BUG: to_datetime with infer_datetime_format dropped timezone names (#33133)

Author: mroeschke

doc/source/whatsnew/v1.1.0.rst

@@ -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`)
 -
 
 

pandas/_libs/tslibs/parsing.pyx

@@ -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:

pandas/core/tools/datetimes.py

@@ -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.

pandas/tests/tools/test_to_datetime.py

@@ -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):
+        # 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