all-nan inferred to correct dtype

Author: jreback

doc/source/whatsnew/v0.22.0.txt

@@ -75,7 +75,7 @@ Other API Changes
 - :class:`CacheableOffset` and :class:`WeekDay` are no longer available in the ``pandas.tseries.offsets`` module (:issue:`17830`)
 - `tseries.frequencies.get_freq_group()` and `tseries.frequencies.DAYS` are removed from the public API (:issue:`18034`)
 - :func:`Series.truncate` and :func:`DataFrame.truncate` will raise a ``ValueError`` if the index is not sorted instead of an unhelpful ``KeyError`` (:issue:`17935`)
-- :func:`Index.map` can now accept ``Series`` and dictionary input objects (:issue:`12756`).
+- :func:`Index.map` can now accept ``Series`` and dictionary input objects (:issue:`12756`, :issue:`18482`).
 - :func:`Dataframe.unstack` will now default to filling with ``np.nan`` for ``object`` columns. (:issue:`12815`)
 - :class:`IntervalIndex` constructor will raise if the ``closed`` parameter conflicts with how the input data is inferred to be closed (:issue:`18421`)
 - Inserting missing values into indexes will work for all types of indexes and automatically insert the correct type of missing value (``NaN``, ``NaT``, etc.) regardless of the type passed in (:issue:`18295`)

pandas/core/indexes/base.py

@@ -2912,6 +2912,8 @@ def map(self, mapper, na_action=None):
             mapper, na_action=na_action)
 
         attributes = self._get_attributes_dict()
+
+        # we can return a MultiIndex
         if new_values.size and isinstance(new_values[0], tuple):
             if isinstance(self, MultiIndex):
                 names = self.names
@@ -2932,6 +2934,17 @@ def map(self, mapper, na_action=None):
             if inferred == 'integer':
                 attributes['dtype'] = self.dtype
 
+        elif not new_values.size:
+            # empty
+            attributes['dtype'] = self.dtype
+        elif isna(new_values).all():
+            # all nan
+            inferred = lib.infer_dtype(self)
+            if inferred in ['datetime', 'datetime64',
+                            'timedelta', 'timedelta64',
+                            'period']:
+                new_values = [libts.NaT] * len(new_values)
+
         return Index(new_values, **attributes)
 
     def isin(self, values, level=None):

pandas/tests/indexes/datetimelike.py

@@ -1,7 +1,6 @@
 """ generic datetimelike tests """
 import pytest
 import pandas as pd
-import numpy as np
 from .common import Base
 import pandas.util.testing as tm
 
@@ -73,6 +72,6 @@ def test_map_dictlike(self, mapper):
 
         # empty map; these map to np.nan because we cannot know
         # to re-infer things
-        expected = pd.Index([np.nan] * len(self.index))
+        expected = pd.Index([pd.NaT] * len(self.index))
         result = self.index.map(mapper([], []))
         tm.assert_index_equal(result, expected)

pandas/tests/indexes/test_base.py

@@ -878,7 +878,7 @@ def test_map_dictlike(self, mapper):
             if name == 'uintIndex':
                 expected = expected.astype('uint64')
             elif name == 'empty':
-                expected = Float64Index([])
+                expected = Index([])
 
             result = index.map(mapper(expected, index))
             tm.assert_index_equal(result, expected)