Combine rows in pandas dataframe by several conditions

Question

I have the following data frame:

ID_number  Name      Date      S_code    S_description 
1          Dani     01/2017      G1       PROCEDURE ON SINGLE VESSEL
1          Dani     01/2017      R56      INSERTION OF THREE VASCULAR STENTS
1          Dani     06/2017      L34      CHOLECYSTECTOMY
2          Alice    03/2015      L12      OTHER CYSTOSCOPY
3          Elle     04/2015      L34      CHOLECYSTECTOMY
3          Elle     04/2015      H6       EXCISION OR DESTRUCTION OF PERITONEAL TISSUE

I want to combine rows if the columns "ID_Number", "Name" and "Date" are identical, and the columns "S_code" and "S_description" will be concatenated so that the Data will look like this:

    ID_number   Name   Date     S_code     S_description 
        1       Dani   01/2017  G1,R56     PROCEDURE ON SINGLE VESSEL,INSERTION OF THREE VASCULAR STENTS
        1       Dani   06/2017    L34      CHOLECYSTECTOMY
        2       Alice  03/2015    L12      OTHER CYSTOSCOPY
        3       Elle   04/2015  L34,H6     CHOLECYSTECTOMY,EXCISION OR DESTRUCTION OF PERITONEAL TISSUE

The "ID_Number" column is sorted.

I'm new with Python and I will appreciate any help with this issue!

sammywemmy · Accepted Answer · 2020-03-08 12:26:37Z

1

Use pandas groupby on the three columns, and pass pandas string cat as a function through the agg method :

 df.groupby(['ID_number','Name','Date']).agg(lambda x: x.str.cat(sep=','))

                            S_code  S_description
ID_number   Name    Date        
1           Dani    01/2017 G1,R56  PROCEDURE ON SINGLE VESSEL,INSERTION OF THREE ...
                    06/2017 L34     CHOLECYSTECTOMY
2           Alice   03/2015 L12     OTHER CYSTOSCOPY
3           Elle    04/2015 L34,H6  CHOLECYSTECTOMY,EXCISION OR DESTRUCTION OF PER...

answered Mar 8, 2020 at 12:26

sammywemmy

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