REF: de-duplicate methods, remove unused kwd

pandas/core/frame.py

@@ -11502,7 +11502,7 @@ def quantile(
                 f"Invalid method: {method}. Method must be in {valid_method}."
             )
         if method == "single":
-            res = data._mgr.quantile(qs=q, axis=1, interpolation=interpolation)
+            res = data._mgr.quantile(qs=q, interpolation=interpolation)
         elif method == "table":
             valid_interpolation = {"nearest", "lower", "higher"}
             if interpolation not in valid_interpolation:

pandas/core/internals/array_manager.py

@@ -324,12 +324,6 @@ def diff(self, n: int) -> Self:
         assert self.ndim == 2  # caller ensures
         return self.apply(algos.diff, n=n)
 
-    def shift(self, periods: int, fill_value) -> Self:
-        if fill_value is lib.no_default:
-            fill_value = None
-
-        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:
             copy = True
@@ -930,12 +924,10 @@ def quantile(
         self,
         *,
         qs: Index,  # with dtype float64
-        axis: AxisInt = 0,
         transposed: bool = False,
         interpolation: QuantileInterpolation = "linear",
     ) -> ArrayManager:
         arrs = [ensure_block_shape(x, 2) for x in self.arrays]
-        assert axis == 1
         new_arrs = [
             quantile_compat(x, np.asarray(qs._values), interpolation) for x in arrs
         ]

pandas/core/internals/base.py

@@ -269,6 +269,12 @@ def pad_or_backfill(self, inplace: bool, **kwargs) -> Self:
             using_cow=using_copy_on_write(),
         )
 
+    def shift(self, periods: int, fill_value) -> Self:
+        if fill_value is lib.no_default:
+            fill_value = None
+
+        return self.apply_with_block("shift", periods=periods, fill_value=fill_value)
+
     # --------------------------------------------------------------------
     # Consolidation: No-ops for all but BlockManager
 

pandas/core/internals/blocks.py

@@ -1511,7 +1511,6 @@ def quantile(
         self,
         qs: Index,  # with dtype float64
         interpolation: QuantileInterpolation = "linear",
-        axis: AxisInt = 0,
     ) -> Block:
         """
         compute the quantiles of the
@@ -1522,16 +1521,13 @@ def quantile(
             The quantiles to be computed in float64.
         interpolation : str, default 'linear'
             Type of interpolation.
-        axis : int, default 0
-            Axis to compute.
 
         Returns
         -------
         Block
         """
         # We should always have ndim == 2 because Series dispatches to DataFrame
         assert self.ndim == 2
-        assert axis == 1  # only ever called this way
         assert is_list_like(qs)  # caller is responsible for this
 
         result = quantile_compat(self.values, np.asarray(qs._values), interpolation)

pandas/core/internals/managers.py

@@ -378,12 +378,6 @@ def diff(self, n: int) -> Self:
         # only reached with self.ndim == 2
         return self.apply("diff", n=n)
 
-    def shift(self, periods: int, fill_value) -> Self:
-        if fill_value is lib.no_default:
-            fill_value = None
-
-        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:
             if using_copy_on_write():
@@ -1463,7 +1457,6 @@ def quantile(
         self,
         *,
         qs: Index,  # with dtype float 64
-        axis: AxisInt = 0,
         interpolation: QuantileInterpolation = "linear",
     ) -> Self:
         """
@@ -1473,9 +1466,6 @@ def quantile(
 
         Parameters
         ----------
-        axis: reduction axis, default 0
-        consolidate: bool, default True. Join together blocks having same
-            dtype
         interpolation : type of interpolation, default 'linear'
         qs : list of the quantiles to be computed
 
@@ -1487,14 +1477,12 @@ def quantile(
         #  simplify some of the code here and in the blocks
         assert self.ndim >= 2
         assert is_list_like(qs)  # caller is responsible for this
-        assert axis == 1  # only ever called this way
 
         new_axes = list(self.axes)
         new_axes[1] = Index(qs, dtype=np.float64)
 
         blocks = [
-            blk.quantile(axis=axis, qs=qs, interpolation=interpolation)
-            for blk in self.blocks
+            blk.quantile(qs=qs, interpolation=interpolation) for blk in self.blocks
         ]
 
         return type(self)(blocks, new_axes)