BUG: pd.to_datetime() throws if caching is on with Null-like arguments

pandas/core/base.py

@@ -33,6 +33,10 @@
                             unique='IndexOpsMixin', duplicated='IndexOpsMixin')
 
 
+class InvalidIndexError(Exception):
+    pass
+
+
 class StringMixin(object):
     """implements string methods so long as object defines a `__unicode__`
     method.
@@ -1201,7 +1205,13 @@ def _map_values(self, mapper, na_action=None):
             else:
                 values = self.values
 
-            indexer = mapper.index.get_indexer(values)
+            try:
+                indexer = mapper.index.get_indexer(values)
+            except InvalidIndexError:
+                from pandas import Series
+                mapper = Series(algorithms.unique(mapper))
+                indexer = mapper.index.get_indexer(values)
+
             new_values = algorithms.take_1d(mapper._values, indexer)
 
             return new_values

pandas/core/indexes/base.py

@@ -37,7 +37,7 @@
 from pandas.core.accessor import CachedAccessor, DirNamesMixin
 import pandas.core.algorithms as algos
 from pandas.core.arrays import ExtensionArray
-from pandas.core.base import IndexOpsMixin, PandasObject
+from pandas.core.base import IndexOpsMixin, InvalidIndexError, PandasObject
 import pandas.core.common as com
 from pandas.core.indexes.frozen import FrozenList
 import pandas.core.missing as missing
@@ -143,10 +143,6 @@ def index_arithmetic_method(self, other):
     return set_function_name(index_arithmetic_method, name, cls)
 
 
-class InvalidIndexError(Exception):
-    pass
-
-
 _o_dtype = np.dtype(object)
 _Identity = object
 

pandas/tests/series/test_timeseries.py

@@ -33,6 +33,19 @@ def _simple_ts(start, end, freq='D'):
     return Series(np.random.randn(len(rng)), index=rng)
 
 
+def test_NA_values_with_cache():
+    # GH 22305
+    na_values = [None, np.nan, pd.NaT]
+    # check pairwise, that no pair of na values
+    # is mangled
+    for f in na_values:
+        for s in na_values:
+            if f is not s:  # otherwise not unique
+                expected = Index([NaT, NaT], dtype='datetime64[ns]')
+                result = to_datetime([f, s], cache=True)
+                tm.assert_index_equal(result, expected)
+
+
 def assert_range_equal(left, right):
     assert (left.equals(right))
     assert (left.freq == right.freq)