REF: remove axis keyword from Manager/Block.shift

pandas/core/arrays/_mixins.py

@@ -238,7 +238,9 @@ def searchsorted(
         return self._ndarray.searchsorted(npvalue, side=side, sorter=sorter)
 
     @doc(ExtensionArray.shift)
-    def shift(self, periods: int = 1, fill_value=None, axis: AxisInt = 0):
+    def shift(self, periods: int = 1, fill_value=None):
+        # NB: shift is always along axis=0
+        axis = 0
         fill_value = self._validate_scalar(fill_value)
         new_values = shift(self._ndarray, periods, axis, fill_value)
 

pandas/core/arrays/base.py

@@ -851,6 +851,8 @@ def shift(self, periods: int = 1, fill_value: object = None) -> ExtensionArray:
         If ``periods > len(self)``, then an array of size
         len(self) is returned, with all values filled with
         ``self.dtype.na_value``.
+
+        For 2-dimensional ExtensionArrays, we are always shifting along axis=0.
         """
         # Note: this implementation assumes that `self.dtype.na_value` can be
         # stored in an instance of your ExtensionArray with `self.dtype`.

pandas/core/generic.py

@@ -10590,9 +10590,8 @@ def shift(
         if freq is None:
             # when freq is None, data is shifted, index is not
             axis = self._get_axis_number(axis)
-            new_data = self._mgr.shift(
-                periods=periods, axis=axis, fill_value=fill_value
-            )
+            assert axis == 0  # axis == 1 cases handled in DataFrame.shift
+            new_data = self._mgr.shift(periods=periods, fill_value=fill_value)
             return self._constructor_from_mgr(
                 new_data, axes=new_data.axes
             ).__finalize__(self, method="shift")

pandas/core/internals/array_manager.py

@@ -324,17 +324,11 @@ def diff(self, n: int) -> Self:
         assert self.ndim == 2  # caller ensures
         return self.apply(algos.diff, n=n)
 
-    def shift(self, periods: int, axis: AxisInt, fill_value) -> Self:
+    def shift(self, periods: int, fill_value) -> Self:
         if fill_value is lib.no_default:
             fill_value = None
 
-        if axis == 1 and self.ndim == 2:
-            # TODO column-wise shift
-            raise NotImplementedError
-
-        return self.apply_with_block(
-            "shift", periods=periods, axis=axis, fill_value=fill_value
-        )
+        return self.apply_with_block("shift", periods=periods, fill_value=fill_value)
 
     def astype(self, dtype, copy: bool | None = False, errors: str = "raise") -> Self:
         if copy is None:

pandas/core/internals/blocks.py

@@ -1478,12 +1478,11 @@ def diff(self, n: int) -> list[Block]:
         new_values = algos.diff(self.values.T, n, axis=0).T
         return [self.make_block(values=new_values)]
 
-    def shift(
-        self, periods: int, axis: AxisInt = 0, fill_value: Any = None
-    ) -> list[Block]:
+    def shift(self, periods: int, fill_value: Any = None) -> list[Block]:
         """shift the block by periods, possibly upcast"""
         # convert integer to float if necessary. need to do a lot more than
         # that, handle boolean etc also
+        axis = self.ndim - 1
 
         # Note: periods is never 0 here, as that is handled at the top of
         #  NDFrame.shift.  If that ever changes, we can do a check for periods=0
@@ -1505,12 +1504,12 @@ def shift(
             )
         except LossySetitemError:
             nb = self.coerce_to_target_dtype(fill_value)
-            return nb.shift(periods, axis=axis, fill_value=fill_value)
+            return nb.shift(periods, fill_value=fill_value)
 
         else:
             values = cast(np.ndarray, self.values)
             new_values = shift(values, periods, axis, casted)
-            return [self.make_block(new_values)]
+            return [self.make_block_same_class(new_values)]
 
     @final
     def quantile(
@@ -1661,6 +1660,18 @@ class EABackedBlock(Block):
 
     values: ExtensionArray
 
+    def shift(self, periods: int, fill_value: Any = None) -> list[Block]:
+        """
+        Shift the block by `periods`.
+
+        Dispatches to underlying ExtensionArray and re-boxes in an
+        ExtensionBlock.
+        """
+        # Transpose since EA.shift is always along axis=0, while we want to shift
+        #  along rows.
+        new_values = self.values.T.shift(periods=periods, fill_value=fill_value).T
+        return [self.make_block_same_class(new_values)]
+
     def setitem(self, indexer, value, using_cow: bool = False):
         """
         Attempt self.values[indexer] = value, possibly creating a new array.
@@ -2113,18 +2124,6 @@ def slice_block_rows(self, slicer: slice) -> Self:
         new_values = self.values[slicer]
         return type(self)(new_values, self._mgr_locs, ndim=self.ndim, refs=self.refs)
 
-    def shift(
-        self, periods: int, axis: AxisInt = 0, fill_value: Any = None
-    ) -> list[Block]:
-        """
-        Shift the block by `periods`.
-
-        Dispatches to underlying ExtensionArray and re-boxes in an
-        ExtensionBlock.
-        """
-        new_values = self.values.shift(periods=periods, fill_value=fill_value)
-        return [self.make_block_same_class(new_values)]
-
     def _unstack(
         self,
         unstacker,
@@ -2231,13 +2230,6 @@ def is_view(self) -> bool:
         # check the ndarray values of the DatetimeIndex values
         return self.values._ndarray.base is not None
 
-    def shift(
-        self, periods: int, axis: AxisInt = 0, fill_value: Any = None
-    ) -> list[Block]:
-        values = self.values
-        new_values = values.shift(periods, fill_value=fill_value, axis=axis)
-        return [self.make_block_same_class(new_values)]
-
 
 def _catch_deprecated_value_error(err: Exception) -> None:
     """

pandas/core/internals/managers.py

@@ -378,12 +378,11 @@ def diff(self, n: int) -> Self:
         # only reached with self.ndim == 2
         return self.apply("diff", n=n)
 
-    def shift(self, periods: int, axis: AxisInt, fill_value) -> Self:
-        axis = self._normalize_axis(axis)
+    def shift(self, periods: int, fill_value) -> Self:
         if fill_value is lib.no_default:
             fill_value = None
 
-        return self.apply("shift", periods=periods, axis=axis, fill_value=fill_value)
+        return self.apply("shift", periods=periods, fill_value=fill_value)
 
     def astype(self, dtype, copy: bool | None = False, errors: str = "raise") -> Self:
         if copy is None: