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Hello
I have three date columns in a dataset, which belong to different parameters (date 1 -> P1, P2 - date 2 -> P3, P4 - date 3 -> P5, P6). How can I combine them in a way that I only ended up in a date column (date -> P1, P2, P3, P4, P5, P6)? I also want to not have any dublication date in the final result. I tried to explain in the screenshots below.
Thank you for your tips on advanced!
Solved! Go to Solution.
Hi @Anonymous ,
Based on your description, you can create a calculated table like this:
New Table =
VAR tab =
ADDCOLUMNS (
'Table',
"Date",
CALCULATE (
MAX ( 'Table'[Date 1] ),
FILTER ( ALL ( 'Table' ), 'Table'[Date 1] = EARLIER ( 'Table'[Date 1] ) )
)
)
VAR tb =
SUMMARIZE (
tab,
[Date],
[Parameter 1],
[Paremeter 2],
[Paremeter 3],
[Parameter 4],
[Paremeter 5],
[Parameter 6]
)
RETURN
tb
Attached a sample file in the below, hopes to help you.
Best Regards,
Community Support Team _ Yingjie Li
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
Hi @Anonymous ,
Based on your description, you can create a calculated table like this:
New Table =
VAR tab =
ADDCOLUMNS (
'Table',
"Date",
CALCULATE (
MAX ( 'Table'[Date 1] ),
FILTER ( ALL ( 'Table' ), 'Table'[Date 1] = EARLIER ( 'Table'[Date 1] ) )
)
)
VAR tb =
SUMMARIZE (
tab,
[Date],
[Parameter 1],
[Paremeter 2],
[Paremeter 3],
[Parameter 4],
[Paremeter 5],
[Parameter 6]
)
RETURN
tb
Attached a sample file in the below, hopes to help you.
Best Regards,
Community Support Team _ Yingjie Li
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
What I have tried myself is I duplicated the dataset two times, then keep date and related parameters in each dataset (and delete the rest):
data set 1 => date 1, P1, P2
data set 2 => date 2, P3, P4
data set 3 => date 1, P5, P6
Then I changed name of date 1, date 2, and date 3 all to date and appened all three data sets. But I ended up in many dublication dates:
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