List indexer on PeriodIndex doesn't coerce strings (pandas-dev#11278)

Author: proost

doc/source/whatsnew/v1.0.0.rst

@@ -778,6 +778,7 @@ Indexing
 - Bug when indexing with ``.loc`` where the index was a :class:`CategoricalIndex` with non-string categories didn't work (:issue:`17569`, :issue:`30225`)
 - :meth:`Index.get_indexer_non_unique` could fail with `TypeError` in some cases, such as when searching for ints in a string index (:issue:`28257`)
 - Bug in :meth:`Float64Index.get_loc` incorrectly raising ``TypeError`` instead of ``KeyError`` (:issue:`29189`)
+- List datetime string indexer could fail on `PeriodIndex` or `DatetimeIndex` (:issue:`11278`)
 
 Missing
 ^^^^^^^

pandas/core/indexing.py

@@ -4,6 +4,7 @@
 
 from pandas._libs.indexing import _NDFrameIndexerBase
 from pandas._libs.lib import item_from_zerodim
+from pandas._libs.tslibs import Period, Timestamp
 from pandas.errors import AbstractMethodError
 from pandas.util._decorators import Appender
 
@@ -18,7 +19,13 @@
     is_sparse,
 )
 from pandas.core.dtypes.concat import concat_compat
-from pandas.core.dtypes.generic import ABCDataFrame, ABCMultiIndex, ABCSeries
+from pandas.core.dtypes.generic import (
+    ABCDataFrame,
+    ABCDatetimeIndex,
+    ABCMultiIndex,
+    ABCPeriodIndex,
+    ABCSeries,
+)
 from pandas.core.dtypes.missing import _infer_fill_value, isna
 
 import pandas.core.common as com
@@ -1660,6 +1667,23 @@ def _get_partial_string_timestamp_match_key(self, key, labels):
                         new_key.append(component)
                 key = tuple(new_key)
 
+        elif isinstance(labels, (ABCDatetimeIndex, ABCPeriodIndex)):
+            if isinstance(key, list):
+                object_type_mapper = {"period": Period, "datetime64": Timestamp}
+                object_type = labels.inferred_type
+                freq_str = labels.freqstr
+
+                for i, comp in enumerate(key):
+                    try:
+                        """
+                        if labels type is period and labels freq is 'D'
+                        '2019-12-27' to Period('2019-12-27', 'D')
+                        """
+                        key[i] = object_type_mapper[object_type](comp, freq=freq_str)
+
+                    except (TypeError, ValueError, KeyError):
+                        pass
+
         return key
 
     def _getitem_axis(self, key, axis: int):

pandas/tests/indexing/test_loc.py

@@ -6,7 +6,7 @@
 import pytest
 
 import pandas as pd
-from pandas import DataFrame, Series, Timestamp, date_range
+from pandas import DataFrame, Period, Series, Timestamp, date_range, period_range
 from pandas.api.types import is_scalar
 from pandas.tests.indexing.common import Base
 import pandas.util.testing as tm
@@ -939,6 +939,68 @@ def test_loc_reverse_assignment(self):
 
         tm.assert_series_equal(result, expected)
 
+    @pytest.mark.parametrize(
+        "idx,labels,expected_idx",
+        [
+            (
+                period_range(start="2000", periods=20, freq="D"),
+                ["2000-01-04", "2000-01-08", "2000-01-12"],
+                [
+                    Period("2000-01-04", freq="D"),
+                    Period("2000-01-08", freq="D"),
+                    Period("2000-01-12", freq="D"),
+                ],
+            ),
+            (
+                date_range(start="2000", periods=20, freq="D"),
+                ["2000-01-04", "2000-01-08", "2000-01-12"],
+                [
+                    Timestamp("2000-01-04", freq="D"),
+                    Timestamp("2000-01-08", freq="D"),
+                    Timestamp("2000-01-12", freq="D"),
+                ],
+            ),
+        ],
+    )
+    def test_loc_with_datetime_string_list(self, idx, labels, expected_idx):
+        # GH 11278
+        s = Series(range(20), index=idx)
+        df = DataFrame(range(20), index=idx)
+
+        expected_value = [3, 7, 11]
+        expected_s = Series(expected_value, expected_idx)
+        expected_df = DataFrame(expected_value, expected_idx)
+
+        tm.assert_series_equal(expected_s, s.loc[labels])
+        tm.assert_series_equal(expected_s, s[labels])
+        tm.assert_frame_equal(expected_df, df.loc[labels])
+
+    @pytest.mark.parametrize(
+        "idx,labels",
+        [
+            (
+                period_range(start="2000", periods=20, freq="D"),
+                ["2000-01-04", "2000-01-30", "2000-01-12"],
+            ),
+            (
+                date_range(start="2000", periods=20, freq="D"),
+                ["2000-01-04", "2000-01-30", "2000-01-12"],
+            ),
+        ],
+    )
+    def test_loc_with_datetime_string_and_missing_value(self, idx, labels):
+        # GH 11278
+        s = Series(range(20), index=idx)
+        df = DataFrame(range(20), index=idx)
+
+        msg = r"Passing list-likes to .loc or \[\] with any missing labels"
+        with pytest.raises(KeyError, match=msg):
+            s.loc[labels]
+        with pytest.raises(KeyError, match=msg):
+            s[labels]
+        with pytest.raises(KeyError, match=msg):
+            df.loc[labels]
+
 
 def test_series_loc_getitem_label_list_missing_values():
     # gh-11428