BUG: Check types in Index.__contains__ (pandas-dev#22085) (pandas-dev…

…#22602)

doc/source/whatsnew/v0.24.0.txt

@@ -723,6 +723,7 @@ Indexing
 - ``Float64Index.get_loc`` now raises ``KeyError`` when boolean key passed. (:issue:`19087`)
 - Bug in :meth:`DataFrame.loc` when indexing with an :class:`IntervalIndex` (:issue:`19977`)
 - :class:`Index` no longer mangles ``None``, ``NaN`` and ``NaT``, i.e. they are treated as three different keys. However, for numeric Index all three are still coerced to a ``NaN`` (:issue:`22332`)
+- Bug in `scalar in Index` if scalar is a float while the ``Index`` is of integer dtype (:issue:`22085`)
 
 Missing
 ^^^^^^^

pandas/core/indexes/numeric.py

@@ -6,6 +6,7 @@
     pandas_dtype,
     needs_i8_conversion,
     is_integer_dtype,
+    is_float,
     is_bool,
     is_bool_dtype,
     is_scalar)
@@ -162,7 +163,25 @@ def insert(self, loc, item):
 )
 
 
-class Int64Index(NumericIndex):
+class IntegerIndex(NumericIndex):
+    """
+    This is an abstract class for Int64Index, UInt64Index.
+    """
+
+    def __contains__(self, key):
+        """
+        Check if key is a float and has a decimal. If it has, return False.
+        """
+        hash(key)
+        try:
+            if is_float(key) and int(key) != key:
+                return False
+            return key in self._engine
+        except (OverflowError, TypeError, ValueError):
+            return False
+
+
+class Int64Index(IntegerIndex):
     __doc__ = _num_index_shared_docs['class_descr'] % _int64_descr_args
 
     _typ = 'int64index'
@@ -220,7 +239,7 @@ def _assert_safe_casting(cls, data, subarr):
 )
 
 
-class UInt64Index(NumericIndex):
+class UInt64Index(IntegerIndex):
     __doc__ = _num_index_shared_docs['class_descr'] % _uint64_descr_args
 
     _typ = 'uint64index'

pandas/tests/indexing/test_indexing.py

@@ -631,6 +631,21 @@ def test_mixed_index_not_contains(self, index, val):
         # GH 19860
         assert val not in index
 
+    def test_contains_with_float_index(self):
+        # GH#22085
+        integer_index = pd.Int64Index([0, 1, 2, 3])
+        uinteger_index = pd.UInt64Index([0, 1, 2, 3])
+        float_index = pd.Float64Index([0.1, 1.1, 2.2, 3.3])
+
+        for index in (integer_index, uinteger_index):
+            assert 1.1 not in index
+            assert 1.0 in index
+            assert 1 in index
+
+        assert 1.1 in float_index
+        assert 1.0 not in float_index
+        assert 1 not in float_index
+
     def test_index_type_coercion(self):
 
         with catch_warnings(record=True):