Merge branch 'master' into cln-getitem_block

Author: jbrockmendel

pandas/core/frame.py

@@ -6464,6 +6464,57 @@ def swaplevel(self, i: Axis = -2, j: Axis = -1, axis: Axis = 0) -> DataFrame:
         Returns
         -------
         DataFrame
+
+        Examples
+        --------
+        >>> df = pd.DataFrame(
+        ...     {"Grade": ["A", "B", "A", "C"]},
+        ...     index=[
+        ...         ["Final exam", "Final exam", "Coursework", "Coursework"],
+        ...         ["History", "Geography", "History", "Geography"],
+        ...         ["January", "February", "March", "April"],
+        ...     ],
+        ... )
+        >>> df
+                                            Grade
+        Final exam  History     January      A
+                    Geography   February     B
+        Coursework  History     March        A
+                    Geography   April        C
+
+        In the following example, we will swap the levels of the indices.
+        Here, we will swap the levels column-wise, but levels can be swapped row-wise
+        in a similar manner. Note that column-wise is the default behaviour.
+        By not supplying any arguments for i and j, we swap the last and second to
+        last indices.
+
+        >>> df.swaplevel()
+                                            Grade
+        Final exam  January     History         A
+                    February    Geography       B
+        Coursework  March       History         A
+                    April       Geography       C
+
+        By supplying one argument, we can choose which index to swap the last
+        index with. We can for example swap the first index with the last one as
+        follows.
+
+        >>> df.swaplevel(0)
+                                            Grade
+        January     History     Final exam      A
+        February    Geography   Final exam      B
+        March       History     Coursework      A
+        April       Geography   Coursework      C
+
+        We can also define explicitly which indices we want to swap by supplying values
+        for both i and j. Here, we for example swap the first and second indices.
+
+        >>> df.swaplevel(0, 1)
+                                            Grade
+        History     Final exam  January         A
+        Geography   Final exam  February        B
+        History     Coursework  March           A
+        Geography   Coursework  April           C
         """
         result = self.copy()
 

pandas/core/generic.py

@@ -11014,7 +11014,9 @@ def ewm(
         times: Optional[Union[str, np.ndarray, FrameOrSeries]] = None,
     ) -> ExponentialMovingWindow:
         axis = self._get_axis_number(axis)
-        return ExponentialMovingWindow(
+        # error: Value of type variable "FrameOrSeries" of "ExponentialMovingWindow"
+        # cannot be "object"
+        return ExponentialMovingWindow(  # type: ignore[type-var]
             self,
             com=com,
             span=span,

pandas/core/internals/array_manager.py

@@ -786,12 +786,10 @@ def get_slice(self, slobj: slice, axis: int = 0) -> ArrayManager:
             arrays = self.arrays[slobj]
 
         new_axes = list(self._axes)
-        new_axes[axis] = new_axes[axis][slobj]
+        new_axes[axis] = new_axes[axis]._getitem_slice(slobj)
 
         return type(self)(arrays, new_axes, verify_integrity=False)
 
-    getitem_mgr = get_slice
-
     def fast_xs(self, loc: int) -> ArrayLike:
         """
         Return the array corresponding to `frame.iloc[loc]`.
@@ -1218,7 +1216,12 @@ def get_slice(self, slobj: slice, axis: int = 0) -> SingleArrayManager:
             raise IndexError("Requested axis not found in manager")
 
         new_array = self.array[slobj]
-        new_index = self.index[slobj]
+        new_index = self.index._getitem_slice(slobj)
+        return type(self)([new_array], [new_index], verify_integrity=False)
+
+    def getitem_mgr(self, indexer) -> SingleArrayManager:
+        new_array = self.array[indexer]
+        new_index = self.index[indexer]
         return type(self)([new_array], [new_index])
 
     def apply(self, func, **kwargs):

pandas/core/window/expanding.py

@@ -5,11 +5,8 @@
     Dict,
     Optional,
     Tuple,
-    Union,
 )
 
-import numpy as np
-
 from pandas._typing import (
     Axis,
     FrameOrSeries,
@@ -589,7 +586,7 @@ def quantile(
     )
     def cov(
         self,
-        other: Optional[Union[np.ndarray, FrameOrSeriesUnion]] = None,
+        other: Optional[FrameOrSeriesUnion] = None,
         pairwise: Optional[bool] = None,
         ddof: int = 1,
         **kwargs,
@@ -654,7 +651,7 @@ def cov(
     )
     def corr(
         self,
-        other: Optional[Union[np.ndarray, FrameOrSeriesUnion]] = None,
+        other: Optional[FrameOrSeriesUnion] = None,
         pairwise: Optional[bool] = None,
         ddof: int = 1,
         **kwargs,

pandas/core/window/rolling.py

@@ -1354,7 +1354,7 @@ def quantile(self, quantile: float, interpolation: str = "linear", **kwargs):
 
     def cov(
         self,
-        other: Optional[Union[np.ndarray, FrameOrSeriesUnion]] = None,
+        other: Optional[FrameOrSeriesUnion] = None,
         pairwise: Optional[bool] = None,
         ddof: int = 1,
         **kwargs,
@@ -1392,7 +1392,7 @@ def cov_func(x, y):
 
     def corr(
         self,
-        other: Optional[Union[np.ndarray, FrameOrSeriesUnion]] = None,
+        other: Optional[FrameOrSeriesUnion] = None,
         pairwise: Optional[bool] = None,
         ddof: int = 1,
         **kwargs,
@@ -2137,7 +2137,7 @@ def quantile(self, quantile: float, interpolation: str = "linear", **kwargs):
     )
     def cov(
         self,
-        other: Optional[Union[np.ndarray, FrameOrSeriesUnion]] = None,
+        other: Optional[FrameOrSeriesUnion] = None,
         pairwise: Optional[bool] = None,
         ddof: int = 1,
         **kwargs,
@@ -2262,7 +2262,7 @@ def cov(
     )
     def corr(
         self,
-        other: Optional[Union[np.ndarray, FrameOrSeriesUnion]] = None,
+        other: Optional[FrameOrSeriesUnion] = None,
         pairwise: Optional[bool] = None,
         ddof: int = 1,
         **kwargs,