ENH: EA.interpolate

ci/code_checks.sh

@@ -241,6 +241,7 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         pandas.api.extensions.ExtensionArray.factorize \
         pandas.api.extensions.ExtensionArray.fillna \
         pandas.api.extensions.ExtensionArray.insert \
+        pandas.api.extensions.ExtensionArray.interpolate \
         pandas.api.extensions.ExtensionArray.isin \
         pandas.api.extensions.ExtensionArray.isna \
         pandas.api.extensions.ExtensionArray.ravel \

doc/source/reference/extensions.rst

@@ -51,6 +51,7 @@ objects.
       api.extensions.ExtensionArray.factorize
       api.extensions.ExtensionArray.fillna
       api.extensions.ExtensionArray.insert
+      api.extensions.ExtensionArray.interpolate
       api.extensions.ExtensionArray.isin
       api.extensions.ExtensionArray.isna
       api.extensions.ExtensionArray.ravel

pandas/_typing.py

@@ -307,6 +307,26 @@ def closed(self) -> bool:
 
 # Arguments for fillna()
 FillnaOptions = Literal["backfill", "bfill", "ffill", "pad"]
+InterpolateOptions = Literal[
+    "linear",
+    "time",
+    "index",
+    "values",
+    "nearest",
+    "zero",
+    "slinear",
+    "quadratic",
+    "cubic",
+    "barycentric",
+    "polynomial",
+    "krogh",
+    "piecewise_polynomial",
+    "spline",
+    "pchip",
+    "akima",
+    "cubicspline",
+    "from_derivatives",
+]
 
 # internals
 Manager = Union[

pandas/core/arrays/base.py

@@ -78,6 +78,7 @@
         AxisInt,
         Dtype,
         FillnaOptions,
+        InterpolateOptions,
         NumpySorter,
         NumpyValueArrayLike,
         PositionalIndexer,
@@ -90,6 +91,8 @@
         npt,
     )
 
+    from pandas import Index
+
 _extension_array_shared_docs: dict[str, str] = {}
 
 
@@ -118,6 +121,7 @@ class ExtensionArray:
     fillna
     equals
     insert
+    interpolate
     isin
     isna
     ravel
@@ -155,6 +159,7 @@ class ExtensionArray:
     * take
     * copy
     * _concat_same_type
+    * interpolate
 
     A default repr displaying the type, (truncated) data, length,
     and dtype is provided. It can be customized or replaced by
@@ -753,6 +758,27 @@ def argmax(self, skipna: bool = True) -> int:
             raise NotImplementedError
         return nargminmax(self, "argmax")
 
+    def interpolate(
+        self,
+        *,
+        method: InterpolateOptions,
+        axis: int,
+        index: Index,
+        limit,
+        limit_direction,
+        limit_area,
+        fill_value,
+        copy: bool,
+        **kwargs,
+    ) -> Self:
+        """
+        See DataFrame.interpolate.__doc__.
+        """
+        # NB: we return type(self) even if copy=False
+        raise NotImplementedError(
+            f"{type(self).__name__} does not implement interpolate"
+        )
+
     def fillna(
         self,
         value: object | ArrayLike | None = None,

pandas/core/arrays/datetimelike.py

@@ -58,6 +58,7 @@
     Dtype,
     DtypeObj,
     F,
+    InterpolateOptions,
     NpDtype,
     PositionalIndexer2D,
     PositionalIndexerTuple,
@@ -2233,23 +2234,23 @@ def copy(self, order: str = "C") -> Self:
     def interpolate(
         self,
         *,
-        method,
+        method: InterpolateOptions,
         axis: int,
         index: Index,
         limit,
         limit_direction,
         limit_area,
-        inplace: bool,
+        copy: bool,
         **kwargs,
     ) -> Self:
         """
         See NDFrame.interpolate.__doc__.
         """
-        # NB: we return type(self) even if inplace=True
+        # NB: we return type(self) even if copy=False
         if method != "linear":
             raise NotImplementedError
 
-        if inplace:
+        if not copy:
             out_data = self._ndarray
         else:
             out_data = self._ndarray.copy()
@@ -2264,7 +2265,7 @@ def interpolate(
             limit_area=limit_area,
             **kwargs,
         )
-        if inplace:
+        if not copy:
             return self
         return type(self)._simple_new(out_data, dtype=self.dtype)
 

pandas/core/arrays/numpy_.py

@@ -36,6 +36,7 @@
         AxisInt,
         Dtype,
         FillnaOptions,
+        InterpolateOptions,
         NpDtype,
         Scalar,
         Self,
@@ -261,20 +262,20 @@ def pad_or_backfill(
     def interpolate(
         self,
         *,
-        method,
+        method: InterpolateOptions,
         axis: int,
         index: Index,
         limit,
         limit_direction,
         limit_area,
-        inplace: bool,
+        copy: bool,
         **kwargs,
     ) -> Self:
         """
         See NDFrame.interpolate.__doc__.
         """
-        # NB: we return type(self) even if inplace=True
-        if inplace:
+        # NB: we return type(self) even if copy=False
+        if not copy:
             out_data = self._ndarray
         else:
             out_data = self._ndarray.copy()
@@ -290,7 +291,7 @@ def interpolate(
             limit_area=limit_area,
             **kwargs,
         )
-        if inplace:
+        if not copy:
             return self
         return type(self)._simple_new(out_data, dtype=self.dtype)
 

pandas/core/generic.py

@@ -62,6 +62,7 @@
     IgnoreRaise,
     IndexKeyFunc,
     IndexLabel,
+    InterpolateOptions,
     IntervalClosedType,
     JSONSerializable,
     Level,
@@ -7753,27 +7754,7 @@ def replace(
     @final
     def interpolate(
         self,
-        method: Literal[
-            "linear",
-            "time",
-            "index",
-            "values",
-            "pad",
-            "nearest",
-            "zero",
-            "slinear",
-            "quadratic",
-            "cubic",
-            "barycentric",
-            "polynomial",
-            "krogh",
-            "piecewise_polynomial",
-            "spline",
-            "pchip",
-            "akima",
-            "cubicspline",
-            "from_derivatives",
-        ] = "linear",
+        method: InterpolateOptions = "linear",
         *,
         axis: Axis = 0,
         limit: int | None = None,