Analytics question to define status that depends on date

Question

      Date                status      output
7/8/2021  12:00:00 AM     latest    
8/11/2021  12:00:00 AM    latest 
2/11/2022  12:00:00 AM    latest
2/1/2022  12:00:00 AM     old

      Date                status      output
7/8/2021  12:00:00 AM     latest    not use
8/11/2021  12:00:00 AM    latest    not use
2/11/2022  12:00:00 AM    latest    use
2/1/2022  12:00:00 AM     old       not use

Compare the date in the Date column with the today's date, if it is less than equal to 6 months old and its status is latest, then the output should be use, otherwise not use.

Answer 1

Let's first build our data :

import pandas as pd
from io import StringIO

csvfile = StringIO(
"""Date\tstatus\toutput
7/8/2021 12:00:00 AM\tlatest
8/11/2021 12:00:00 AM\tlatest
2/11/2022 12:00:00 AM\tlatest
2/1/2022 12:00:00 AM\told""")
df = pd.read_csv(csvfile, sep = '\t', engine='python')

Ensure Date column contains date formatting

df.Date = pd.to_datetime(df.Date, format = "%m/%d/%Y %H:%M:%S %p")

df
Out[344]: 
                 Date  status  output
0 2021-07-08 12:00:00  latest     NaN
1 2021-08-11 12:00:00  latest     NaN
2 2022-02-11 12:00:00  latest     NaN
3 2022-02-01 12:00:00     old     NaN

Then apply the logic you said, True if latest and if Date + 6 months is greater than today (which is the same as said it's less than 6 months old) :

mask_date = (df.Date + pd.DateOffset(months=6) > pd.to_datetime("today")) & (df.status == 'latest')

mask_date
Out[347]: 
0    False
1    False
2     True
3    False
dtype: bool

Finally just map your mask :

df.loc[:, "output"] = mask_date.map(lambda x : "use" if x else "not used")

df
Out[350]: 
                 Date  status    output
0 2021-07-08 12:00:00  latest  not used
1 2021-08-11 12:00:00  latest  not used
2 2022-02-11 12:00:00  latest       use
3 2022-02-01 12:00:00     old  not used