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Anonymous
Not applicable

How to group like data onto the same row in a table

Hi All,

 

I am trying to use a table to format some data for export from Power BI to csv. The problem I am having is that I would like to group the data with the same values on the same row, but at the moment I am getting this:

 

Capture.PNG

I think I am running into problems because the data for the rows with the blank values have null values in my data, but I would to group everything with the same values onto the same row if at all possible.

 

I can't just filter off the blank values in the GB column because I lose the whole row and thus values in other columns, and I have tried using a summary table without any success.

 

Any help on how to consolidate the data onto fewer rows would be very much appreciated.

 

Andrew

3 REPLIES 3
v-yulgu-msft
Employee
Employee

Hi @Anonymous ,

 

Apart from adding fields [Family Name], [Family Type] and [Attribute] into table visual, add below measures instead of columns [GB] and [US].

GB measure = CONCATENATEX(Table3,Table3[GB])
US measure = CONCATENATEX(Table3,Table3[US])

2.png

 

Best regards,

Yuliana Gu

Community Support Team _ Yuliana Gu
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
Anonymous
Not applicable

Hi Yuliana,

 

Unfortunately I'm not getting the same result as you. If I use the measure as you have suggested the result is the concatenation of every possible value for the GB column together in the same row. Can you think of any reason this might be?

 

Andrew

Hi @Anonymous ,

 

Did the result show the concatenation of every possible value across the whole data table for the GB column, rather than showing the concatenation of every possible value per Name, per Type and per Attribute?

 

Please show the measure formula you wrote.

 

Best regards,

Yuliana Gu

Community Support Team _ Yuliana Gu
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

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