DISTINCTCOUNT values difference between AXIS visual and card visual

[Anonymous]

Hello, guys!

I need some help over here, if you could so, I appreciate.

I'm using a DISTINCTCOUNT to get the distinct values from column A applying this measure to a Card, but when I apply to a Clustered Column Chart, this doesn't working fully.

If you sum the values from the Column Chart the total will be different.

Like this (the number format from the visuals is from Brazil, so dot is comma and comma is dot):

MyMeasure = DISTINCTCOUNT(Table1[ColumnA])

Let's add up the values from column chart:

4520+488+108+99+23+1 =5239

How can you see, the total values is different between Card and Column Chart distributed by AXIS labels.

The question is: how could I use the same total from Card applied to the Column Chart?

Bellow samples of my dataset and PBIX to make it more easy to understand.

Dataset

https://drive.google.com/open?id=1Mhg0QPpPxTPxmo_q2OYYwLn4xbiV47J1

PBIX

https://drive.google.com/open?id=1IPeK7j5uDWIU2517T8D_7l6Lh5nmCtmh

Best

Willian Victor

[camargos88]

Hi @Anonymous ,

Have you noticed you have Ordens with more than 1 situation ?

On your clustered chart, it shows 12 duplicated values.

Ricardo

[Anonymous]

Hi, @camargos88

Yep. I know that.

The point is to do the total of column chart be equal the card.

I was trying to do a distinct one that ignore this "situation" thing and only count all distinct orders independent where it is (where is the context).

I don't even know if this will work fully.. but I wanna give a try before use a new dataset without these double orders.

(The original dataset came from my company and run by invoice (first-level criterial) and not by orders, so if I've to change it.. it'll take a while. And I don't wanna it).

Anyway, thanks for your help!

[camargos88 · Accepted solution]

@Anonymous ,

Perhaps if you get the first or last value per order, would it work ?

Check this file: Download PBIX 

Ricardo

[Anonymous]

That's it! The "_First" worked perfectly!

Thanks for your help, @camargos88 !

Willian Victor