Merge branch 'pandas-dev:main' into main

Author: Tirthchoksi22

ci/code_checks.sh

@@ -253,13 +253,11 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.Timestamp.ctime SA01" \
         -i "pandas.Timestamp.date SA01" \
         -i "pandas.Timestamp.day GL08" \
-        -i "pandas.Timestamp.dst SA01" \
         -i "pandas.Timestamp.floor SA01" \
         -i "pandas.Timestamp.fold GL08" \
         -i "pandas.Timestamp.fromordinal SA01" \
         -i "pandas.Timestamp.fromtimestamp PR01,SA01" \
         -i "pandas.Timestamp.hour GL08" \
-        -i "pandas.Timestamp.is_leap_year SA01" \
         -i "pandas.Timestamp.isocalendar SA01" \
         -i "pandas.Timestamp.isoweekday SA01" \
         -i "pandas.Timestamp.max PR02" \

doc/source/whatsnew/v3.0.0.rst

@@ -247,6 +247,7 @@ Removal of prior version deprecations/changes
 - Removed the "closed" and "normalize" keywords in :meth:`DatetimeIndex.__new__` (:issue:`52628`)
 - Removed the deprecated ``delim_whitespace`` keyword in :func:`read_csv` and :func:`read_table`, use ``sep=r"\s+"`` instead (:issue:`55569`)
 - Require :meth:`SparseDtype.fill_value` to be a valid value for the :meth:`SparseDtype.subtype` (:issue:`53043`)
+- Stopped automatically casting non-datetimelike values (mainly strings) in :meth:`Series.isin` and :meth:`Index.isin` with ``datetime64``, ``timedelta64``, and :class:`PeriodDtype` dtypes (:issue:`53111`)
 - Stopped performing dtype inference when setting a :class:`Index` into a :class:`DataFrame` (:issue:`56102`)
 - Stopped performing dtype inference with in :meth:`Index.insert` with object-dtype index; this often affects the index/columns that result when setting new entries into an empty :class:`Series` or :class:`DataFrame` (:issue:`51363`)
 - Removed the "closed" and "unit" keywords in :meth:`TimedeltaIndex.__new__` (:issue:`52628`, :issue:`55499`)

pandas/_libs/tslibs/nattype.pyx

@@ -542,6 +542,14 @@ class NaTType(_NaT):
         """
         Return the daylight saving time (DST) adjustment.
 
+        This method returns the DST adjustment as a `datetime.timedelta` object
+        if the Timestamp is timezone-aware and DST is applicable.
+
+        See Also
+        --------
+        Timestamp.tz_localize : Localize the Timestamp to a timezone.
+        Timestamp.tz_convert : Convert timezone-aware Timestamp to another time zone.
+
         Examples
         --------
         >>> ts = pd.Timestamp('2000-06-01 00:00:00', tz='Europe/Brussels')

pandas/_libs/tslibs/timestamps.pyx

@@ -820,9 +820,20 @@ cdef class _Timestamp(ABCTimestamp):
         """
         Return True if year is a leap year.
 
+        A leap year is a year, which has 366 days (instead of 365) including 29th of
+        February as an intercalary day. Leap years are years which are multiples of
+        four with the exception of years divisible by 100 but not by 400.
+
         Returns
         -------
         bool
+            True if year is a leap year, else False
+
+        See Also
+        --------
+        Period.is_leap_year : Return True if the period’s year is in a leap year.
+        DatetimeIndex.is_leap_year : Boolean indicator if the date belongs to a
+            leap year.
 
         Examples
         --------
@@ -1658,6 +1669,14 @@ class Timestamp(_Timestamp):
         """
         Return the daylight saving time (DST) adjustment.
 
+        This method returns the DST adjustment as a `datetime.timedelta` object
+        if the Timestamp is timezone-aware and DST is applicable.
+
+        See Also
+        --------
+        Timestamp.tz_localize : Localize the Timestamp to a timezone.
+        Timestamp.tz_convert : Convert timezone-aware Timestamp to another time zone.
+
         Examples
         --------
         >>> ts = pd.Timestamp('2000-06-01 00:00:00', tz='Europe/Brussels')

pandas/core/arrays/datetimelike.py

@@ -759,14 +759,6 @@ def isin(self, values: ArrayLike) -> npt.NDArray[np.bool_]:
         values = ensure_wrapped_if_datetimelike(values)
 
         if not isinstance(values, type(self)):
-            inferable = [
-                "timedelta",
-                "timedelta64",
-                "datetime",
-                "datetime64",
-                "date",
-                "period",
-            ]
             if values.dtype == object:
                 values = lib.maybe_convert_objects(
                     values,  # type: ignore[arg-type]
@@ -775,32 +767,11 @@ def isin(self, values: ArrayLike) -> npt.NDArray[np.bool_]:
                 )
                 if values.dtype != object:
                     return self.isin(values)
-
-                inferred = lib.infer_dtype(values, skipna=False)
-                if inferred not in inferable:
-                    if inferred == "string":
-                        pass
-
-                    elif "mixed" in inferred:
-                        return isin(self.astype(object), values)
-                    else:
-                        return np.zeros(self.shape, dtype=bool)
-
-            try:
-                values = type(self)._from_sequence(values)
-            except ValueError:
-                return isin(self.astype(object), values)
-            else:
-                warnings.warn(
-                    # GH#53111
-                    f"The behavior of 'isin' with dtype={self.dtype} and "
-                    "castable values (e.g. strings) is deprecated. In a "
-                    "future version, these will not be considered matching "
-                    "by isin. Explicitly cast to the appropriate dtype before "
-                    "calling isin instead.",
-                    FutureWarning,
-                    stacklevel=find_stack_level(),
-                )
+                else:
+                    # TODO: Deprecate this case
+                    # https://github.com/pandas-dev/pandas/pull/58645/files#r1604055791
+                    return isin(self.astype(object), values)
+            return np.zeros(self.shape, dtype=bool)
 
         if self.dtype.kind in "mM":
             self = cast("DatetimeArray | TimedeltaArray", self)

pandas/tests/test_algos.py

@@ -990,21 +990,18 @@ def test_isin_datetimelike_all_nat(self, dtype):
         tm.assert_numpy_array_equal(result, expected)
 
     @pytest.mark.parametrize("dtype", ["m8[ns]", "M8[ns]", "M8[ns, UTC]"])
-    def test_isin_datetimelike_strings_deprecated(self, dtype):
+    def test_isin_datetimelike_strings_returns_false(self, dtype):
         # GH#53111
         dta = date_range("2013-01-01", periods=3)._values
         arr = Series(dta.view("i8")).array.view(dtype)
 
         vals = [str(x) for x in arr]
-        msg = "The behavior of 'isin' with dtype=.* is deprecated"
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            res = algos.isin(arr, vals)
-        assert res.all()
+        res = algos.isin(arr, vals)
+        assert not res.any()
 
         vals2 = np.array(vals, dtype=str)
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            res2 = algos.isin(arr, vals2)
-        assert res2.all()
+        res2 = algos.isin(arr, vals2)
+        assert not res2.any()
 
     def test_isin_dt64tz_with_nat(self):
         # the all-NaT values used to get inferred to tznaive, which was evaluated