BUG: DatetimeIndex.get_loc/get_value raise InvalidIndexError

pandas/core/groupby/grouper.py

@@ -27,6 +27,7 @@
 from pandas.core.groupby import ops
 from pandas.core.groupby.categorical import recode_for_groupby, recode_from_groupby
 from pandas.core.indexes.api import CategoricalIndex, Index, MultiIndex
+from pandas.core.indexes.base import InvalidIndexError
 from pandas.core.series import Series
 
 from pandas.io.formats.printing import pprint_thing
@@ -565,7 +566,7 @@ def is_in_axis(key) -> bool:
             items = obj._data.items
             try:
                 items.get_loc(key)
-            except (KeyError, TypeError):
+            except (KeyError, TypeError, InvalidIndexError):
                 # TypeError shows up here if we pass e.g. Int64Index
                 return False
 

pandas/core/indexes/datetimes.py

@@ -27,7 +27,7 @@
     validate_tz_from_dtype,
 )
 import pandas.core.common as com
-from pandas.core.indexes.base import Index, maybe_extract_name
+from pandas.core.indexes.base import Index, InvalidIndexError, maybe_extract_name
 from pandas.core.indexes.datetimelike import (
     DatetimelikeDelegateMixin,
     DatetimeTimedeltaMixin,
@@ -641,6 +641,8 @@ def get_value(self, series, key):
         Fast lookup of value from 1-dimensional ndarray. Only use this if you
         know what you're doing
         """
+        if not is_scalar(key):
+            raise InvalidIndexError(key)
 
         if isinstance(key, (datetime, np.datetime64)):
             return self.get_value_maybe_box(series, key)
@@ -677,6 +679,9 @@ def get_loc(self, key, method=None, tolerance=None):
         -------
         loc : int
         """
+        if not is_scalar(key):
+            raise InvalidIndexError(key)
+
         if is_valid_nat_for_dtype(key, self.dtype):
             key = NaT
 

pandas/core/indexes/multi.py

@@ -2778,7 +2778,7 @@ def maybe_mi_droplevels(indexer, levels, drop_level: bool):
                     indexer = self._get_level_indexer(key, level=level)
                     new_index = maybe_mi_droplevels(indexer, [0], drop_level)
                     return indexer, new_index
-            except TypeError:
+            except (TypeError, InvalidIndexError):
                 pass
 
             if not any(isinstance(k, slice) for k in key):

pandas/core/series.py

@@ -947,6 +947,9 @@ def __setitem__(self, key, value):
                 self[:] = value
             else:
                 self.loc[key] = value
+        except InvalidIndexError:
+            # e.g. slice
+            self._set_with(key, value)
 
         except TypeError as e:
             if isinstance(key, tuple) and not isinstance(self.index, MultiIndex):

pandas/tests/indexes/datetimes/test_indexing.py

@@ -7,6 +7,7 @@
 import pandas as pd
 from pandas import DatetimeIndex, Index, Timestamp, date_range, notna
 import pandas._testing as tm
+from pandas.core.indexes.base import InvalidIndexError
 
 from pandas.tseries.offsets import BDay, CDay
 
@@ -697,7 +698,7 @@ def test_get_loc(self):
 
         with pytest.raises(KeyError, match="'foobar'"):
             idx.get_loc("foobar")
-        with pytest.raises(TypeError):
+        with pytest.raises(InvalidIndexError, match=r"slice\(None, 2, None\)"):
             idx.get_loc(slice(2))
 
         idx = pd.to_datetime(["2000-01-01", "2000-01-04"])