TYP: Typing fixes and improvements related to scipy.interpolate (#62211)

Author: jorenham

pandas/core/missing.py

@@ -45,8 +45,12 @@
 )
 
 if TYPE_CHECKING:
+    from typing import TypeAlias
+
     from pandas import Index
 
+    _CubicBC: TypeAlias = Literal["not-a-knot", "clamped", "natural", "periodic"]
+
 
 def check_value_size(value, mask: npt.NDArray[np.bool_], length: int):
     """
@@ -652,7 +656,7 @@ def _akima_interpolate(
     xi: np.ndarray,
     yi: np.ndarray,
     x: np.ndarray,
-    der: int | list[int] | None = 0,
+    der: int = 0,
     axis: AxisInt = 0,
 ):
     """
@@ -673,10 +677,8 @@ def _akima_interpolate(
     x : np.ndarray
         Of length M.
     der : int, optional
-        How many derivatives to extract; None for all potentially
-        nonzero derivatives (that is a number equal to the number
-        of points), or a list of derivatives to extract. This number
-        includes the function value as 0th derivative.
+        How many derivatives to extract. This number includes the function
+        value as 0th derivative.
     axis : int, optional
         Axis in the yi array corresponding to the x-coordinate values.
 
@@ -702,9 +704,9 @@ def _cubicspline_interpolate(
     yi: np.ndarray,
     x: np.ndarray,
     axis: AxisInt = 0,
-    bc_type: str | tuple[Any, Any] = "not-a-knot",
-    extrapolate=None,
-):
+    bc_type: _CubicBC | tuple[Any, Any] = "not-a-knot",
+    extrapolate: Literal["periodic"] | bool | None = None,
+) -> np.ndarray:
     """
     Convenience function for cubic spline data interpolator.