On Sun, 9 Jun 2002, Patrick Hausmann wrote:
> Hello,
>
> I have a csv-file which looks like:
>
> #### pwt6_r.csv ####
> code;year;rgdpch
> AGO;1998;1234
> ALB;1998;3576
> ARG;1998;#NA
> SVN;1996;13439
> SWE;1996;21492
> AGO;1960;#NA
> ALB;1960;2345
> ARG;1960;4634
> #### pwt6_r.csv ####
>
> To import this file i call:
>
pwt6<-read.csv("d:/pwt6_r.csv",header=T,na.strings="#NA",sep=";")
>
> Now I want to generate a new data.frame which include only
> + observations for the years 1960 and 1998
> + where the variable 'rgdpch' has no missing values.
pwt6[(pwt6$year %in% c("1996", "1998")) &
!is.na(pwt6$rgdch), ]
if you actually meant the rows in which 'rgdpch' was not missing.
>
> The result should be:
>
> code;year;rgdpch
> ALB;1998;3576
> ALB;1960;2345
>
> I tried to solve this with logical operators (==), but without any
> success.
It can be done, and as you did not tell us what you tried, we cannot help
correct your misconceptions.
> Thanks for your help!
> Patrick
> -------------
> Patrick Hausmann
> Friedrich-Wilhelm Str. 37 - D-28199 Bremen
> Tel. +49 421 5980631 - Fax. +49 421 5980632
>
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--
Brian D. Ripley, ripley at stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
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