BUG: value_counts may raise OutOfBoundsDatetime

doc/source/whatsnew/v0.19.0.txt

@@ -747,6 +747,8 @@ Bug Fixes
 - Bug in invalid datetime parsing in ``to_datetime`` and ``DatetimeIndex`` may raise ``TypeError`` rather than ``ValueError`` (:issue:`11169`, :issue:`11287`)
 - Bug in ``Index`` created with tz-aware ``Timestamp`` and mismatched ``tz`` option incorrectly coerces timezone (:issue:`13692`)
 - Bug in ``DatetimeIndex`` with nanosecond frequency does not include timestamp specified with ``end`` (:issue:`13672`)
+- Bug in ``Index`` raises ``OutOfBoundsDatetime`` if ``datetime`` exceeds ``datetime64[ns]`` bounds, rather than coercing to ``object`` dtype (:issue:`13663`)
+- Bug in ``.value_counts`` raises ``OutOfBoundsDatetime`` if data exceeds ``datetime64[ns]`` bounds (:issue:`13663`)
 
 - Bug in ``Categorical.remove_unused_categories()`` changes ``.codes`` dtype to platform int (:issue:`13261`)
 - Bug in ``groupby`` with ``as_index=False`` returns all NaN's when grouping on multiple columns including a categorical one (:issue:`13204`)

pandas/core/series.py

@@ -291,11 +291,13 @@ def _set_axis(self, axis, labels, fastpath=False):
 
             if not isinstance(labels,
                               (DatetimeIndex, PeriodIndex, TimedeltaIndex)):
-                labels = DatetimeIndex(labels)
-
-                # need to set here becuase we changed the index
-                if fastpath:
-                    self._data.set_axis(axis, labels)
+                try:
+                    labels = DatetimeIndex(labels)
+                    # need to set here becuase we changed the index
+                    if fastpath:
+                        self._data.set_axis(axis, labels)
+                except tslib.OutOfBoundsDatetime:
+                    pass
         self._set_subtyp(is_all_dates)
 
         object.__setattr__(self, '_index', labels)

pandas/indexes/base.py

@@ -258,13 +258,15 @@ def __new__(cls, data=None, dtype=None, copy=False, name=None,
                     pass
                 elif inferred != 'string':
                     if inferred.startswith('datetime'):
-
                         if (lib.is_datetime_with_singletz_array(subarr) or
                                 'tz' in kwargs):
                             # only when subarr has the same tz
                             from pandas.tseries.index import DatetimeIndex
-                            return DatetimeIndex(subarr, copy=copy, name=name,
-                                                 **kwargs)
+                            try:
+                                return DatetimeIndex(subarr, copy=copy,
+                                                     name=name, **kwargs)
+                            except tslib.OutOfBoundsDatetime:
+                                pass
 
                     elif inferred.startswith('timedelta'):
                         from pandas.tseries.tdi import TimedeltaIndex

pandas/tests/indexes/test_datetimelike.py

@@ -1,6 +1,6 @@
 # -*- coding: utf-8 -*-
 
-from datetime import timedelta, time
+from datetime import datetime, timedelta, time
 
 import numpy as np
 
@@ -12,7 +12,7 @@
 import pandas.util.testing as tm
 
 import pandas as pd
-from pandas.lib import Timestamp
+from pandas.tslib import Timestamp, OutOfBoundsDatetime
 
 from .common import Base
 
@@ -336,6 +336,18 @@ def test_construction_base_constructor(self):
         tm.assert_index_equal(pd.Index(np.array(arr)),
                               pd.DatetimeIndex(np.array(arr)))
 
+    def test_construction_outofbounds(self):
+        # GH 13663
+        dates = [datetime(3000, 1, 1), datetime(4000, 1, 1),
+                 datetime(5000, 1, 1), datetime(6000, 1, 1)]
+        exp = Index(dates, dtype=object)
+        # coerces to object
+        tm.assert_index_equal(Index(dates), exp)
+
+        with tm.assertRaises(OutOfBoundsDatetime):
+            # can't create DatetimeIndex
+            DatetimeIndex(dates)
+
     def test_astype(self):
         # GH 13149, GH 13209
         idx = DatetimeIndex(['2016-05-16', 'NaT', NaT, np.NaN])

pandas/tests/test_algos.py

@@ -4,7 +4,7 @@
 import numpy as np
 from numpy.random import RandomState
 from numpy import nan
-import datetime
+from datetime import datetime
 from pandas import Series, Categorical, CategoricalIndex, Index
 import pandas as pd
 
@@ -121,7 +121,7 @@ def test_mixed_integer(self):
 
     def test_unsortable(self):
         # GH 13714
-        arr = np.array([1, 2, datetime.datetime.now(), 0, 3], dtype=object)
+        arr = np.array([1, 2, datetime.now(), 0, 3], dtype=object)
         if compat.PY2 and not pd._np_version_under1p10:
             # RuntimeWarning: tp_compare didn't return -1 or -2 for exception
             with tm.assert_produces_warning(RuntimeWarning):
@@ -556,6 +556,18 @@ def test_value_counts_nat(self):
         tm.assert_series_equal(algos.value_counts(dt), exp_dt)
         # TODO same for (timedelta)
 
+    def test_value_counts_datetime_outofbounds(self):
+        # GH 13663
+        s = pd.Series([datetime(3000, 1, 1), datetime(5000, 1, 1),
+                       datetime(5000, 1, 1), datetime(6000, 1, 1),
+                       datetime(3000, 1, 1), datetime(3000, 1, 1)])
+        res = s.value_counts()
+
+        exp_index = pd.Index([datetime(3000, 1, 1), datetime(5000, 1, 1),
+                              datetime(6000, 1, 1)], dtype=object)
+        exp = pd.Series([3, 2, 1], index=exp_index)
+        tm.assert_series_equal(res, exp)
+
     def test_categorical(self):
         s = Series(pd.Categorical(list('aaabbc')))
         result = s.value_counts()
@@ -818,7 +830,7 @@ def _check(arr):
 def test_pad_backfill_object_segfault():
 
     old = np.array([], dtype='O')
-    new = np.array([datetime.datetime(2010, 12, 31)], dtype='O')
+    new = np.array([datetime(2010, 12, 31)], dtype='O')
 
     result = _algos.pad_object(old, new)
     expected = np.array([-1], dtype=np.int64)