@@ -126,6 +126,49 @@ class DatetimeProperties(Properties):
126126    """ 
127127
128128    def  to_pydatetime (self ):
129+         """ 
130+         Return the data as an array of native Python datetime objects 
131+ 
132+         Timezone information is retained if present. 
133+ 
134+         .. warning:: 
135+ 
136+            Python's datetime uses microsecond resolution, which is lower than 
137+            pandas (nanosecond). The values are truncated. 
138+ 
139+         Returns 
140+         ------- 
141+         numpy.ndarray 
142+             object dtype array containing native Python datetime objects. 
143+ 
144+         See Also 
145+         -------- 
146+         datetime.datetime : Standard library value for a datetime. 
147+ 
148+         Examples 
149+         -------- 
150+         >>> s = pd.Series(pd.date_range('20180310', periods=2)) 
151+         >>> s 
152+         0   2018-03-10 
153+         1   2018-03-11 
154+         dtype: datetime64[ns] 
155+ 
156+         >>> s.dt.to_pydatetime() 
157+         array([datetime.datetime(2018, 3, 10, 0, 0), 
158+                datetime.datetime(2018, 3, 11, 0, 0)], dtype=object) 
159+ 
160+         pandas' nanosecond precision is truncated to microseconds. 
161+ 
162+         >>> s = pd.Series(pd.date_range('20180310', periods=2, freq='ns')) 
163+         >>> s 
164+         0   2018-03-10 00:00:00.000000000 
165+         1   2018-03-10 00:00:00.000000001 
166+         dtype: datetime64[ns] 
167+ 
168+         >>> s.dt.to_pydatetime() 
169+         array([datetime.datetime(2018, 3, 10, 0, 0), 
170+                datetime.datetime(2018, 3, 10, 0, 0)], dtype=object) 
171+         """ 
129172        return  self ._get_values ().to_pydatetime ()
130173
131174    @property  
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