extract datetime obj value from pandas Series (single row)

Question

I have same issue as describe here link but this time with a datetime object.

Using .values converts the datetime object to something like 2011-02-28T19:00:00.000000000-0500 .

Prior to the conversion the datetime was 2011-03-01

What is the proper way to do what I want to do?

Answer 1

由于高精度的datetime64的[NS]值，如果你只是对日期感兴趣的话可以calll dt.date之前调用.values ：

p0_cost = (cost_df['price1'][cost_df['date']==p0] - cost_df['price2'][cost_df['date']==p0]).dt.date.values[0]