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You should be able to do this using table calculations as you suggested. It depends how the view is set up and how they are being computed. However, using a combination of index and window_sum will allow you to get the desired results.
A calculation similar to the following may help:
if index()=1 and window_count(max([Order Date]))=1 then 'March'
elseif index()=2 and window_count(max([Order Date]))=1 then 'December'
elseif window_count(max([Order Date]))>=2 then 'Both'
Hope it does!
Hi, Tracy. That's very helpful. I'm _almost_ there, but not quite. I'm still getting comfortable with the partitioning concepts in Tableau.
Attached is a spreadsheet of mock up data. The Result column is what I'm trying to generate via the calculation. Essentially, I want to know if a given ticket is still open, if it was closed between the two periods, or whether the ticket is a new one when using any two dates as dimensions. My goal is to get the "Result" field which I can then count/aggregate for the entire dataset, or for arbitrary levels of detail ("hostname" in this sample data). I'd like to not have to include the prior period at all in the visualization, but I think that may be asking a bit much.
Window_Sample.xlsx 8.6 KB