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Aggregate operator applied to each subset

SylvainMSylvainM Member Posts: 18  Maven
edited August 2020 in Help
Hello everyone,

I apologize if this question has already been asked elsewhere, or if it is an obvious one. I'm still learning how to use Rapidminer :smile:

This is my problem. Let's suppose that I have a dataset looking like that (but much more different values):

Year Region Item
01      QC      CCD
01      QC      CCD
01      QC      CS

01      ON      CCD
01      ON      CS

01      NB      CCD
01      NB      CS
--------------------------
02      QC      CCD
02      QC      CS
02      QC      CS

02      ON      CS
02      ON      CS

02      NB      CCD
02      NB      CCD

I would like to get the relative percentage of each Item related to the Region and to the Year

Year Region Item   Proportion
01      QC      CCD   66.6%
01      QC      CS      33.3%

01      ON      CCD   50%
01      ON      CS      50%

01      NB      CCD    50%
01      NB      CCS    50%
-------------------------------------
02      QC      CCD    33.3%
02      QC      CS       66.6%

02      ON      CS       100%

02      NB      CCD     100%

I tried many combinations with the operators Aggregate, Loop values, Branch, etc. but I seem to constantly fail... 

Do you have any suggestion?

Thanks a lot!
Sylvain
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Best Answer

Answers

  • BalazsBaranyBalazsBarany Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert Posts: 709   Unicorn
    Hi,

    what you're trying to achieve is called "window functions" in SQL. 

    You should check out this project, it's an implementation of window functions in RapidMiner.
    https://github.com/bbarany/rapidminer-windowfunctions

    You can calculate groupwise sums or counts, generate the ratios, and then aggregate according to your needs. 

    Regards,

    Balazs
  • SylvainMSylvainM Member Posts: 18  Maven
    Thanks BalazsBarany  and SGolbert for your help,

    Your solution, Sebastian, is perfect! Thank you so much! :smiley:

    Best regards to both of you,
    Sylvain


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