DatetimeIndex.normalize now accounts for nanoseconds (#5461).

datetime64(ns) uses the dts->ps which was not being set to zero in the
normalize function.

Author: rockg

pandas/tseries/tests/test_timeseries.py

@@ -1420,6 +1420,11 @@ def test_normalize(self):
         result = rng.normalize()
         expected = date_range('1/1/2000', periods=10, freq='D')
         self.assert_(result.equals(expected))
+        
+        rng_ns = pd.DatetimeIndex(np.array([1380585623454345752, 1380585612343234312]).astype("datetime64[ns]"))
+        rng_ns_normalized = rng_ns.normalize()
+        expected = pd.DatetimeIndex(np.array([1380585600000000000, 1380585600000000000]).astype("datetime64[ns]"))
+        self.assert_(rng_ns_normalized.equals(expected))
 
         self.assert_(result.is_normalized)
         self.assert_(not rng.is_normalized)

pandas/tslib.pyx

@@ -2180,6 +2180,7 @@ cdef inline int64_t _normalized_stamp(pandas_datetimestruct *dts):
     dts.min = 0
     dts.sec = 0
     dts.us = 0
+    dts.ps = 0
     return pandas_datetimestruct_to_datetime(PANDAS_FR_ns, dts)