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> > > > > _______________________________________________ > Pspp-users mailing list > 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 +815.588.3846 (Office) +267.334.4143 (Mobile) http://www.alanmead.org Announcing the Journal of Computerized Adaptive Testing (JCAT), a peer-reviewed electronic journal designed to advance the science and practice of computerized adaptive testing: http://www.iacat.org/jcat
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