BUG: fix failing DataFrame.loc when indexing with an IntervalIndex

doc/source/whatsnew/v0.24.0.txt

@@ -669,6 +669,7 @@ Indexing
 - Bug where indexing with a Numpy array containing negative values would mutate the indexer (:issue:`21867`)
 - Bug where mixed indexes wouldn't allow integers for ``.at`` (:issue:`19860`)
 - ``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`)
 
 Missing
 ^^^^^^^

pandas/core/indexing.py

@@ -1491,7 +1491,7 @@ def __getitem__(self, key):
             try:
                 if self._is_scalar_access(key):
                     return self._getitem_scalar(key)
-            except (KeyError, IndexError):
+            except (KeyError, IndexError, AttributeError):
                 pass
             return self._getitem_tuple(key)
         else:

pandas/tests/frame/test_indexing.py

@@ -3099,6 +3099,28 @@ def test_type_error_multiindex(self):
         result = dg['x', 0]
         assert_series_equal(result, expected)
 
+    def test_interval_index(self):
+        # GH 19977
+        index = pd.interval_range(start=0, periods=3)
+        df = pd.DataFrame([[1, 2, 3], [4, 5, 6], [7, 8, 9]],
+                          index=index,
+                          columns=['A', 'B', 'C'])
+
+        expected = 1
+        result = df.loc[0.5, 'A']
+        assert_almost_equal(result, expected)
+
+        index = pd.interval_range(start=0, periods=3, closed='both')
+        df = pd.DataFrame([[1, 2, 3], [4, 5, 6], [7, 8, 9]],
+                          index=index,
+                          columns=['A', 'B', 'C'])
+
+        index_exp = pd.interval_range(start=0, periods=2,
+                                      freq=1, closed='both')
+        expected = pd.Series([1, 4], index=index_exp, name='A')
+        result = df.loc[1, 'A']
+        assert_series_equal(result, expected)
+
 
 class TestDataFrameIndexingDatetimeWithTZ(TestData):