convert a SAS datetime in Pandas

Question

I am using Pandas to read a Sas dataset using read_sas

There is a datetime variable in the SAS dataset, which appears in Pandas as:

1.775376e+09

Once I convert it to str the date is:

1775376002.0

The corresponding date in SAS (not in my Pandas dataset) appears to be a DATETIME21.2

04APR2016:08:00:02.00

I tried to convert it using

pd.to_datetime(df.mysasdate,format='%d%m%Y%H%M%S') with no success

TypeError: 'float' object is unsliceable

Any ideas? Thanks!

Answer 1

SAS date value

is a value that represents the number of days between January 1, 1960, and a specified date. link

So you can convert number to_timedelta and add date 1960-01-01 00:00:00

df = pd.DataFrame({'mysasdate':[1775376002.0, 1775377002.0]})
print (df)
      mysasdate
0  1.775376e+09
1  1.775377e+09

print (pd.to_timedelta(df['mysasdate'], unit='s') + pd.datetime(1960, 1, 1)) 
0   2016-04-04 08:00:02
1   2016-04-04 08:16:42
Name: mysasdate, dtype: datetime64[ns]

Answer 2

You will get the right date in Python by using format='sas7bdat' option in your read_sas() method. For example, I used: pd.read_sas(dataset, format='sas7bdat'), and the dates got translated correctly to python dataframe.