[FIX] pandas_compat: fix conversion of datetime series #5547
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Codecov Report
@@ Coverage Diff @@
## master #5547 +/- ##
==========================================
- Coverage 86.38% 85.90% -0.48%
==========================================
Files 304 313 +9
Lines 61801 65353 +3552
==========================================
+ Hits 53386 56143 +2757
- Misses 8415 9210 +795 |
ajdapretnar
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Aug 13, 2021
| if (dt_nonnat.dt.floor("d") == dt_nonnat).all(): | ||
| # all times are 00:00:00.0 - pure date | ||
| return 1, 0 | ||
| elif (dt_nonnat.dt.date == pd.Timestamp("now").date()).all(): |
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Does pandas automatically assume today's date if only time is present?
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yep. When pd.datetime() is called on column of times it will be transformed to datetime64 and all dates will be today's dates
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Issue
datetime.strftimeand specified formats (e.g. pandas output time on nanosecond precision while DateTime only support reading of milliseconds precision max, and some other cases). It could be solvable via some string manipulation which is heavily error prune.Description of changes
timezoneattribute. Storing utc_offset in TimeVariable is also not a good practice since two dates in the same timezone can have two different offsets depending on summer, wintertime or time zones changes in history. Remembering the timezone is more suitable.Includes