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Anonymous
Not applicable

Multiple IF Calculation

Hello,

 

I have two datasets as follows:

 

Dataset 1

IDErect HoursDismantle Hours
11020
2510

 

Dataset 2 

IDJob Type% CompleteBurned
1Erect100%12
2Erect100%5
2Dismantle100%10
2Day Work Mod 5
2Star Rate Mod100%4.5

 

Relationship has been created between ID in both datasets. 

 

I need to create a DAX measure as follows:

 

If job type is 'Erect' then (% complete * erect hours) 
If job type is 'Dismantle' then (% complete * dismantle hours) 

If job type is 'Star Rate Mod' then (% complete * 4.5)

If job type is 'Day Work Mod' then (sum burned)

 

Is the above logic possible in one DAX statement?

1 ACCEPTED SOLUTION
amitchandak
Super User
Super User

@Anonymous , A new column in dataset2

 

new column =

var _1 = sumx(filter(dataset1, dataset1[ID] = dataset2[ID]) ,[Erect Hours])

var _2 = sumx(filter(dataset1, dataset1[ID] = dataset2[ID]) ,[Dismantle Hours])

return

Switch([Job Type],

"Erect", [% complete]*_1,

"Dismantle", [% complete]*_2,

"Star Rate Mod", [% complete]*.45,

"Dismantle", [Burned]

)

 

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View solution in original post

2 REPLIES 2
amitchandak
Super User
Super User

@Anonymous , A new column in dataset2

 

new column =

var _1 = sumx(filter(dataset1, dataset1[ID] = dataset2[ID]) ,[Erect Hours])

var _2 = sumx(filter(dataset1, dataset1[ID] = dataset2[ID]) ,[Dismantle Hours])

return

Switch([Job Type],

"Erect", [% complete]*_1,

"Dismantle", [% complete]*_2,

"Star Rate Mod", [% complete]*.45,

"Dismantle", [Burned]

)

 

Share with Power BI Enthusiasts: Full Power BI Video (20 Hours) YouTube
Microsoft Fabric Series 60+ Videos YouTube
Microsoft Fabric Hindi End to End YouTube
Anonymous
Not applicable

Thanks for answering my questions.

 

Is there anyway I can use the below formular but reference columns from another table in the highlighted section of your code?

 

new column =

var _1 = sumx(filter(dataset1, dataset1[ID] = dataset2[ID]) ,[Erect Hours])

var _2 = sumx(filter(dataset1, dataset1[ID] = dataset2[ID]) ,[Dismantle Hours])


These highlighted columns come from another table that is connect via a many to many relationship. 

 

Many thanks,

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