fix empty list case

Author: jorisvandenbossche

pandas/core/arrays/datetimelike.py

@@ -517,16 +517,17 @@ def __getitem__(self, key):
                 return self._box_func(val)
             return type(self)(val, dtype=self.dtype)
 
-        if is_list_like(key) and not isinstance(key, tuple):
-            key = check_array_indexer(self, key)
-
         if com.is_bool_indexer(key):
-            # can still have object dtype
+            # first check for boolean, because check_array_indexer doesn't
+            # allow object dtype
             key = np.asarray(key, dtype=bool)
+            key = check_array_indexer(self, key)
             if key.all():
                 key = slice(0, None, None)
             else:
                 key = lib.maybe_booleans_to_slice(key.view(np.uint8))
+        elif is_list_like(key) and not isinstance(key, tuple):
+            key = check_array_indexer(self, key)
 
         is_period = is_period_dtype(self)
         if is_period:

pandas/core/indexers.py

@@ -371,6 +371,9 @@ def check_array_indexer(array: AnyArrayLike, indexer) -> np.ndarray:
 
     if not is_array_like(indexer):
         indexer = pd_array(indexer)
+        if len(indexer) == 0:
+            # empty list is converted to float array by pd.array
+            indexer = np.array([], dtype=np.intp)
     dtype = indexer.dtype
     if is_bool_dtype(dtype):
         try:

pandas/tests/extension/base/getitem.py

@@ -97,6 +97,15 @@ def test_getitem_scalar_na(self, data_missing, na_cmp, na_value):
         result = data_missing[0]
         assert na_cmp(result, na_value)
 
+    def test_getitem_empty(self, data):
+        # Indexing with empty list
+        result = data[[]]
+        assert len(result) == 0
+        assert isinstance(result, type(data))
+
+        expected = data[np.array([], dtype="int64")]
+        self.assert_extension_array_equal(result, expected)
+
     def test_getitem_mask(self, data):
         # Empty mask, raw array
         mask = np.zeros(len(data), dtype=bool)
@@ -153,7 +162,10 @@ def test_getitem_boolean_array_mask_raises(self, data):
         mask = pd.array(np.zeros(data.shape, dtype="bool"), dtype="boolean")
         mask[:2] = pd.NA
 
-        msg = "Cannot mask with a boolean indexer containing NA values"
+        msg = (
+            "Cannot mask with a boolean indexer containing NA values|"
+            "cannot mask with array containing NA / NaN values"
+        )
         with pytest.raises(ValueError, match=msg):
             data[mask]