BUG: NumericIndex.insert(0, False) casting to int

doc/source/whatsnew/v1.2.0.rst

@@ -619,6 +619,7 @@ Indexing
 - Bug in indexing on a :class:`Series` or :class:`DataFrame` with a :class:`CategoricalIndex` using listlike indexer that contains elements that are in the index's ``categories`` but not in the index itself failing to raise ``KeyError`` (:issue:`37901`)
 - Bug in :meth:`DataFrame.iloc` and :meth:`Series.iloc` aligning objects in ``__setitem__`` (:issue:`22046`)
 - Bug in :meth:`DataFrame.loc` did not raise ``KeyError`` when missing combination was given with ``slice(None)`` for remaining levels (:issue:`19556`)
+- Bug on inserting a boolean label into a :class:`DataFrame` with a numeric :class:`Index` columns incorrectly casting to integer (:issue:`36319`)
 
 Missing
 ^^^^^^^

pandas/core/indexes/numeric.py

@@ -124,6 +124,12 @@ def _validate_fill_value(self, value):
             raise TypeError
         elif isinstance(value, str) or lib.is_complex(value):
             raise TypeError
+        elif is_scalar(value) and isna(value):
+            if is_valid_nat_for_dtype(value, self.dtype):
+                value = self._na_value
+            else:
+                # NaT, np.datetime64("NaT"), np.timedelta64("NaT")
+                raise TypeError
 
         return value
 
@@ -162,13 +168,10 @@ def _is_all_dates(self) -> bool:
 
     @doc(Index.insert)
     def insert(self, loc: int, item):
-        # treat NA values as nans:
-        if is_scalar(item) and isna(item):
-            if is_valid_nat_for_dtype(item, self.dtype):
-                item = self._na_value
-            else:
-                # NaT, np.datetime64("NaT"), np.timedelta64("NaT")
-                return self.astype(object).insert(loc, item)
+        try:
+            item = self._validate_fill_value(item)
+        except TypeError:
+            return self.astype(object).insert(loc, item)
 
         return super().insert(loc, item)
 

pandas/tests/frame/indexing/test_setitem.py

@@ -304,6 +304,20 @@ def test_setitem_complete_column_with_array(self):
         )
         tm.assert_frame_equal(df, expected)
 
+    @pytest.mark.parametrize("dtype", ["f8", "i8", "u8"])
+    def test_setitem_bool_with_numeric_index(self, dtype):
+        # GH#36319
+        cols = Index([1, 2, 3], dtype=dtype)
+        df = DataFrame(np.random.randn(3, 3), columns=cols)
+
+        df[False] = ["a", "b", "c"]
+
+        expected_cols = Index([1, 2, 3, False], dtype=object)
+        if dtype == "f8":
+            expected_cols = Index([1.0, 2.0, 3.0, False], dtype=object)
+
+        tm.assert_index_equal(df.columns, expected_cols)
+
 
 class TestDataFrameSetItemSlicing:
     def test_setitem_slice_position(self):

pandas/tests/indexing/test_coercion.py

@@ -393,7 +393,7 @@ def test_insert_index_object(self, insert, coerced_val, coerced_dtype):
         [
             (1, 1, np.int64),
             (1.1, 1.1, np.float64),
-            (False, 0, np.int64),
+            (False, False, object),  # GH#36319
             ("x", "x", object),
         ],
     )
@@ -409,7 +409,7 @@ def test_insert_index_int64(self, insert, coerced_val, coerced_dtype):
         [
             (1, 1.0, np.float64),
             (1.1, 1.1, np.float64),
-            (False, 0.0, np.float64),
+            (False, False, object),  # GH#36319
             ("x", "x", object),
         ],
     )