Parsing Additional Date Array Values

[HYPERTONE]

Currently we can parse Date arrays for month and year via the following:

>>> d = Date(['2000-02-29', '2018-12-25'])
>>> d.month
>>> d.year

However it would be fantastic if we could parse additional components, such as:

• Hour
• Minute
• Second
• Microsecond
• Nanosecond

I.e. Given the following Date(['2018-12-25 12:45:30.123456000'], parse all 'hour' components into a Fast Array and/or put into a new column.

[OrestZborowski-SIG]

There are additional date/time types available, such as DateTimeNano. Could those be useful here?

[HYPERTONE]

Yes!

For anyone else who stumbles upon this.

Given the following:
dtn = rt.DateTimeNano(['6/1/2022 12:00:03 AM'], from_tz='GMT', to_tz='GMT', format="%m/%d/%Y %H:%M:%S")

We can output the hour via:

dtn.hour
>> FastArray([12.00083333])

Where 0.00083333 is the hourly conversion of 3 seconds from the timestamp.

If you only wish to preserve the hour, you can type cast via the following:
dtn.hour.astype(int)

~8,000,000 rows in ~3 seconds to process. Very cool indeed!