CLN: ensure_int64->ensure_platform_int

pandas/core/generic.py

@@ -71,8 +71,8 @@
 )
 
 from pandas.core.dtypes.common import (
-    ensure_int64,
     ensure_object,
+    ensure_platform_int,
     ensure_str,
     is_bool,
     is_bool_dtype,
@@ -4887,7 +4887,7 @@ def _reindex_with_indexers(
 
             index = ensure_index(index)
             if indexer is not None:
-                indexer = ensure_int64(indexer)
+                indexer = ensure_platform_int(indexer)
 
             # TODO: speed up on homogeneous DataFrame objects
             new_data = new_data.reindex_indexer(

pandas/core/indexes/base.py

@@ -3846,9 +3846,9 @@ def _reindex_non_unique(self, target):
 
             missing = ensure_platform_int(missing)
             missing_labels = target.take(missing)
-            missing_indexer = ensure_int64(length[~check])
+            missing_indexer = ensure_platform_int(length[~check])
             cur_labels = self.take(indexer[check]).values
-            cur_indexer = ensure_int64(length[check])
+            cur_indexer = ensure_platform_int(length[check])
 
             new_labels = np.empty((len(indexer),), dtype=object)
             new_labels[cur_indexer] = cur_labels

pandas/core/internals/array_manager.py

@@ -28,7 +28,7 @@
     soft_convert_objects,
 )
 from pandas.core.dtypes.common import (
-    ensure_int64,
+    ensure_platform_int,
     is_datetime64_ns_dtype,
     is_dtype_equal,
     is_extension_array_dtype,
@@ -1007,7 +1007,7 @@ def _reindex_indexer(
 
         else:
             validate_indices(indexer, len(self._axes[0]))
-            indexer = ensure_int64(indexer)
+            indexer = ensure_platform_int(indexer)
             if (indexer == -1).any():
                 allow_fill = True
             else:
@@ -1098,7 +1098,7 @@ def unstack(self, unstacker, fill_value) -> ArrayManager:
             new_indexer[unstacker.mask] = indexer
             allow_fill = True
         new_indexer2D = new_indexer.reshape(*unstacker.full_shape)
-        new_indexer2D = ensure_int64(new_indexer2D)
+        new_indexer2D = ensure_platform_int(new_indexer2D)
 
         new_arrays = []
         for arr in self.arrays:

pandas/core/reshape/tile.py

@@ -11,7 +11,7 @@
 
 from pandas.core.dtypes.common import (
     DT64NS_DTYPE,
-    ensure_int64,
+    ensure_platform_int,
     is_bool_dtype,
     is_categorical_dtype,
     is_datetime64_dtype,
@@ -413,7 +413,7 @@ def _bins_to_cuts(
             bins = unique_bins
 
     side = "left" if right else "right"
-    ids = ensure_int64(bins.searchsorted(x, side=side))
+    ids = ensure_platform_int(bins.searchsorted(x, side=side))
 
     if include_lowest:
         ids[x == bins[0]] = 1

pandas/tests/reshape/test_cut.py

@@ -414,7 +414,7 @@ def test_single_bin(data, length):
     ser = Series([data] * length)
     result = cut(ser, 1, labels=False)
 
-    expected = Series([0] * length)
+    expected = Series([0] * length, dtype=np.intp)
     tm.assert_series_equal(result, expected)
 
 

pandas/tests/reshape/test_qcut.py

@@ -202,7 +202,7 @@ def test_single_quantile(data, start, end, length, labels):
         intervals = IntervalIndex([Interval(start, end)] * length, closed="right")
         expected = Series(intervals).astype(CDT(ordered=True))
     else:
-        expected = Series([0] * length)
+        expected = Series([0] * length, dtype=np.intp)
 
     tm.assert_series_equal(result, expected)