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Hi Power Bi Gurus,
I have a table with date and value, I am using the DAX code to fill up the gaps as following:
It is perfectly solution. But if there are duplicated date, and value(01/02/2023 which is duplicated) something wrong happened. I have to keep the duplicated rows.
So I want to introduce a var to summarize the date and value, then I stuck here :
Please help me out!!!
Thank you in advance!
Branko
ID | Date | Value |
A | 1/1/2023 | |
A | 1/2/2023 | 6 |
A | 1/2/2023 | 6 |
A | 1/4/2023 | |
A | 1/5/2023 | 12 |
A | 1/6/2023 | |
B | 1/3/2023 | |
B | 1/6/2023 | |
B | 1/7/2023 | |
B | 1/8/2023 | |
B | 1/9/2023 | 8 |
B | 1/10/2023 | |
B | 1/15/2023 | |
B | 1/17/2023 | 43 |
B | 1/18/2023 | |
C | 1/19/2023 | |
C | 1/20/2023 | |
C | 1/21/2023 | 11 |
C | 1/22/2023 |
Solved! Go to Solution.
Hi @babyjb1979 ,
Here are the steps you can follow:
1. Create measure.
Measure =
IF(
MAX('Table'[Value]) =BLANK(),
MINX(
FILTER(ALL('Table'),
'Table'[ID]=MAX('Table'[ID])&&'Table'[Date]>MAX('Table'[Date])&&'Table'[Value]<>BLANK()),[Value]),
MAX('Table'[Value]))
2. Result:
Best Regards,
Liu Yang
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly
@Anonymous
Hi Liu,
The logic appears to be correct, but please check that the data is still incorrect. Please use new data to test
ID | Date | Value |
1023201 | 9/1/2023 | |
1023201 | 9/2/2023 | |
1023201 | 9/3/2023 | |
1023201 | 9/4/2023 | |
1023201 | 9/5/2023 | |
1023201 | 9/6/2023 | |
1023201 | 9/7/2023 | |
1023201 | 9/8/2023 | |
1023201 | 9/9/2023 | |
1023201 | 9/10/2023 | |
1023201 | 9/11/2023 | |
1023201 | 9/12/2023 | 12 |
1023201 | 9/26/2023 | |
1023201 | 9/27/2023 | |
1023201 | 9/28/2023 | |
1023201 | 9/29/2023 | |
1023201 | 9/30/2023 | |
1023201 | 10/1/2023 | |
1023201 | 10/2/2023 | 7 |
221934 | 9/1/2023 | |
221934 | 9/2/2023 | |
221934 | 9/3/2023 | |
221934 | 9/4/2023 | |
221934 | 9/5/2023 | 5 |
221934 | 9/11/2023 | |
221934 | 9/12/2023 | |
221934 | 9/13/2023 | |
221934 | 9/14/2023 | |
221934 | 9/15/2023 | |
221934 | 9/16/2023 | |
221934 | 9/17/2023 | |
221934 | 9/18/2023 | |
221934 | 9/19/2023 | |
221934 | 9/20/2023 | |
221934 | 9/21/2023 | |
221934 | 9/22/2023 | |
221934 | 9/23/2023 | |
221934 | 9/24/2023 | |
221934 | 9/25/2023 | |
221934 | 9/26/2023 | 16 |
246075 | 9/1/2023 | |
246075 | 9/2/2023 | |
246075 | 9/3/2023 | |
246075 | 9/4/2023 | |
246075 | 9/5/2023 | |
246075 | 9/6/2023 | |
246075 | 9/7/2023 | |
246075 | 9/8/2023 | |
246075 | 9/9/2023 | |
246075 | 9/10/2023 | |
246075 | 9/11/2023 | |
246075 | 9/12/2023 | |
246075 | 9/13/2023 | |
246075 | 9/14/2023 | 14 |
246075 | 9/27/2023 | |
246075 | 9/28/2023 | |
246075 | 9/29/2023 | |
246075 | 9/30/2023 | |
246075 | 10/1/2023 | |
246075 | 10/2/2023 | |
246075 | 10/3/2023 | 7 |
Hi @babyjb1979 ,
Here are the steps you can follow:
