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DAX – More Fun With IF(VALUES())

“I mean, IF() I’m paying top dollar, I want a little production VALUE()”

I bet you thought I was out of movie quotes for IF(VALUES()) didn’t you!  If I had a fake ID, my name would be “McPivot.”

Bag of Tricks

OK, once you have a reasonable level of comfort with the workings of IF(VALUES()), whether that comfort is “I understand it” or even just “I can make it give me the right results,” you are in for some treats.  There are a number of ways to use IF(VALUES()) to produce different desired effects.  I’m going to blast through a few of them here real quick.

Note:  If you have not read the previous post, you should do so before reading this one.

Returning BLANK() for Subtotals and Grand Totals

Sometimes you end up with a measure that simply doesn’t make sense unless you are in the context of a single item.  Returning to the football project, let’s say I write a measure that for “Personal Best Single Game Rushing Yards,” which, for a given football player, returns their personal best single-game total over all time:

Cool huh?  (My data ends before Adrian Peterson broke Jamal Lewis’ record).  By the way, the formula for that measure is:

   =MAXX(ALL(DimProschedule[GameDate]),[Rushing Yards])

(To understand how that measure works, I refer you to one of my personal favorite posts, the Five-Point-Palm, Exploding Function Technique.)

Now, if you put another field on the pivot, you have a decision to make:  do you want that measure to be evaluated at levels other than a single player?  How about for an entire team?  Or all players of a given position?  You may decide that doesn’t make sense, and prefer that the measure NEVER return a value in those cases.

Good thing we have IF(VALUES()).  We can create another measure based on the existing measure:

   =IF(COUNTROWS(VALUES( CleanPlayers[PlayerID] ))=1,
       [Best Single Gm Rush Yds], BLANK())

Notice how the original measure does not reflect the best player total?  In the week that Lewis ran for 295, apparently the Ravens had other players run for a total of 39 additional yards.  Depending on the semantics desired, you could argue that the Ravens’ number should be 295, for best single player performance in a game.

Or you can just return blank and forget about it, as my second measure does.

Returning different measures for different cases (aka “Branching”)

If we look at the picture above, you may say “hey it’s not fair to compare QB’s against RB’s in rushing yards, shouldn’t each position be measured by its primary metric – pass yards for QB, rush yards for RB, and receiving yards for WR’s and TE’s?”

Yeah, let’s do that.  First let’s create similar “best game ever” measures for the other two kinds of yardage – passing (throwing) and receiving (catching).  (Rushing is running, btw).

OK, cool, so we have all three measures, but it results in a scraggly pivot.  I want a single column of numbers, and for the number to reflect the position (primary role) of the particular player.

IF(VALUES()) to the rescue.  A new measure that “branches” into the right measure for each position:

   =IF(COUNTROWS(VALUES( CleanPlayers[PlayerID] ))=1,
      IF(VALUES(CleanPlayers[PositionCode])=”QB”, [Best Single Game Pass Yards],
      IF(VALUES(CleanPlayers[PositionCode])=”RB”, [Best Single Game Rush Yards],
      IF(VALUES(CleanPlayers[PositionCode])=”WR”, [Best Single Game Rec Yards],
      IF(VALUES(CleanPlayers[PositionCode])=”TE”, [Best Single Game Rec Yards],

Cool, huh?  A few things to note:

  1. IF(VALUES()) is used to check the value of [PositionCode], but [PositionCode] isn’t even on the pivot!  This works because each PlayerID does correspond, in the CleanPlayers table, to a single position code, because each PlayerID is unique.
  2. That said, it IS hard to tell which player is which position, especially for the 49ers, who had awful teams during the years for which I have data.  So I’ll add Position to the pivot below.
  3. I’m pretty sure that Johnnie Morton had his 153 yard receiving day when he played for the Lions, not the 49ers, but solving that problem is best saved for another day.

Here’s the pivot with position added in for clarity:

(I decided to screenshot the Bears section rather than 49ers because the Bears had better players in those years.)

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