int64 0 1 1 2 2 3 3 4 4 5 5 6 dtype: int64 With `ignore_index` set to True: 0 1 1 2 2 3 3 4 4 5 5 6 dtype: int64 With `verify_integrity` set to True: Traceback (most recent call last):
 ValueError: Indexes have overlapping values: [0, 1, 2] """

        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)