CLN: Refactor PeriodArray._format_native_types to use DatetimeArray

[TomAugspurger]

Once we have a DatetimeArray, we'll almost be able to share the implementation of _format_native_types. The main sticking point is that Period has a different default date format. It only prints the resolution necessary for the frequency.

In [2]: pd.Timestamp('2000')
Out[2]: Timestamp('2000-01-01 00:00:00')

In [3]: pd.Period('2000', 'D')
Out[3]: Period('2000-01-01', 'D')

In [4]: pd.Period('2000', 'H')
Out[4]: Period('2000-01-01 00:00', 'H')

We could refactor period_format in _libs/tslibs/period.pyx into two functions

1. get_period_format_string(freq). Get the format string like %Y for a given freq.
2. period_format(value, fat): given a freq string, format the values.

Looking at that, WK frequency may cause some issues, not sure.

In [5]: pd.Period('2000', 'W-SUN')
Out[5]: Period('1999-12-27/2000-01-02', 'W-SUN')

If we can do that, then PeriodArray._format_native_types can be

    def _format_native_types(self, na_rep=u'NaT', date_format=None, **kwargs):
        """ actually format my specific types """
        return self.to_timestamp()._format_native_types(na_rep=na_rep,
                                                        date_format=date_format,
                                                        **kwargs)

This is blocked by #23185