ENH: (GH3863) Timestamp.min and Timestamp.max return a valid Timestamp

RELEASE.rst

@@ -69,6 +69,8 @@ pandas 0.11.1
     - support python3 (via ``PyTables 3.0.0``) (GH3750_)
   - Add modulo operator to Series, DataFrame
   - Add ``date`` method to DatetimeIndex
+  - Timestamp.min and Timestamp.max now represent valid Timestamp instances instead
+    of the default datetime.min and datetime.max (respectively).
   - Simplified the API and added a describe method to Categorical
   - ``melt`` now accepts the optional parameters ``var_name`` and ``value_name``
     to specify custom column names of the returned DataFrame (GH3649_),

doc/source/gotchas.rst

@@ -271,9 +271,10 @@ can be represented using a 64-bit integer is limited to approximately 584 years:
 
 .. ipython:: python
 
-   begin = Timestamp(-9223285636854775809L)
+   begin = Timestamp.min
    begin
-   end = Timestamp(np.iinfo(np.int64).max)
+
+   end = Timestamp.max
    end
 
 If you need to represent time series data outside the nanosecond timespan, use

doc/source/v0.11.1.txt

@@ -289,8 +289,12 @@ Enhancements
        dff.groupby('B').filter(lambda x: len(x) > 2, dropna=False)
 
   - Series and DataFrame hist methods now take a ``figsize`` argument (GH3834_)
+
   - DatetimeIndexes no longer try to convert mixed-integer indexes during join
     operations (GH3877_)
+
+  - Timestamp.min and Timestamp.max now represent valid Timestamp instances instead
+    of the default datetime.min and datetime.max (respectively).
 
 
 Bug Fixes

pandas/tests/test_tseries.py

@@ -2,7 +2,7 @@
 
 from numpy import nan
 import numpy as np
-from pandas import Index, isnull
+from pandas import Index, isnull, Timestamp
 from pandas.util.testing import assert_almost_equal
 import pandas.util.testing as common
 import pandas.lib as lib
@@ -683,6 +683,22 @@ def test_int_index(self):
         expected = arr.sum(1)
         assert_almost_equal(result, expected)
 
+
+class TestTsUtil(unittest.TestCase):
+    def test_min_valid(self):
+        # Ensure that Timestamp.min is a valid Timestamp
+        Timestamp(Timestamp.min)
+
+    def test_max_valid(self):
+        # Ensure that Timestamp.max is a valid Timestamp
+        Timestamp(Timestamp.max)
+
+    def test_to_datetime_bijective(self):
+        # Ensure that converting to datetime and back only loses precision
+        # by going from nanoseconds to microseconds.
+        self.assertEqual(Timestamp(Timestamp.max.to_pydatetime()).value/1000, Timestamp.max.value/1000)
+        self.assertEqual(Timestamp(Timestamp.min.to_pydatetime()).value/1000, Timestamp.min.value/1000)
+
 if __name__ == '__main__':
     import nose
     nose.runmodule(argv=[__file__, '-vvs', '-x', '--pdb', '--pdb-failure'],

pandas/tslib.pyx

@@ -388,6 +388,15 @@ cpdef object get_value_box(ndarray arr, object loc):
         return util.get_value_1d(arr, i)
 
 
+# Add the min and max fields at the class level
+# These are defined as magic numbers due to strange
+# wraparound behavior when using the true int64 lower boundary
+cdef int64_t _NS_LOWER_BOUND = -9223285636854775000LL
+cdef int64_t _NS_UPPER_BOUND = 9223372036854775807LL
+Timestamp.min = Timestamp(_NS_LOWER_BOUND)
+Timestamp.max = Timestamp(_NS_UPPER_BOUND)
+
+
 #----------------------------------------------------------------------
 # Frequency inference
 
@@ -769,8 +778,6 @@ cdef inline object _get_zone(object tz):
         except AttributeError:
             return tz
 
-# cdef int64_t _NS_LOWER_BOUND = -9223285636854775809LL
-# cdef int64_t _NS_UPPER_BOUND = -9223372036854775807LL
 
 cdef inline _check_dts_bounds(int64_t value, pandas_datetimestruct *dts):
     cdef pandas_datetimestruct dts2
@@ -2868,4 +2875,4 @@ def _calc_julian_from_U_or_W(year, week_of_year, day_of_week, week_starts_Mon):
         return 1 + days_to_week + day_of_week
 
 # def _strptime_time(data_string, format="%a %b %d %H:%M:%S %Y"):
-#     return _strptime(data_string, format)[0]
+#     return _strptime(data_string, format)[0]