Sam Albers
2012-Jan-19 23:05 UTC
[R] Establishing groups using something other than ifelse()
Hello all, This is one of those "Is there a better way to do this questions". Say I have a dataframe (df) with a grouping variable (z). This is my base data. Now I know that there is a higher order level of grouping that exist for my group variable. So what I want to do is create a new column that express that higher order level of grouping based on values in the sub-group (z in this case). In the past I have used ifelse() but this tends to get fairly redundant and messy with a large amount of sub-groupings (z). I've created a sample dataset below. Can anyone recommend a better way of achieving what I am currently achieving with ifelse()? A long series of ifelse statements makes me think that there is something better for this. ## Dataframe creation df <- data.frame(x=runif(36, 0, 120), y=runif(36, 0, 120), z=factor(c("A1","A1","A2","A2","B1","B1","B2","B2","C1","C","C2","C2")) ) ## Current method is grouping df$Big.Group <- with(df, ifelse(df$z=="A1","A", ifelse(df$z=="A2","A", ifelse(df$z=="B1", "B", ifelse(df$z=="B2", "B", "C"))))) So any suggestions? Thanks in advance! Sam
Justin Haynes
2012-Jan-19 23:34 UTC
[R] Establishing groups using something other than ifelse()
how bout levels(df$z)[grep('A',levels(df$z))] <- 'A' levels(df$z)[grep('B',levels(df$z))] <- 'B' levels(df$z)[grep('C',levels(df$z))] <- 'C' does that do what you're wanting? On Thu, Jan 19, 2012 at 3:05 PM, Sam Albers <tonightsthenight@gmail.com>wrote:> Hello all, > > This is one of those "Is there a better way to do this questions". Say > I have a dataframe (df) with a grouping variable (z). This is my base > data. Now I know that there is a higher order level of grouping that > exist for my group variable. So what I want to do is create a new > column that express that higher order level of grouping based on > values in the sub-group (z in this case). In the past I have used > ifelse() but this tends to get fairly redundant and messy with a large > amount of sub-groupings (z). I've created a sample dataset below. Can > anyone recommend a better way of achieving what I am currently > achieving with ifelse()? A long series of ifelse statements makes me > think that there is something better for this. > > ## Dataframe creation > df <- data.frame(x=runif(36, 0, 120), > y=runif(36, 0, 120), > > z=factor(c("A1","A1","A2","A2","B1","B1","B2","B2","C1","C","C2","C2")) > ) > > ## Current method is grouping > df$Big.Group <- with(df, ifelse(df$z=="A1","A", ifelse(df$z=="A2","A", > ifelse(df$z=="B1", "B", ifelse(df$z=="B2", "B", "C"))))) > > > So any suggestions? Thanks in advance! > > Sam > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >[[alternative HTML version deleted]]
Jorge I Velez
2012-Jan-19 23:49 UTC
[R] Establishing groups using something other than ifelse()
Hi Sam, Check the examples in require(car) ?recode HTH, Jorge.- On Thu, Jan 19, 2012 at 6:05 PM, Sam Albers <> wrote:> Hello all, > > This is one of those "Is there a better way to do this questions". Say > I have a dataframe (df) with a grouping variable (z). This is my base > data. Now I know that there is a higher order level of grouping that > exist for my group variable. So what I want to do is create a new > column that express that higher order level of grouping based on > values in the sub-group (z in this case). In the past I have used > ifelse() but this tends to get fairly redundant and messy with a large > amount of sub-groupings (z). I've created a sample dataset below. Can > anyone recommend a better way of achieving what I am currently > achieving with ifelse()? A long series of ifelse statements makes me > think that there is something better for this. > > ## Dataframe creation > df <- data.frame(x=runif(36, 0, 120), > y=runif(36, 0, 120), > > z=factor(c("A1","A1","A2","A2","B1","B1","B2","B2","C1","C","C2","C2")) > ) > > ## Current method is grouping > df$Big.Group <- with(df, ifelse(df$z=="A1","A", ifelse(df$z=="A2","A", > ifelse(df$z=="B1", "B", ifelse(df$z=="B2", "B", "C"))))) > > > So any suggestions? Thanks in advance! > > Sam > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >[[alternative HTML version deleted]]
Duncan Murdoch
2012-Jan-20 03:39 UTC
[R] Establishing groups using something other than ifelse()
On 12-01-19 6:05 PM, Sam Albers wrote:> Hello all, > > This is one of those "Is there a better way to do this questions". Say > I have a dataframe (df) with a grouping variable (z). This is my base > data. Now I know that there is a higher order level of grouping that > exist for my group variable. So what I want to do is create a new > column that express that higher order level of grouping based on > values in the sub-group (z in this case). In the past I have used > ifelse() but this tends to get fairly redundant and messy with a large > amount of sub-groupings (z). I've created a sample dataset below. Can > anyone recommend a better way of achieving what I am currently > achieving with ifelse()? A long series of ifelse statements makes me > think that there is something better for this. > > ## Dataframe creation > df<- data.frame(x=runif(36, 0, 120), > y=runif(36, 0, 120), > > z=factor(c("A1","A1","A2","A2","B1","B1","B2","B2","C1","C","C2","C2")) > ) > > ## Current method is grouping > df$Big.Group<- with(df, ifelse(df$z=="A1","A", ifelse(df$z=="A2","A", > ifelse(df$z=="B1", "B", ifelse(df$z=="B2", "B", "C"))))) > > > So any suggestions? Thanks in advance!Use a named vector, e.g. newcodes <- c(A1="A", A2="A", ... etc. Then Big.Group <- newcodes[as.character(z)] Duncan Murdoch