Forum Discussion
Structuring data that doesn't use dates
Create date like
//New Column
date = date(table[season],1,1). Create a Calendar time intelligence function and use that for time related comparision.
Also, create dimension for round and player.
// New table
player dim = distinct(table[player])
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Hi amitchandak I did consider using the season and rounds to create pseudo dates to work with, the problem is finding a consistency in periods. Say if I wanted to do a weighted average of the last x games which would look something like (Score * weighting) + (Score previous period * weighting-1) + (Score previous period * weighting-2) and so on. Previously I have done this just using edate month-1 type stuff, this works within a season since I could just use day increments but it doesn't help across seasons since I'd be jumping a year.
I have come up with a solution using 2 calculated columns - the first is a simple concatenation of season and round so it's like 201701, 201702 .... 202001. Then a Rankx column so that as new seasons and rounds get added the most recent will always be rank 1. Then I can do calculations using the rank column as the filter, which I think is the neatest and easiest?
Concatenate = if('2016-2019'[Round]<10,CONCATENATE('2016-2019'[Season]&"0",'2016-2019'[Round]),CONCATENATE('2016-2019'[Season],'2016-2019'[Round]))Rank = RANKX('2016-2019','2016-2019'[Concatenate],,DESC,Dense)Interested to hear if someone has a better suggestion.
