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kdewald's avatar
kdewald
New Member
7 years ago

Dynamic groupby calculation

Hi everybody,   I am working on a dataset with the following columns, used to log visits to a website: person_id visit_id visit_datetime What I am looking for is to visuallize how many people...
PattemManohar's avatar
PattemManohar
Community Champion
7 years ago

kdewald Please post some sample data to replicate and test/resolve your scenario....

  • kdewald's avatar
    kdewald
    New Member
    7 years ago

    Sure, here is an example:

     

    person_id,visit_id,visit_datetime
A,0,2018-05-04
A,1,2018-05-19
A,2,2018-06-01
A,3,2018-06-18
A,4,2018-07-01
A,5,2018-07-20
A,6,2018-08-02
A,7,2018-08-09
A,8,2018-08-27
A,9,2018-09-14
B,0,2018-05-05
B,1,2018-05-19
B,2,2018-06-06
B,3,2018-06-24
B,4,2018-07-02
C,0,2018-07-21
C,1,2018-08-06
C,2,2018-08-23
C,3,2018-09-17
C,4,2018-10-05
D,0,2018-05-06
D,1,2018-05-23
D,2,2018-06-13
D,3,2018-07-09
D,4,2018-07-25
E,0,2018-07-22
E,1,2018-08-14
E,2,2018-09-10
E,3,2018-10-05
E,4,2018-11-01
    • PattemManohar's avatar
      PattemManohar
      Community Champion
      7 years ago

      kdewald Thanks for posting sample data.

       

      I've tried below to solve your scenario...

       

      Created a table with single column from the visit_id values (distinct values) as below

       

      VisitsFilter = DISTINCT(VisitCount[visit_id])

      Create a relationship between main source table (In my case it is VisitCount) with the VisitsFilter that was created above with visit_id field.

       

      use visit_id from VisitsFilter as slicer and use source table data for visualizing the data.

       

       

      Hope this is what you are looking for...