Dear Aurelien,
Thanks for the reproducible example. Here is one way:
yyyymm<- c("19860228", "19860331","19860430","19860531")
id<-c("10000","10000","10000","10000")
re<- c("C","0.25", "0.98", "1.34")
mret <- data.frame(yyyymm, id, re)
subset(mret, !is.na(as.numeric(as.character(re))))
HTH,
Jorge.-
On Wed, Mar 14, 2012 at 6:07 PM, Aurélien PHILIPPOT <> wrote:
> Dear R experts,
> I have a dataframe imported from a csv file (with read.csv).
>
> Here is an example:
>
> yyyymm<- c("19860228", "19860331","19860430","19860531")
> id<-c("10000","10000","10000","10000")
> re<- c("C","0.25", "0.98", "1.34")
>
> mret<-data.frame(yyyymm, id, re)
>
> mret<-as.numeric(as.character(mret$re))
> Error: (converted from warning) NAs introduced by coercion
>
>
> One of the column ("re" in the example above) has characters and numbers,
> but it should be treated a numeric column. Therefore, I want to eliminate
> the rows in which the variable re has characters values (the first row in
> the example).
> In the past, I always used this code successfully (the characters were
> replaced by NA, and only a warning message was issued). But now, I have an
> error message and it no longer works. Could anyone suggest an alternative
> way to do it?
>
> Thanks a lot,
> Best,
> Aurelien
>
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>
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