'Backport PR pandas-dev#53257: BUG: Add AM/PM token support on guess_datetime_format'

* BUG: Add am/pm parsing support on guess_format

* ⛏️ add unit tests

* more unit tests

* ⛏️ not guess am/pm mark

* 🪲 bug fix parsing am/pm tokens

* 📝 whatsnew

* 📝 whats new doc

* isort on whatsnew entry

* move whatsnew note to 2.0.1

* 2.0.2, not 2.0.1

* clarify

---------

Co-authored-by: MarcoGorelli <[email protected]>
(cherry picked from commit f2de598)

Author: juli4nb4dillo

doc/source/whatsnew/v2.0.2.rst

@@ -29,6 +29,9 @@ Bug fixes
 - Bug in :func:`api.interchange.from_dataframe` was returning :class:`DataFrame`'s of incorrect sizes when called on slices (:issue:`52824`)
 - Bug in :func:`api.interchange.from_dataframe` was unnecessarily raising on bitmasks (:issue:`49888`)
 - Bug in :func:`merge` when merging on datetime columns on different resolutions (:issue:`53200`)
+- Bug in :func:`to_datetime` was inferring format to contain ``"%H"`` instead of ``"%I"`` if date contained "AM" / "PM" tokens (:issue:`53147`)
+- Bug in :func:`to_timedelta` was raising ``ValueError`` with ``pandas.NA`` (:issue:`52909`)
+- Bug in :meth:`DataFrame.__getitem__` not preserving dtypes for :class:`MultiIndex` partial keys (:issue:`51895`)
 - Bug in :meth:`DataFrame.convert_dtypes` ignores ``convert_*`` keywords when set to False ``dtype_backend="pyarrow"`` (:issue:`52872`)
 - Bug in :meth:`DataFrame.sort_values` raising for PyArrow ``dictionary`` dtype (:issue:`53232`)
 - Bug in :meth:`Series.describe` treating pyarrow-backed timestamps and timedeltas as categorical data (:issue:`53001`)

pandas/_libs/tslibs/parsing.pyx

@@ -990,6 +990,11 @@ def guess_datetime_format(dt_str: str, bint dayfirst=False) -> str | None:
 
             output_format.append(tokens[i])
 
+    # if am/pm token present, replace 24-hour %H, with 12-hour %I
+    if "%p" in output_format and "%H" in output_format:
+        i = output_format.index("%H")
+        output_format[i] = "%I"
+
     guessed_format = "".join(output_format)
 
     try:

pandas/tests/tools/test_to_datetime.py

@@ -2953,6 +2953,9 @@ class TestDatetimeParsingWrappers:
             ("2005-11-09 10:15", datetime(2005, 11, 9, 10, 15)),
             ("2005-11-09 08H", datetime(2005, 11, 9, 8, 0)),
             ("2005/11/09 10:15", datetime(2005, 11, 9, 10, 15)),
+            ("2005/11/09 10:15:32", datetime(2005, 11, 9, 10, 15, 32)),
+            ("2005/11/09 10:15:32 AM", datetime(2005, 11, 9, 10, 15, 32)),
+            ("2005/11/09 10:15:32 PM", datetime(2005, 11, 9, 22, 15, 32)),
             ("2005/11/09 08H", datetime(2005, 11, 9, 8, 0)),
             ("Thu Sep 25 10:36:28 2003", datetime(2003, 9, 25, 10, 36, 28)),
             ("Thu Sep 25 2003", datetime(2003, 9, 25)),

pandas/tests/tslibs/test_parsing.py

@@ -201,8 +201,10 @@ def test_parsers_month_freq(date_str, expected):
         ("2011-12-30T00:00:00.000000+9:0", "%Y-%m-%dT%H:%M:%S.%f%z"),
         ("2011-12-30T00:00:00.000000+09:", None),
         ("2011-12-30 00:00:00.000000", "%Y-%m-%d %H:%M:%S.%f"),
-        ("Tue 24 Aug 2021 01:30:48 AM", "%a %d %b %Y %H:%M:%S %p"),
-        ("Tuesday 24 Aug 2021 01:30:48 AM", "%A %d %b %Y %H:%M:%S %p"),
+        ("Tue 24 Aug 2021 01:30:48", "%a %d %b %Y %H:%M:%S"),
+        ("Tuesday 24 Aug 2021 01:30:48", "%A %d %b %Y %H:%M:%S"),
+        ("Tue 24 Aug 2021 01:30:48 AM", "%a %d %b %Y %I:%M:%S %p"),
+        ("Tuesday 24 Aug 2021 01:30:48 AM", "%A %d %b %Y %I:%M:%S %p"),
         ("27.03.2003 14:55:00.000", "%d.%m.%Y %H:%M:%S.%f"),  # GH50317
     ],
 )