?setdiff
Sent from my iPad
On Mar 29, 2012, at 4:28, "Eric Fail" <eric.f...@gmx.us> wrote:
> Dear R experts,
>
> I've realized that it might not be possible to define a negative SELCET
> statement in a SQL call so now I'm looking for the smoothest way to generate
> a list of what I would like from my large database by first pulling all the
> names with a query like this "SELECT top 1 * FROM your_table" (thank you Bart
> Joosen for the idea) and then subtract the variables I am not allow to pull
> manually ending up with a 'positive' definition of what I want, something I
> can use in a SQL SELCT statement (see my email on this list from yesterday
> for more on that).
>
> When I query the database for the variable names I get something similar to
> 'DBquery' in my working example below, but considerable longer with over 2400
> hundred variables. As I only need to remove two or three variables I would
> like to define a lookup table (like the list 'lookup' in my example) and
> subtract that from my data base query. Now to my question. Is there a way I
> can subtract one list from another? Like setoff or alike?
>
> I would like to end up with a list like the one shown in my example called
> 'result.' In short, I would like to subtract 'lookup' from 'DBquery' and end
> up with 'result,' please note that 'result' is a list fo vecktors and not a
> list of dataframes. In my real life example DBquery is considerable longer so
> defining that by hand would make a really really long syntax.
>
> Hope someone know some smart function that I can use to solve my problem in
> an elegant way.
>
> Thanks for reading.
>
> Erick
>
> ###### begin R code ######
>
> DBquery <- list(tableA=data.frame(id = numeric(0), atwin = numeric(0),
> atrout = numeric(0)),
> tableB=data.frame(id = numeric(0), mq = numeric(0), z =
> numeric(0), m = numeric(0)),
> tableC=data.frame(V1 = numeric(0), mfn = numeric(0),
> iiff = numeric(0)),
> tableD=data.frame(id = numeric(0), msf = numeric(0),
> oom = numeric(0)))
>
> lookup <- list(tableA= c('atwin', 'atrout'),
> tableB= c('m', 'z'),
> tableC= 'ALL')
>
> ### ...
>
> result <- list(tableA= c('id'),
> tableB= c('id', 'mq'),
> tableC= c('V1', 'mfn', 'iiff'))
>
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