REF: share methods between ExtensionBlock, NDArrayBackedExtensionBlock

pandas/core/internals/blocks.py

@@ -1354,6 +1354,31 @@ def delete(self, loc) -> None:
             # _cache not yet initialized
             pass
 
+    @cache_readonly
+    def array_values(self) -> ExtensionArray:
+        return self.values
+
+    def get_values(self, dtype: DtypeObj | None = None) -> np.ndarray:
+        """
+        return object dtype as boxed values, such as Timestamps/Timedelta
+        """
+        values = self.values
+        if dtype == _dtype_obj:
+            values = values.astype(object)
+        # TODO(EA2D): reshape not needed with 2D EAs
+        return np.asarray(values).reshape(self.shape)
+
+    def interpolate(
+        self, method="pad", axis=0, inplace=False, limit=None, fill_value=None, **kwargs
+    ):
+        values = self.values
+        if values.ndim == 2 and axis == 0:
+            # NDArrayBackedExtensionArray.fillna assumes axis=1
+            new_values = values.T.fillna(value=fill_value, method=method, limit=limit).T
+        else:
+            new_values = values.fillna(value=fill_value, method=method, limit=limit)
+        return self.make_block_same_class(new_values)
+
 
 class ExtensionBlock(EABackedBlock):
     """
@@ -1478,15 +1503,6 @@ def setitem(self, indexer, value):
         self.values[indexer] = value
         return self
 
-    def get_values(self, dtype: DtypeObj | None = None) -> np.ndarray:
-        # ExtensionArrays must be iterable, so this works.
-        # TODO(EA2D): reshape not needed with 2D EAs
-        return np.asarray(self.values).reshape(self.shape)
-
-    @cache_readonly
-    def array_values(self) -> ExtensionArray:
-        return self.values
-
     def take_nd(
         self,
         indexer,
@@ -1558,12 +1574,6 @@ def fillna(
         values = self.values.fillna(value=value, limit=limit)
         return [self.make_block_same_class(values=values)]
 
-    def interpolate(
-        self, method="pad", axis=0, inplace=False, limit=None, fill_value=None, **kwargs
-    ):
-        new_values = self.values.fillna(value=fill_value, method=method, limit=limit)
-        return self.make_block_same_class(new_values)
-
     def diff(self, n: int, axis: int = 1) -> list[Block]:
         if axis == 0 and n != 0:
             # n==0 case will be a no-op so let is fall through
@@ -1671,27 +1681,12 @@ class NDArrayBackedExtensionBlock(EABackedBlock):
 
     values: NDArrayBackedExtensionArray
 
-    @property
-    def array_values(self) -> NDArrayBackedExtensionArray:
-        return self.values
-
     @property
     def is_view(self) -> bool:
         """ return a boolean if I am possibly a view """
         # check the ndarray values of the DatetimeIndex values
         return self.values._ndarray.base is not None
 
-    def get_values(self, dtype: DtypeObj | None = None) -> np.ndarray:
-        """
-        return object dtype as boxed values, such as Timestamps/Timedelta
-        """
-        values = self.values
-        if dtype == _dtype_obj:
-            # DTA/TDA constructor and astype can handle 2D
-            values = values.astype(object)
-        # TODO(EA2D): reshape not needed with 2D EAs
-        return np.asarray(values).reshape(self.shape)
-
     def iget(self, key):
         # GH#31649 we need to wrap scalars in Timestamp/Timedelta
         # TODO(EA2D): this can be removed if we ever have 2D EA
@@ -1795,8 +1790,6 @@ class DatetimeTZBlock(ExtensionBlock, DatetimeLikeBlock):
     putmask = NDArrayBackedExtensionBlock.putmask
     fillna = NDArrayBackedExtensionBlock.fillna
 
-    get_values = NDArrayBackedExtensionBlock.get_values
-
     # error: Incompatible types in assignment (expression has type
     # "Callable[[NDArrayBackedExtensionBlock], bool]", base class "ExtensionBlock"
     # defined the type as "bool")  [assignment]

pandas/tests/extension/base/setitem.py

@@ -356,3 +356,14 @@ def test_setitem_series(self, data, full_indexer):
             data.astype(object), index=ser.index, name="data", dtype=object
         )
         self.assert_series_equal(result, expected)
+
+    def test_delitem_series(self, data):
+        # GH#40763
+        ser = pd.Series(data, name="data")
+
+        taker = np.arange(len(ser))
+        taker = np.delete(taker, 1)
+
+        expected = ser[taker]
+        del ser[1]
+        self.assert_series_equal(ser, expected)