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I have a table with data similar to below:
ID | Date A | Date B | Date Diff |
1 | 02.06.2021 | ||
2 | 09.07.2021 | ||
3 | 01.01.2021 | 05.01.2021 | 4 |
4 | 07.02.2021 | 01.02.2021 | -6 |
As you can see there are four possible outcomes...
1. Date A happens first and there is no Date B for this row
2. Date B happens first and there is no Date A for this row
3. Date A happens first but the action has been taken in Date B too
4. Date B happens first but the action has been taken in Date A too
I want to be able to make a table which shows the count for each four items 1-4. So I can identify which is the most popular flow.
Then also for 1 and 2 I will be able to manipulate the date diff.
Please advise?
Solved! Go to Solution.
is this what you want?
1 = countx(FILTER('Table',ISBLANK('Table'[Date B])),'Table'[Date A])
2 = countx(FILTER('Table',ISBLANK('Table'[Date A])),'Table'[Date B])
3 = countx(FILTER('Table','Table'[Date A]<'Table'[Date B]),'Table'[Date A])
4 = countx(FILTER('Table','Table'[Date A]>'Table'[Date B]&&NOT(ISBLANK('Table'[Date B]))),'Table'[Date A])
Proud to be a Super User!
Hi @andrewb95 ,
According to your description, I did a test and think that the solution provided by @ryan_mayu can meet your needs. If there is still confusion, please point out and provide the desired result, I will answer you as soon as possible.
Looking forward to your reply.
Best Regards,
Henry
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
is this what you want?
1 = countx(FILTER('Table',ISBLANK('Table'[Date B])),'Table'[Date A])
2 = countx(FILTER('Table',ISBLANK('Table'[Date A])),'Table'[Date B])
3 = countx(FILTER('Table','Table'[Date A]<'Table'[Date B]),'Table'[Date A])
4 = countx(FILTER('Table','Table'[Date A]>'Table'[Date B]&&NOT(ISBLANK('Table'[Date B]))),'Table'[Date A])
Proud to be a Super User!
@andrewb95 , expected output is not clear, what value should be there in first 2 rows
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