1. Create measure.
Measure =
IF(
MAX('Table'[Value]) =BLANK(),
MINX(
FILTER(ALL('Table'),
'Table'[ID]=MAX('Table'[ID])&&'Table'[Date]>MAX('Table'[Date])&&'Table'[Value]<>BLANK()),[Value]),
MAX('Table'[Value]))
2. Result:
Best Regards,
Liu Yang
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly
@Anonymous
The logic appears to be correct, but please check that the data is still incorrect. Please use the new data to test. Thank you very much for your time and help!!!
| ||
ID | Date | Value |
1023201 | 9/1/2023 0:00 | |
1023201 | 9/2/2023 0:00 | |
1023201 | 9/3/2023 0:00 | |
1023201 | 9/4/2023 0:00 | |
1023201 | 9/5/2023 0:00 | |
1023201 | 9/6/2023 0:00 | |
1023201 | 9/7/2023 0:00 | |
1023201 | 9/8/2023 0:00 | |
1023201 | 9/9/2023 0:00 | |
1023201 | 9/10/2023 0:00 | |
1023201 | 9/11/2023 0:00 | |
1023201 | 9/12/2023 0:00 | 12 |
1023201 | 9/26/2023 0:00 | |
1023201 | 9/27/2023 0:00 | |
1023201 | 9/28/2023 0:00 | |
1023201 | 9/29/2023 0:00 | |
1023201 | 9/30/2023 0:00 | |
1023201 | 10/1/2023 0:00 | |
1023201 | 10/2/2023 0:00 | 7 |
221934 | 9/1/2023 0:00 | |
221934 | 9/2/2023 0:00 | |
221934 | 9/3/2023 0:00 | |
221934 | 9/4/2023 0:00 | |
221934 | 9/5/2023 0:00 | 5 |
221934 | 9/11/2023 0:00 | |
221934 | 9/12/2023 0:00 | |
221934 | 9/13/2023 0:00 | |
221934 | 9/14/2023 0:00 | |
221934 | 9/15/2023 0:00 | |
221934 | 9/16/2023 0:00 | |
221934 | 9/17/2023 0:00 | |
221934 | 9/18/2023 0:00 | |
221934 | 9/19/2023 0:00 | |
221934 | 9/20/2023 0:00 | |
221934 | 9/21/2023 0:00 | |
221934 | 9/22/2023 0:00 | |
221934 | 9/23/2023 0:00 | |
221934 | 9/24/2023 0:00 | |
221934 | 9/25/2023 0:00 | |
221934 | 9/26/2023 0:00 | 16 |
246075 | 9/1/2023 0:00 | |
246075 | 9/2/2023 0:00 | |
246075 | 9/3/2023 0:00 | |
246075 | 9/4/2023 0:00 | |
246075 | 9/5/2023 0:00 | |
246075 | 9/6/2023 0:00 | |
246075 | 9/7/2023 0:00 | |
246075 | 9/8/2023 0:00 | |
246075 | 9/9/2023 0:00 | |
246075 | 9/10/2023 0:00 | |
246075 | 9/11/2023 0:00 | |
246075 | 9/12/2023 0:00 | |
246075 | 9/13/2023 0:00 | |
246075 | 9/14/2023 0:00 | 14 |
246075 | 9/27/2023 0:00 | |
246075 | 9/28/2023 0:00 | |
246075 | 9/29/2023 0:00 | |
246075 | 9/30/2023 0:00 | |
246075 | 10/1/2023 0:00 | |
246075 | 10/2/2023 0:00 | |
246075 | 10/3/2023 0:00 | 7 |
Would you like to address gaps in your data by inserting missing dates and updating the value column with the most recent non-blank value? For instance, if there's a missing date like 1/3/2023, would you want to create a new row with that date and a value of 6 copied from the previous date?
I want to fill up the blank with the lastest non-blank value
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