Merging Two Dataframes In Pandas Based On Time-range Difference

I have these two dataframes, df1,df2. df1: dateTime userId session 2018-08-30 02:20:19 2233 1 2018-08-30 05:32:10 1933 1 2018-08-30 09:10:39

Solution 1:

IIUC: Use pandas.merge_asof

pd.merge_asof(df1,df2,left_on='dateTime',right_on='clickTime',by='userId',direction='nearest')dateTimeuserIdsessionclickTimeclickId02018-08-30 02:20:19    2233        12018-08-30 02:21:09     198712018-08-30 05:32:10    1933        12018-08-30 05:33:10     200922018-08-30 09:10:39    2233        22018-08-30 02:32:09     199032018-08-30 10:26:59    2233        32018-08-30 02:32:09     199042018-08-30 11:56:25    4459        12018-08-30 11:57:25     301252018-08-30 12:30:55    4459        12018-08-30 11:58:55     3013

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You can specify a tolerance on how far away to look

pd.merge_asof(df1,df2,left_on='dateTime',right_on='clickTime',by='userId',direction='nearest',tolerance=pd.Timedelta(15,unit='m'))dateTimeuserIdsessionclickTimeclickId02018-08-30 02:20:19    2233        12018-08-30 02:21:09   1987.012018-08-30 05:32:10    1933        12018-08-30 05:33:10   2009.022018-08-30 09:10:39    2233        2NaTNaN32018-08-30 10:26:59    2233        3NaTNaN42018-08-30 11:56:25    4459        12018-08-30 11:57:25   3012.052018-08-30 12:30:55    4459        1NaTNaN