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doc/source/whatsnew/v1.0.2.rst

@@ -18,6 +18,7 @@ Fixed regressions
 - Fixed regression in :meth:`DataFrame.to_excel` when ``columns`` kwarg is passed (:issue:`31677`)
 - Fixed regression in :meth:`Series.align` when ``other`` is a DataFrame and ``method`` is not None (:issue:`31785`)
 - Fixed regression in :meth:`pandas.core.groupby.RollingGroupby.apply` where the ``raw`` parameter was ignored (:issue:`31754`)
+- Fixed regression in :meth:`rolling(..).corr() <pandas.core.window.Rolling.corr>` when using a time offset (:issue:`31789`)
 -
 
 .. ---------------------------------------------------------------------------

pandas/core/frame.py

@@ -5222,7 +5222,7 @@ def nsmallest(self, n, columns, keep="first") -> "DataFrame":
         Examples
         --------
         >>> df = pd.DataFrame({'population': [59000000, 65000000, 434000,
-        ...                                   434000, 434000, 337000, 11300,
+        ...                                   434000, 434000, 337000, 337000,
         ...                                   11300, 11300],
         ...                    'GDP': [1937894, 2583560 , 12011, 4520, 12128,
         ...                            17036, 182, 38, 311],
@@ -5239,43 +5239,44 @@ def nsmallest(self, n, columns, keep="first") -> "DataFrame":
         Maldives      434000     4520      MV
         Brunei        434000    12128      BN
         Iceland       337000    17036      IS
-        Nauru          11300      182      NR
+        Nauru         337000      182      NR
         Tuvalu         11300       38      TV
         Anguilla       11300      311      AI
 
         In the following example, we will use ``nsmallest`` to select the
-        three rows having the smallest values in column "a".
+        three rows having the smallest values in column "population".
 
         >>> df.nsmallest(3, 'population')
-                  population  GDP alpha-2
-        Nauru          11300  182      NR
-        Tuvalu         11300   38      TV
-        Anguilla       11300  311      AI
+                  population    GDP alpha-2
+        Tuvalu         11300     38      TV
+        Anguilla       11300    311      AI
+        Iceland       337000  17036	     IS
 
         When using ``keep='last'``, ties are resolved in reverse order:
 
         >>> df.nsmallest(3, 'population', keep='last')
                   population  GDP alpha-2
         Anguilla       11300  311      AI
         Tuvalu         11300   38      TV
-        Nauru          11300  182      NR
+        Nauru         337000  182      NR
 
         When using ``keep='all'``, all duplicate items are maintained:
 
         >>> df.nsmallest(3, 'population', keep='all')
-                  population  GDP alpha-2
-        Nauru          11300  182      NR
-        Tuvalu         11300   38      TV
-        Anguilla       11300  311      AI
+                  population    GDP alpha-2
+        Tuvalu         11300     38      TV
+        Anguilla       11300    311      AI
+        Iceland       337000  17036      IS
+        Nauru         337000    182      NR
 
-        To order by the largest values in column "a" and then "c", we can
+        To order by the smallest values in column "population" and then "GDP", we can
         specify multiple columns like in the next example.
 
         >>> df.nsmallest(3, ['population', 'GDP'])
                   population  GDP alpha-2
         Tuvalu         11300   38      TV
-        Nauru          11300  182      NR
         Anguilla       11300  311      AI
+        Nauru         337000  182      NR
         """
         return algorithms.SelectNFrame(
             self, n=n, keep=keep, columns=columns

pandas/core/generic.py

@@ -3498,13 +3498,11 @@ def _iget_item_cache(self, item):
     def _box_item_values(self, key, values):
         raise AbstractMethodError(self)
 
-    def _slice(
-        self: FrameOrSeries, slobj: slice, axis=0, kind: str = "getitem"
-    ) -> FrameOrSeries:
+    def _slice(self: FrameOrSeries, slobj: slice, axis=0) -> FrameOrSeries:
         """
         Construct a slice of this container.
 
-        kind parameter is maintained for compatibility with Series slicing.
+        Slicing with this method is *always* positional.
         """
         axis = self._get_block_manager_axis(axis)
         result = self._constructor(self._data.get_slice(slobj, axis=axis))