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## Calculate value by matching only one of many multiple comma-seperated values

Hey all,

I have a large dataset with an ID and corresponding value, and want to SUM() those together using CALCULATE() and FILTER() to add them up together based on which item has what ID (or IDs). Each item might have one or more IDs which need to be matched in the data table.

Data

 ID Total X-0233 30 X-0233 50 X-9660 80 X-9660 77 X-9660 63 X-9955 185 X-7755 80 X-7755 96

Items

 IDs Totals (what I need to calculate!) X-0233 80 X-0233, X-9660 300 X-7755, X-0233, X-9660 380

I've tried with the following DAX, but it will only return an item total if there is only one ID, not multiple IDs separated by a comma.

``````totals = CALCULATE(
SUM(data[id]),
FILTER(
VALUES(data),
CONTAINSSTRING(data[id], items[ids])
)
)``````

Previsouly I've used a measure and a relationship to complete this when there was only one ID to match with another ID - that was much easier!

Any suggestions or ideas would be incredible as I'm completely stuck on this one! Thanks all.

1 ACCEPTED SOLUTION
Community Support

Hi @djworsdell ,

Please refer to my pbix file to see if it helps you.

Create a measure.

``````Measure =
SUMX (
CALCULATETABLE (
'Date',
CONTAINSSTRING ( SELECTEDVALUE ( Items[Ds] ), 'Date'[ID] )
),
[Total]
)
``````

Best Regards

Community Support Team _ Polly

If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

2 REPLIES 2
Community Support

Hi @djworsdell ,

Please refer to my pbix file to see if it helps you.

Create a measure.

``````Measure =
SUMX (
CALCULATETABLE (
'Date',
CONTAINSSTRING ( SELECTEDVALUE ( Items[Ds] ), 'Date'[ID] )
),
[Total]
)
``````

Best Regards

Community Support Team _ Polly

If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

Super User

You may try

``````totals =
VAR CurrentItemsID = Itms[ID's]
RETURN
SUMX (
FILTER ( Data, CONTAINSSTRING ( data[id], CurrentItemsID ) ),
Data[Total]
)``````

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