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| author | Pierre de Buyl <pdebuyl@pdebuyl.be> | 2020-03-06 11:39:48 +0100 |
|---|---|---|
| committer | Pierre de Buyl <pdebuyl@pdebuyl.be> | 2020-03-06 11:39:48 +0100 |
| commit | 4cd8a598c38109ba5ac53c70f849b10d21aa2b43 (patch) | |
| tree | c9ae35b47d1b3bef16bc37a7688da7606e3a62db | |
| parent | 91991e6d9aca5d32724039856e170141d2aca2ed (diff) | |
| download | numpy-4cd8a598c38109ba5ac53c70f849b10d21aa2b43.tar.gz | |
DOC: move deprecation info to apart paragraph.
| -rw-r--r-- | doc/source/reference/arrays.datetime.rst | 12 |
1 files changed, 8 insertions, 4 deletions
diff --git a/doc/source/reference/arrays.datetime.rst b/doc/source/reference/arrays.datetime.rst index 364f6f8f2..74d886fcb 100644 --- a/doc/source/reference/arrays.datetime.rst +++ b/doc/source/reference/arrays.datetime.rst @@ -61,10 +61,6 @@ When creating an array of datetimes from a string, it is still possible to automatically select the unit from the inputs, by using the datetime type with generic units. -For backwards compatibility, datetime64 still parses timezone offsets, -which it handles by converting to UTC. However, the resulting datetime -is timezone naive. - .. admonition:: Example >>> np.array(['2007-07-13', '2006-01-13', '2010-08-13'], dtype='datetime64') @@ -106,6 +102,14 @@ because the moment of time is still being represented exactly. >>> np.datetime64('2010-03-14T15') == np.datetime64('2010-03-14T15:00:00.00') True +.. deprecated:: 1.11.0 + + NumPy does not use timezones. For backwards compatibility, datetime64 + still parses timezone offsets, which it handles by converting to + UTC. This behaviour is deprecated and will raise an error in the + future. + + Datetime and Timedelta Arithmetic ================================= |