Reputation: 25
Does anyone know of way to circumvent the Spotfire limitation for using the OVER function to RANK or order dates when using a custom expression?
Providing a little background, I am trying to identify or mark a lease based on the below data as 1, 2, 3 etc. For example, since we see twice 63 in the left column, I would like to return a 1 and a 2 to identify the two different leases, starting on 1/1/2016 and 8/1/2016. Then a 1 and 2 for 72, a 1 for 140 and so one. Unfortunately, OVER functions can only be used with aggregation methods and I don't know of another method to produce the result that I am looking for.
Tenant Lease_From Lease_To Tenant_status
63 1/1/2016 1/31/2017 Current
63 8/1/2017 7/31/2018 Current
72 10/1/2016 7/31/2017 Current
72 8/1/2017 7/31/2018 Current
140 2/1/2017 7/31/2018 Current
149 8/1/2016 7/31/2017 Current
149 8/1/2017 7/31/2018 Current
156 1/15/2017 3/31/2018 Current
156 4/1/2018 3/31/2019 Current
Upvotes: 2
Views: 1717
Reputation: 3974
please consider @blakeoft's answer as the correct one!
that said, as an FYI, First()
is considered an aggregation method, and OVER
statements can be included inside of an If()
! so you can accomplish the same thing with an expression like:
If([Lease_From] = First([Lease_From]) OVER ([Tenant]), 1, 2)
when you combine If()
and OVER
in this way, you can get some really cool and powerful visualizations, BUT you do lose the ability to mark data effectively. this is because the expression is evaluated from the context of the If()
rather than the OVER
; in other words, all rows are considered instead of only the ones selected.
you can get around this with some black magic (AKA data functions) but it's a bit contrived.
again, in this situation, Rank()
is absolutely the correct solution.
Upvotes: 1
Reputation: 2400
Use this:
Rank([Lease_From], [Tenant])
Gives this as the result:
Tenant Lease_From Lease_To Tenant_status Rank([Lease_From], [Tenant])
63 1/1/2016 1/31/2017 Current 1
63 8/1/2017 7/31/2018 Current 2
72 10/1/2016 7/31/2017 Current 1
72 8/1/2017 7/31/2018 Current 2
140 2/1/2017 7/31/2018 Current 1
149 8/1/2016 7/31/2017 Current 1
149 8/1/2017 7/31/2018 Current 2
156 1/15/2017 3/31/2018 Current 1
156 4/1/2018 3/31/2019 Current 2
Upvotes: 3