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BUG: to_datetime with infer_datetime_format dropped timezone names #33133

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Merged
merged 6 commits into from
Mar 31, 2020
Merged

BUG: to_datetime with infer_datetime_format dropped timezone names #33133

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4c9b116
BUG: to_datetime with infer_datetime_format dropped timezone names
Mar 29, 2020
c9cbeec
Add issue number
Mar 29, 2020
48a4fbb
Clarify infer_datetime_format
Mar 29, 2020
ab1bcc4
Merge remote-tracking branch 'upstream/master' into tz_infered_parsing
Mar 30, 2020
42d0e6f
Add parameterized test
Mar 30, 2020
77a0434
Add GH ref
Mar 31, 2020
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2 changes: 1 addition & 1 deletion doc/source/whatsnew/v1.1.0.rst
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Expand Up @@ -313,7 +313,7 @@ Timedelta
Timezones
^^^^^^^^^

-
- Bug in :func:`to_datetime` with ``infer_datetime_format=True`` where timezone names (e.g. ``UTC``) would not be parsed correctly (:issue:`33133`)
-


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1 change: 1 addition & 0 deletions pandas/_libs/tslibs/parsing.pyx
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Expand Up @@ -805,6 +805,7 @@ def _guess_datetime_format(dt_str, dayfirst=False, dt_str_parse=du_parse,
(('second',), '%S', 2),
(('microsecond',), '%f', 6),
(('second', 'microsecond'), '%S.%f', 0),
(('tzinfo',), '%Z', 0),
]

if dayfirst:
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6 changes: 3 additions & 3 deletions pandas/core/tools/datetimes.py
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Expand Up @@ -606,9 +606,9 @@ def to_datetime(
would calculate the number of milliseconds to the unix epoch start.
infer_datetime_format : bool, default False
If True and no `format` is given, attempt to infer the format of the
datetime strings, and if it can be inferred, switch to a faster
method of parsing them. In some cases this can increase the parsing
speed by ~5-10x.
datetime strings based on the first non-NaN element,
and if it can be inferred, switch to a faster method of parsing them.
In some cases this can increase the parsing speed by ~5-10x.
origin : scalar, default 'unix'
Define the reference date. The numeric values would be parsed as number
of units (defined by `unit`) since this reference date.
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12 changes: 12 additions & 0 deletions pandas/tests/tools/test_to_datetime.py
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Expand Up @@ -1862,6 +1862,18 @@ def test_to_datetime_infer_datetime_format_series_start_with_nans(self, cache):
pd.to_datetime(s, infer_datetime_format=True, cache=cache),
)

@pytest.mark.parametrize(
"tz_name, offset", [("UTC", 0), ("UTC-3", 180), ("UTC+3", -180)]
)
def test_infer_datetime_format_tz_name(self, tz_name, offset):
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GH ref?

# GH 33133
s = pd.Series([f"2019-02-02 08:07:13 {tz_name}"])
result = to_datetime(s, infer_datetime_format=True)
expected = pd.Series(
[pd.Timestamp("2019-02-02 08:07:13").tz_localize(pytz.FixedOffset(offset))]
)
tm.assert_series_equal(result, expected)

@pytest.mark.parametrize("cache", [True, False])
def test_to_datetime_iso8601_noleading_0s(self, cache):
# GH 11871
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