Robert,

Something like this?

sort cases by Cluster.
execute.
split file by Cluster.
execute.
freq  / Code.
split file off.
execute.

All that was from memory and untested; my apologies if I remembered
wrong but hopefully it suggests the solution.

-Alan

On 4/16/2015 5:14 AM, Robert Orzanna wrote:
> Dear all,
>
> I recently started using PSPP to analyse sav data. I must say that I
> have no previous experience with SPSS. But from what I have seen so
> far, I very much like PSPP. I have one (maybe simple) question that I
> couldn't find an answer for in the documentation.
>
> In an Excel file I have a list that looks as follows:
>
> Cluster | Code
> 2A         | 33edfdkeew
> 2A         | 29dnewdnd
> 2B         | sd2034wss
> 2B         | 29jsnn2221
>
> Then I have a sav file that I analyse with PSPP. This file contains ~
> 400 cases, all with unique entries for the "Code" variable. I want to
> perform the analysis of the data for the different clusters. Thus, I
> want to filter the file for cases whose codes belong to a specific
> cluster.
>
> What is the best way of doing this in PSPP?
>
> Select cases only allows me to select a random case sample, based on a
> range (but only allowing me to select case numbers) or a filter
> variable (which I don't have in my default sav file).
>
> My current idea was to create 2 new variables for the two different
> clusters and then assign a 1 to the variable for each case that
> belongs to the respective cluster. However, this seems to be very
> inconvenient and I am wondering if there is a better way to do this.
>
> Thanks ahead!
>
> Robert
>
> -- 
>
> mindfully present. just be and let go.
> passionate. simple life. user-centred design.
> impulsive thinking. human hearted.
> Co-Creator of @MindfulMeerkats <https://twitter.com/MindfulMeerkat>.
>
> Website: robert.orzanna.de <http://robert.orzanna.de/>
> Twitter: @orschiro <https://twitter.com/orschiro>
>
>
>
> _______________________________________________
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> Pspp-users@gnu.org
> https://lists.gnu.org/mailman/listinfo/pspp-users

-- 

Alan D. Mead, Ph.D.
President, Talent Algorithms Inc.

science + technology = better workers

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