replacing pandas drop duplicates functionality

[wonka1234]

Hi,

Is there a way to replicate pandas drop duplicates on all columns?

Is this the same as using Unique on all columns?

Thanks.

[SoccerTil]

From what I can see about Pandas drop duplicates, Alteryx Unique will perform the same as the drop duplicates with the First option. The drop duplicates by default will be based on all columns. You can select them all or if you only require a subset of columns then select just those. To replicate the Last option you would need to number your rows and then sort them descending first. To replicate the False option, you will need to use additional data analytics. If this doesn't help, you can supply a test input and output data set with your drop duplicates statement.

[atcodedog05 · Accepted solution]

Hi @wonka1234 

Pandas function

DataFrame.drop_duplicates(subset=None, keep='first', inplace=False, ignore_index=False)

Another approach is you can also use a sample tool to get the first 1 row for each group or the last 1 row for each group. This way you can keep 1st occurrence or last occurrence.

inplace=False is similar as taking data from the previous step (original copy) and after drop (new copy)

ignore_index=False and indexes are not used in Alteryx

Hope this helps : )

[mutama]

Hi @wonka1234 , in addition to the suggestions provided by @atcodedog05 and @SoccerTil, you may also refer to the Alteryx Tool Mastery Guide here regarding the detailed, step-by-step explanation on how to use each tool (e.g. Unique, Sample etc): https://community.alteryx.com/t5/Alteryx-Designer-Knowledge-Base/Tool-Mastery-Index/ta-p/84593

[atcodedog05]

Happy to help : ) @wonka1234 

Cheers and have a nice day!