convert numeric sas date to datetime in Pandas

Question

I am using Pandas 0.18 and read_sas to load a sas7bdat dataset.

The dates in the Pandas dataframe appear as:

Out[56]: 
0    19411.0
1    19325.0
2    19325.0
3    19443.0
4    19778.0
Name: sas_date, dtype: float64

pd.to_datetime does not recognize this format. What should I do parse the date correctly?

Thanks!

Answer 1

According to this link,

[A] SAS date value is a value that represents the number of days between January 1, 1960, and a specified date

Therefore, if we convert the numbers to Pandas Timedeltas and add them to 1960-1-1 we can recover the date:

import numpy as np
import pandas as pd

ser = pd.Series([19411.0, 19325.0, 19325.0, 19443.0, 19778.0])
ser = pd.to_timedelta(ser, unit='D') + pd.Timestamp('1960-1-1')

yields

0   2013-02-22
1   2012-11-28
2   2012-11-28
3   2013-03-26
4   2014-02-24
dtype: datetime64[ns]