[R] merge dataframes with conditions formulated as logical expressions

[Adaikalavan Ramasamy]

You have discontinuity between your MIN.VAL and MAX.VAL for a given
group. If this is true in practise, then you may want to check and
report when VAL is in the discontinuous region.

Here is my solution that ignores that (and only uses MIN.VAL and
completely disrespecting MAX.VAL). Not very elegant but should do the
trick.


 df <- data.frame( GRP=c( "A", "A", "B" ), VAL=c( 10, 100, 200 ) )
 dp <- data.frame( GRP=c( "A", "A", "B", "B" ), MIN.VAL=c( 1, 50, 1,
70 ), MAX.VAL=c( 49, 999, 59, 999 ),  VAL2=c( 1.1, 2.2, 3.3, 4.4 ) )

 x <- split(df, df$GRP)
 y <- split(dp, dp$GRP)

 out <- NULL
 for(g in names(x)){

   xx <- x[[g]]
   yy <- y[[g]]

   w   <- cut(xx$VAL, breaks=c(yy$MIN.VAL, Inf), labels=F)
   tmp <- cbind(xx, yy[w, "VAL2"])
   colnames(tmp) <- c("GRP", "VAL", "VAL2")
   out <- rbind(out, tmp)
 } 
 out

Regards, Adai



On Wed, 2006-06-14 at 16:55 +0200, Wolfram Fischer wrote:
> I have a data.frame df containing two variables:
>     GRP: Factor
>     VAL: num
> 
> I have a data.frame dp containing:
>     GRP: Factor
>     MIN.VAL: num
>     MAX.VAL: num
>     VAL2: num
> with several rows per "GRP"
> where dp[i-1, "MAX.VAL"] < dp[i, "MIN.VAL"]
> within the same "GRP".
> 
> I want to create df[i, "VAL2"] <- dpp[z, "VAL2"] 
> with    i along df 
> and     dpp <- subset( dp, GRP = df[i, "GRP"] )
> so that it is true for each i:
>         df[i, "VAL"] > dpp[z, "MIN.VAL"]
>    and  df[i, "VAL"] <= dpp[z, "MAX.VAL"]
> 
> Is there an easy/efficient way to do that?
> 
> Example:
> df <- data.frame( GRP=c( "A", "A", "B" ), VAL=c( 10, 100, 200 ) )
> dp <- data.frame( GRP=c( "A", "A", "B", "B" ),
>     MIN.VAL=c( 1, 50, 1, 70 ), MAX.VAL=c( 49, 999, 59, 999 ), 
>     VAL2=c( 1.1, 2.2, 3.3, 4.4 ) )
> 
> The result should be:
>     df$VAL2 <- c( 1.1, 2.2, 4.4 )
> 
> Thanks - Wolfram
> 
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