change np.float_ to np.double

Author: Dr-Irv

pandas-stubs/core/resample.pyi

@@ -163,7 +163,7 @@ class Resampler(BaseGroupBy[NDFrameT]):
     def count(self: Resampler[DataFrame]) -> DataFrame: ...
     def quantile(
         self,
-        q: float | list[float] | npt.NDArray[np.float_] | Series[float] = ...,
+        q: float | list[float] | npt.NDArray[np.double] | Series[float] = ...,
         **kwargs,
     ) -> NDFrameT: ...
 

pandas-stubs/core/reshape/tile.pyi

@@ -250,7 +250,7 @@ def qcut(
     retbins: Literal[True],
     precision: int = ...,
     duplicates: Literal["raise", "drop"] = ...,
-) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.float_]]: ...
+) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.double]]: ...
 @overload
 def qcut(
     x: Series,
@@ -260,7 +260,7 @@ def qcut(
     retbins: Literal[True],
     precision: int = ...,
     duplicates: Literal["raise", "drop"] = ...,
-) -> tuple[Series, npt.NDArray[np.float_]]: ...
+) -> tuple[Series, npt.NDArray[np.double]]: ...
 @overload
 def qcut(
     x: Index | npt.NDArray | Sequence[int] | Sequence[float],
@@ -270,4 +270,4 @@ def qcut(
     retbins: Literal[True],
     precision: int = ...,
     duplicates: Literal["raise", "drop"] = ...,
-) -> tuple[Categorical, npt.NDArray[np.float_]]: ...
+) -> tuple[Categorical, npt.NDArray[np.double]]: ...

pandas-stubs/plotting/_core.pyi

@@ -340,7 +340,7 @@ class PlotAccessor:
             | Callable[[gaussian_kde], float]
             | None
         ) = ...,
-        ind: npt.NDArray[np.float_] | int | None = ...,
+        ind: npt.NDArray[np.double] | int | None = ...,
         *,
         subplots: Literal[False] | None = ...,
         **kwargs,
@@ -354,7 +354,7 @@ class PlotAccessor:
             | Callable[[gaussian_kde], float]
             | None
         ) = ...,
-        ind: npt.NDArray[np.float_] | int | None = ...,
+        ind: npt.NDArray[np.double] | int | None = ...,
         *,
         subplots: Literal[True],
         **kwargs,

tests/test_pandas.py

@@ -1004,10 +1004,10 @@ def test_qcut() -> None:
     check(assert_type(c0, pd.Categorical), pd.Categorical)
     check(assert_type(d0, pd.Series), pd.Series)
 
-    check(assert_type(a1, npt.NDArray[np.float_]), np.ndarray)
-    check(assert_type(b1, npt.NDArray[np.float_]), np.ndarray)
-    check(assert_type(c1, npt.NDArray[np.float_]), np.ndarray)
-    check(assert_type(d1, npt.NDArray[np.float_]), np.ndarray)
+    check(assert_type(a1, npt.NDArray[np.double]), np.ndarray)
+    check(assert_type(b1, npt.NDArray[np.double]), np.ndarray)
+    check(assert_type(c1, npt.NDArray[np.double]), np.ndarray)
+    check(assert_type(d1, npt.NDArray[np.double]), np.ndarray)
 
     e0, e1 = pd.qcut(val_list, [0.25, 0.5, 0.75], retbins=True)
     f0, f1 = pd.qcut(val_arr, np.array([0.25, 0.5, 0.75]), retbins=True)
@@ -1023,12 +1023,12 @@ def test_qcut() -> None:
     check(assert_type(i0, npt.NDArray[np.intp]), np.ndarray)
     check(assert_type(j0, npt.NDArray[np.intp]), np.ndarray)
 
-    check(assert_type(e1, npt.NDArray[np.float_]), np.ndarray)
-    check(assert_type(f1, npt.NDArray[np.float_]), np.ndarray)
-    check(assert_type(g1, npt.NDArray[np.float_]), np.ndarray)
-    check(assert_type(h1, npt.NDArray[np.float_]), np.ndarray)
-    check(assert_type(i1, npt.NDArray[np.float_]), np.ndarray)
-    check(assert_type(j1, npt.NDArray[np.float_]), np.ndarray)
+    check(assert_type(e1, npt.NDArray[np.double]), np.ndarray)
+    check(assert_type(f1, npt.NDArray[np.double]), np.ndarray)
+    check(assert_type(g1, npt.NDArray[np.double]), np.ndarray)
+    check(assert_type(h1, npt.NDArray[np.double]), np.ndarray)
+    check(assert_type(i1, npt.NDArray[np.double]), np.ndarray)
+    check(assert_type(j1, npt.NDArray[np.double]), np.ndarray)
 
 
 def test_merge() -> None: