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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 truncate(self, before=None, after=None, axis=None, copy=True):
 """ Truncate a Series or DataFrame before and after some index value. This is a useful shorthand for boolean indexing based on index values above or below certain thresholds. Parameters before : date, string, int Truncate all rows before this index value. after : date, string, int Truncate all rows after this index value. axis : {0 or 'index', 1 or 'columns'}, optional Axis to truncate. Truncates the index (rows) by default. copy : boolean, default is True, Return a copy of the truncated section. Returns ------- type of caller The truncated Series or DataFrame. See Also -------- DataFrame.loc : Select a subset of a DataFrame by label. DataFrame.iloc : Select a subset of a DataFrame by position. Notes ----- If the index being truncated contains only datetime values, `before` and `after` may be specified as strings instead of Timestamps. Examples -------- A B C 1 a f k 2 b g l 3 c h m 4 d i n 5 e j o A B C 2 b g l 3 c h m 4 d i n The columns of a DataFrame can be truncated. A B 1 a f 2 b g 3 c h 4 d i 5 e j For Series, only rows can be truncated. 2 b 3 c 4 d Name: A, dtype: object The index values in ``truncate`` can be datetimes or string dates. A 2016-01-31 23:59:56 1 2016-01-31 23:59:57 1 2016-01-31 23:59:58 1 2016-01-31 23:59:59 1 2016-02-01 00:00:00 1 A 2016-01-09 23:59:56 1 2016-01-09 23:59:57 1 2016-01-09 23:59:58 1 2016-01-09 23:59:59 1 2016-01-10 00:00:00 1 Because the index is a DatetimeIndex containing only dates, we can specify `before` and `after` as strings. They will be coerced to Timestamps before truncation. A 2016-01-09 23:59:56 1 2016-01-09 23:59:57 1 2016-01-09 23:59:58 1 2016-01-09 23:59:59 1 2016-01-10 00:00:00 1 Note that ``truncate`` assumes a 0 value for any unspecified time component (midnight). This differs from partial string slicing, which returns any partially matching dates. A 2016-01-10 23:59:55 1 2016-01-10 23:59:56 1 2016-01-10 23:59:57 1 2016-01-10 23:59:58 1 2016-01-10 23:59:59 1 """


        if axis is None:
            axis = self._stat_axis_number
        axis = self._get_axis_number(axis)
        ax = self._get_axis(axis)

        # GH 17935
        # Check that index is sorted
        if not ax.is_monotonic_increasing and not ax.is_monotonic_decreasing:
            raise ValueError("truncate requires a sorted index")

        # if we have a date index, convert to dates, otherwise
        # treat like a slice
        if ax.is_all_dates:
            from pandas.core.tools.datetimes import to_datetime
            before = to_datetime(before)
            after = to_datetime(after)

        if before is not None and after is not None:
            if before > after:
                raise ValueError('Truncate: %s must be after %s' %
                                 (after, before))

        slicer = [slice(None, None)] * self._AXIS_LEN
        slicer[axis] = slice(before, after)
        result = self.loc[tuple(slicer)]

        if isinstance(ax, MultiIndex):
            setattr(result, self._get_axis_name(axis),
                    ax.truncate(before, after))

        if copy:
            result = result.copy()

        return result