Is there an equivalent for the SAS "intnx" command in python?

Question

I am a beginner in python and stuck on translating a piece of code from SAS to Python (see below). How would I recreate the "intnx"-command in line 10 in Python, which introduces a 3-month-lag to the actual date (datadate) in order to create the variable "HouDate".

data data._1_compustat_prep (keep = gvkey tic datadate fyear HouDate HouYear ib at dvc act che 
lct dlc txp dp ibc oancf);
retain gvkey tic datadate fyear HouDate HouYear;
set data._0_compustat_students;

  if indfmt   = 'INDL' and datafmt = 'STD';

  format HouDate DDMMYY10.;
  format DataDate DDMMYY10.;
  HouDate = intnx("month", datadate, +3, "E");
  if month(HouDate) >= 7 then HouYear = year(HouDate) + 1; else HouYear = year(HouDate);

  if mdy(07,01,1963) <= HouDate <= mdy(06,30,2009);
  if exchg in (11,12,14,15,17);
  if 6000 <= sich <= 6999 then delete;

run;

Asked By: ChurrrT

||

Source

Answer 1

You can use the datetime and [dateutil] libraries to help you with this. In particular the datetime.datetime and ~~datetime.timedelta~~ dateutil.realtivedelta.relativedelta classes.
The dateutil.relativedelta.relativedelta class is better than the datetime.timedelta here, because the latter won’t allow you to specify a delta with units bigger than days, when the former does.

Additionally, I’ve added type hints in the code, to make it easier to understand. I corresponds to the syntax xx:yy where xx is the variable name, and yy its type.

from datetime import datetime
from dateutil.relativedelta import relativedelta

lag:relativedelta = relativedelta(months=3)
datadate:datetime = datetime(year=2022, month=8, day=25, hour=11, minute=37, second=8)
HouDate:datetime = datadate + lag

HouYear:int = HouDate.year
if HouDate.month >= 7:
    HouYear += 1

print("{} || {}".format(HouYear, HouDate))

2023 || 2022-11-25 11:37:08

As the author mentioned in one of their comment:

how would you do the commands above for whole columns in a dataframe?

Here is the way I’d do it when using a pandas.DataFrame:

from datetime import datetime
from dateutil.relativedelta import relativedelta
import pandas as pd

lag:relativedelta = relativedelta(months=3)

df:pd.DataFrame = pd.DataFrame({
    "datadate": [
        datetime(year=2022, month=1, day=1, hour=1, minute=1, second=1),
        datetime(year=2022, month=6, day=2, hour=2, minute=2, second=2),
        datetime(year=2022, month=10, day=3, hour=3, minute=3, second=3)
    ]
})

df["HouDate"] = df.datadate.apply(lambda x: x+lag)
df["HouYear"] = df.HouDate.apply(lambda x: x.year if x.month < 7 else x.year+1)

print(df)

Pre-treatment dataframe:

	datadate
0	2022-01-01 01:01:01
1	2022-06-02 02:02:02
2	2022-10-03 03:03:03

Post-treatment dataframe:

	datadate	HouDate	HouYear
0	2022-01-01 01:01:01	2022-04-01 01:01:01	2022
1	2022-06-02 02:02:02	2022-09-02 02:02:02	2023
2	2022-10-03 03:03:03	2023-01-03 03:03:03	2023

Answered By: GregoirePelegrin

Is there an equivalent for the SAS "intnx" command in python?

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