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Home/ Questions/Q 8411131
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Editorial Team
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Editorial Team
Asked: June 10, 20262026-06-10T00:21:48+00:00 2026-06-10T00:21:48+00:00

I’m looking to ‘flatten’ my dataset in order to facilitate data mining. Each categorical

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I’m looking to ‘flatten’ my dataset in order to facilitate data mining.
Each categorical column should be changed to multiple Boolean columns.
I have a column with categorical values, e.g.:

 ID    col1
  1     A
  2     B
  3     A

I’m looking for a way to pivot this table, and have an aggregated function telling me whether this ID has value A or B:

Result:

 ID    col1A    col1B
  1     1        0
  2     0        1
  3     1        0

I tried using PIVOT but have no idea which aggregated function to use inside it.

Also looked for answers in SF but couldn’t find any…

I’m using MS-SQL 2012.

Any help would be appreciated!
Omri

EDIT:

The number of categories in col1 is unknown, therefore the solution must be dynamic.
Thanks 🙂

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1 Answer

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  1. Editorial Team
    Editorial Team
    2026-06-10T00:21:50+00:00Added an answer on June 10, 2026 at 12:21 am

    try this:

    select ID,
             col1A=(case when col1='A' then 1 else 0 end),
             col1B=(case when col1='B' then 1 else 0 end)
      from <table>    
    

    IF you have one ID with both A and B and you want to have distinct ID in the output you could do

     select ID,
             col1A=max(case when col1='A' then 1 else 0 end),
             col1B=max(case when col1='B' then 1 else 0 end)
      from <table> 
      group by id
    

    EDIT

    As per your comment, If you do not know the number of options for col1, then you can go for dynamic PIVOT

    DECLARE @cols AS NVARCHAR(MAX),
        @query  AS NVARCHAR(MAX)
    
    select @cols = STUFF((SELECT distinct ',' + QUOTENAME(col1) 
                        from <table> 
                FOR XML PATH(''), TYPE
                ).value('.', 'NVARCHAR(MAX)') 
            ,1,1,'')
    
    set @query = 'SELECT id, ' + @cols + ' from <table> 
    
                pivot 
                (
                    count([col1])
                    for col1 in (' + @cols + ')
                ) p '
    print(@query)
    execute(@query)
    

    SQL Fiddle Demo

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