Cast to DatetimeArray/Index. If possible, gives microsecond-unit DatetimeArray/Index. Otherwise gives nanosecond unit. Parameters ---------- freq : str or DateOffset, optional Target frequency. The default is 'D' for week or longer,
(self, freq=None, how: str = "start")
| 756 | return isleapyear_arr(np.asarray(self.year)) |
| 757 | |
| 758 | def to_timestamp(self, freq=None, how: str = "start") -> DatetimeArray: |
| 759 | """ |
| 760 | Cast to DatetimeArray/Index. |
| 761 | |
| 762 | If possible, gives microsecond-unit DatetimeArray/Index. Otherwise |
| 763 | gives nanosecond unit. |
| 764 | |
| 765 | Parameters |
| 766 | ---------- |
| 767 | freq : str or DateOffset, optional |
| 768 | Target frequency. The default is 'D' for week or longer, |
| 769 | 's' otherwise. |
| 770 | how : {'s', 'e', 'start', 'end'} |
| 771 | Whether to use the start or end of the time period being converted. |
| 772 | |
| 773 | Returns |
| 774 | ------- |
| 775 | DatetimeArray/Index |
| 776 | Timestamp representation of given Period-like object. |
| 777 | |
| 778 | See Also |
| 779 | -------- |
| 780 | PeriodIndex.day : The days of the period. |
| 781 | PeriodIndex.from_fields : Construct a PeriodIndex from fields |
| 782 | (year, month, day, etc.). |
| 783 | PeriodIndex.from_ordinals : Construct a PeriodIndex from ordinals. |
| 784 | PeriodIndex.hour : The hour of the period. |
| 785 | PeriodIndex.minute : The minute of the period. |
| 786 | PeriodIndex.month : The month as January=1, December=12. |
| 787 | PeriodIndex.second : The second of the period. |
| 788 | PeriodIndex.year : The year of the period. |
| 789 | |
| 790 | Examples |
| 791 | -------- |
| 792 | >>> idx = pd.PeriodIndex(["2023-01", "2023-02", "2023-03"], freq="M") |
| 793 | >>> idx.to_timestamp() |
| 794 | DatetimeIndex(['2023-01-01', '2023-02-01', '2023-03-01'], |
| 795 | dtype='datetime64[us]', freq='MS') |
| 796 | |
| 797 | The frequency will not be inferred if the index contains less than |
| 798 | three elements, or if the values of index are not strictly monotonic: |
| 799 | |
| 800 | >>> idx = pd.PeriodIndex(["2023-01", "2023-02"], freq="M") |
| 801 | >>> idx.to_timestamp() |
| 802 | DatetimeIndex(['2023-01-01', '2023-02-01'], dtype='datetime64[us]', freq=None) |
| 803 | |
| 804 | >>> idx = pd.PeriodIndex( |
| 805 | ... ["2023-01", "2023-02", "2023-02", "2023-03"], freq="2M" |
| 806 | ... ) |
| 807 | >>> idx.to_timestamp() |
| 808 | DatetimeIndex(['2023-01-01', '2023-02-01', '2023-02-01', '2023-03-01'], |
| 809 | dtype='datetime64[us]', freq=None) |
| 810 | """ |
| 811 | from pandas.core.arrays import DatetimeArray |
| 812 | |
| 813 | how = libperiod.validate_end_alias(how) |
| 814 | |
| 815 | if self.freq.base == "ns" or freq == "ns": |
no test coverage detected