see if intp fixes int32 problems

pandas-dev · Nov 7, 2022 · 8b52054 · 8b52054
1 parent b332214
commit 8b52054
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Showing 3 changed files with 12 additions and 3 deletions.
diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py
@@ -555,7 +555,7 @@ def _ensure_array(cls, data, dtype, copy: bool):
             data = data.copy()
         return data
 
-    @final
+    # @final (temporary off until merge NumericIndex into Index
     @classmethod
     def _dtype_to_subclass(cls, dtype: DtypeObj):
         # Delay import for perf. https://github.com/pandas-dev/pandas/pull/31423
@@ -1051,6 +1051,7 @@ def astype(self, dtype, copy: bool = True):
                     UInt64Index,
                 )
 
+                klass: Index
                 if is_signed_integer_dtype(dtype):
                     klass = Int64Index
                 elif is_unsigned_integer_dtype(dtype):

diff --git a/pandas/tests/window/test_groupby.py b/pandas/tests/window/test_groupby.py
@@ -919,7 +919,10 @@ def test_nan_and_zero_endpoints(self):
             arr,
             name="adl2",
             index=MultiIndex.from_arrays(
-                [[0] * 999 + [1], [0] * 999 + [1]], names=["index", "index"]
+                [
+                    Index([0] * 999 + [1], dtype=np.intp, name="index"),
+                    Index([0] * 999 + [1], dtype=np.intp, name="index"),
+                ],
             ),
         )
         tm.assert_series_equal(result, expected)

diff --git a/pandas/tests/window/test_pairwise.py b/pandas/tests/window/test_pairwise.py
@@ -99,6 +99,7 @@ def test_flex_binary_frame(method, frame):
     exp = DataFrame(
         {k: getattr(frame[k].rolling(window=10), method)(frame2[k]) for k in frame}
     )
+    exp.columns = exp.columns.astype(np.intp)
     tm.assert_frame_equal(res3, exp)
 
 
@@ -431,7 +432,11 @@ def test_multindex_columns_pairwise_func(self):
         expected = DataFrame(
             np.nan,
             index=MultiIndex.from_arrays(
-                [np.repeat(np.arange(5), 2), ["M", "N"] * 5, ["P", "Q"] * 5],
+                [
+                    np.repeat(np.arange(5, dtype=np.int64), 2),
+                    ["M", "N"] * 5,
+                    ["P", "Q"] * 5,
+                ],
                 names=[None, "a", "b"],
             ),
             columns=columns,