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Hello All,
Unfortunately, I am unable to share my data for security reasons.
I am looking to create 2 columns depending on Category 1 or 2 equalling YES, it will tell me if the customer ID has appeared before within the last 12 months and if so how many times.
an example of my data is below
Row ID | Date | customer ID | Category 1 | Category 2 |
1 | 01/01/2022 | 1 | YES | NO |
2 | 01/01/2022 | 2 | YES | NO |
3 | 01/02/2022 | 1 | NO | YES |
4 | 01/03/2022 | 1 | YES | YES |
any help would be great,
THANKS ALL
@Anonymous thank you for your reply.
Unfortunately, this is not what I am looking for.
I am looking to replace "Repeat CAT1" & "Repeat CAT2" with calculated columns. These were created as an example of what outcome I am expecting/ would like.
The calculation should first identify if the customer ID has been repeated within the last 12 months (from today, not the date of the row) with category 1 as YES. If the above is true count row id with that person id, within the last 12 months.
This would then be duplicated on another column to identify the same but with category 2 as YES.
I hope this makes sense,
Thanks
Will
Hi @Will_Powell93 ,
I have created a simple sample, please refer to it to see if it helps you.
Create 2 measures.
Measure =
VAR _12months =
EDATE ( MAX ( 'Table'[Date] ), -12 )
VAR _customer =
SELECTEDVALUE ( 'Table'[Customer ID] )
VAR _1re =
CALCULATE (
MIN ( 'Table'[Date] ),
FILTER (
ALL ( 'Table' ),
'Table'[Customer ID] = SELECTEDVALUE ( 'Table'[Customer ID] )
&& ( 'Table'[Category 1] = "Yes"
|| 'Table'[Category 2] = "Yes" )
&& 'Table'[Date] < SELECTEDVALUE ( 'Table'[Date] )
&& 'Table'[Date] >= _12months
)
)
RETURN
_1re
Measure2 =
COUNTAX ( FILTER ( ALL ( 'Table' ), [Measure] <> BLANK () ), [Measure] )
How to Get Your Question Answered Quickly
If it does not help, please provide more details with your desired output and pbix file without privacy information (or some sample data) .
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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.
Apologies,
Ideally 2 new colunms would be added to the orginal dataset, to show count of cases that the customer has appeared in example below.
Row ID | Date | Customer ID | Category 1 | Category 2 | Repeat CAT1 | Repeat CAT2 |
1 | 01/01/2020 | 1 | YES | NO | ||
2 | 01/01/2022 | 2 | YES | NO | 1 | |
3 | 01/02/2022 | 1 | NO | YES | 2 | 2 |
4 | 01/03/2022 | 1 | YES | YES | 2 | 2 |
5 | 01/03/2019 | 3 | NO | YES | ||
6 | 01/10/2022 | 3 | YES | NO | 1 | |
7 | 01/10/2022 | 4 | YES | NO | 2 | |
8 | 01/10/2022 | 4 | YES | NO | 2 |
I attempted the below calculation but return incorrect numbers.
VAR ID=customerID
RETURN
IF( CAT1 = "YES" && DATE > (TODAY() - 365),
Calculate( count(rowid)
,filter(table , CAT1 = "YES" && DATE > (TODAY() - 365) && ID=CustomerID))
,blank())
@FreemanZ hope this helps,
thanks
the logic is too vague. additional explanation with expected table would be very helpful for those who may help you.
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