datatable.Type.time64

datatable.Type.

time64

Added in version 1.0.0

The time64 type is used to represent a specific moment in time. This corresponds to datetime in Python, or timestamp in Arrow or pandas. Internally, this type is stored as a 64-bit integer containing the number of nanoseconds since the epoch (Jan 1, 1970) in UTC.

This type is not leap-seconds aware, meaning that it assumes that each day has exactly 24×3600 seconds. In practice it means that calculating time difference between two time64 moments may be off by the number of leap seconds that have occurred between them.

Currently, time64 type is not timezone-aware, addition of time zones is planned for the next release.

A time64 column converts into datetime.datetime objects in python, a pa.timestamp('ns') type in pyarrow and dtype('datetime64[ns]') in numpy and pandas.

Examples

DT = dt.Frame(["2018-01-31 03:16:57", "2021-06-15 15:44:23.951", None, "1965-11-25 19:29:00"]) DT[0] = dt.Type.time64 DT

	C0
	time64
0	2018-01-31T03:16:57
1	2021-06-15T15:44:23.951
2	NA
3	1965-11-25T19:29:00

4 rows × 1 column

dt.Type.time64.min

datetime.datetime(1677, 9, 22, 0, 12, 43, 145225)

dt.Type.time64.max

datetime.datetime(2262, 4, 11, 23, 47, 16, 854775)