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Anonymous
Not applicable

Need Help on create the Measure

I am trying to create the Measure where the below table formation . Please help me how to create the Measure where it should count the recent transaction date based on ID as higher rank. Each Rank I want to calculate the total net amount , Paid Amount , Rejected Amount.  I attempted countrows with filter option & RankX but it showing error .

 

 

Transaction DateIDService CodeNet AmountPaid AmountRejected AmountManual mapping
7/7/2024CLA0001572502501001501st Received transaction
8/8/2024CLA00015725015015002nd Recived Transaction
6/6/2024CLA00058830520020001st Received transaction
6/6/2024CLA00059921328502851st Received transaction
6/6/2024CLA00057104611001101st Received transaction
7/7/2024CLA00059921328528502nd time received
7/7/2024CLA00057104611001102nd time received
8/7/2024CLA00057104611011003rd time Received
1 ACCEPTED SOLUTION
Anonymous
Not applicable

Hello,rajendraongole1 ,thanks for your concern about this issue.

Your answer is excellent! And I would like to share some additional solutions below.
Hi,@Anonymous .I am glad to help you.
If the calculated columns don't fit your needs, here is what I calculated by creating a measure, which enables dynamic transformations based on the data in the visual.
In fact I only modified the code rajendraongole1  provided by using RANK().
measure:

 

M_Rank = 
VAR _rank=
RANK(DENSE,FILTER(ALL(Rknk),'Rknk'[ID]=MAX('Rknk'[ID])),ORDERBY('Rknk'[Transaction Date],DESC),DEFAULT)
RETURN _rank

 

 

vjtianmsft_0-1723436234297.png

I hope my suggestions give you good ideas, if you have any more questions, please clarify in a follow-up reply.
Best Regards,
Carson Jian

 

View solution in original post

4 REPLIES 4
Anonymous
Not applicable

Hello,rajendraongole1 ,thanks for your concern about this issue.

Your answer is excellent! And I would like to share some additional solutions below.
Hi,@Anonymous .I am glad to help you.
If the calculated columns don't fit your needs, here is what I calculated by creating a measure, which enables dynamic transformations based on the data in the visual.
In fact I only modified the code rajendraongole1  provided by using RANK().
measure:

 

M_Rank = 
VAR _rank=
RANK(DENSE,FILTER(ALL(Rknk),'Rknk'[ID]=MAX('Rknk'[ID])),ORDERBY('Rknk'[Transaction Date],DESC),DEFAULT)
RETURN _rank

 

 

vjtianmsft_0-1723436234297.png

I hope my suggestions give you good ideas, if you have any more questions, please clarify in a follow-up reply.
Best Regards,
Carson Jian

 

Anonymous
Not applicable

Acutally as per @rajendraongole1 I have done the calculated column and the measure as well added . it was worked well. @Anonymous Thanks for your update regarding the measure. It's working well also. 

rajendraongole1
Super User
Super User

Hi @Anonymous - create a new calculated column to calcuate the rank the transactions for each id.

Rank:

TransactionRank =
RANKX(
    FILTER(
        'Rknk',
        'Rknk'[ID] = EARLIER('Rknk'[ID])
    ),
    'Rknk'[Transaction Date],
    ,
    DESC,
    DENSE
)
 

rajendraongole1_1-1723140946005.png

create measures to calculate the total Net Amount, Paid Amount, and Rejected Amount

TotalNetAmount =
CALCULATE(
    SUM('Rknk'[Net Amount]),
    FILTER(
        'Rknk',
        'Rknk'[TransactionRank] = 1
    )
)
 
total paid amount measure:
 
TotalPaidAmount =
CALCULATE(
    SUM('Rknk'[Paid Amount]),
    FILTER(
        'Rknk',
        'Rknk'[TransactionRank] = 1
    )
)
 
total rejected amount measure : 
 
TotalRejectedAmount =
CALCULATE(
    SUM('Rknk'[Rejected Amount]),
    FILTER(
        'Rknk',
        'Rknk'[TransactionRank] = 1
    )
)

 

Hope it helps, replace with your table name as per your model.

 

 





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Anonymous
Not applicable

@rajendraongole1 Thanks for your reply. That means rank always should be calculated column . I have done same earlier in microsoft excel data model . Unfortunately I couldnt do as rank Measure for better performance. correct me if I am wrong, so Everytime I should create calculated column in the Model where the data range is changing( adding new data weekly once).  

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