DEPR: Disallow indexing an Index with a float

doc/source/whatsnew/v2.0.0.rst

@@ -275,6 +275,7 @@ Removal of prior version deprecations/changes
 - Enforced :meth:`Rolling.count` with ``min_periods=None`` to default to the size of the window (:issue:`31302`)
 - Renamed ``fname`` to ``path`` in :meth:`DataFrame.to_parquet`, :meth:`DataFrame.to_stata` and :meth:`DataFrame.to_feather` (:issue:`30338`)
 - Enforced disallowing indexing a :class:`Series` with a single item list with a slice (e.g. ``ser[[slice(0, 2)]]``). Either convert the list to tuple, or pass the slice directly instead (:issue:`31333`)
+- Enforced disallowing indexing an :class:`Index` object with a float key which will raise an ``IndexError`` (:issue:`34191`).
 - Enforced the ``display.max_colwidth`` option to not accept negative integers (:issue:`31569`)
 - Removed the ``display.column_space`` option in favor of ``df.to_string(col_space=...)`` (:issue:`47280`)
 - Removed the deprecated method ``mad`` from pandas classes (:issue:`11787`)

pandas/core/common.py

@@ -148,30 +148,24 @@ def is_bool_indexer(key: Any) -> bool:
     return False
 
 
-def cast_scalar_indexer(val, warn_float: bool = False):
+def cast_scalar_indexer(val):
     """
     To avoid numpy DeprecationWarnings, cast float to integer where valid.
 
     Parameters
     ----------
     val : scalar
-    warn_float : bool, default False
-        If True, issue deprecation warning for a float indexer.
 
     Returns
     -------
     outval : scalar
     """
     # assumes lib.is_scalar(val)
     if lib.is_float(val) and val.is_integer():
-        if warn_float:
-            warnings.warn(
-                "Indexing with a float is deprecated, and will raise an IndexError "
-                "in pandas 2.0. You can manually convert to an integer key instead.",
-                FutureWarning,
-                stacklevel=find_stack_level(),
-            )
-        return int(val)
+        raise IndexError(
+            "Indexing with a float is not allowed. Manually convert "
+            f"to {val} to an integer key instead.",
+        )
     return val
 
 

pandas/core/indexes/base.py

@@ -5221,7 +5221,7 @@ def __getitem__(self, key):
 
         if is_integer(key) or is_float(key):
             # GH#44051 exclude bool, which would return a 2d ndarray
-            key = com.cast_scalar_indexer(key, warn_float=True)
+            key = com.cast_scalar_indexer(key)
             return getitem(key)
 
         if isinstance(key, slice):

pandas/core/indexes/multi.py

@@ -2031,7 +2031,7 @@ def __reduce__(self):
 
     def __getitem__(self, key):
         if is_scalar(key):
-            key = com.cast_scalar_indexer(key, warn_float=True)
+            key = com.cast_scalar_indexer(key)
 
             retval = []
             for lev, level_codes in zip(self.levels, self.codes):

pandas/tests/indexes/test_indexing.py

@@ -287,14 +287,11 @@ def test_putmask_with_wrong_mask(self, index):
 @pytest.mark.parametrize(
     "idx", [Index([1, 2, 3]), Index([0.1, 0.2, 0.3]), Index(["a", "b", "c"])]
 )
-def test_getitem_deprecated_float(idx):
-    # https://github.com/pandas-dev/pandas/issues/34191
+def test_getitem_raises_float(idx):
+    # https://github.com/pandas-dev/pandas/issues/34191; enforced 2.0
 
-    with tm.assert_produces_warning(FutureWarning):
-        result = idx[1.0]
-
-    expected = idx[1]
-    assert result == expected
+    with pytest.raises(IndexError, match="Indexing with a float is not allowed"):
+        idx[1.0]
 
 
 @pytest.mark.parametrize(