What is the most useful R trick? [closed]

Answer 1

In R programming (not interactive sessions), I use if (bad.condition) stop("message") a lot. Every function starts with a few of these, and as I work through computations, I pepper these in, too. I guess I got into the habit from using assert() in C. The benefits are two-fold. First, it's a lot faster to get working code with these checks in place. Second, and probably more important, it is a lot easier to work with existing code when you see these checks on every screen in your editor. You won't have to wonder whether x>0, or trust a comment stating that it is ... you'll know, from a glance, that it is.

PS. my first post here. Be gentle!

Answer 2

I've posted this once before but I use it so much I thought I'd post it again. Its just a little function to return the names and position numbers of a data.frame. Its nothing special to be sure, but I almost never make it through a session without using it multiple times.

##creates an object from a data.frame listing the column names and location

namesind=function(df){

temp1=names(df)
temp2=seq(1,length(temp1))
temp3=data.frame(temp1,temp2)
names(temp3)=c("VAR","COL")
return(temp3)
rm(temp1,temp2,temp3)

}

ni <- namesind

Answer 3

str() tells you the structure of any object.

Answer 4

Use backticks to reference non standard names.

> df <- data.frame(x=rnorm(5),y=runif(5))
> names(df) <- 1:2
> df
           1         2
1 -1.2035003 0.6989573
2 -1.2146266 0.8272276
3  0.3563335 0.0947696
4 -0.4372646 0.9765767
5 -0.9952423 0.6477714
> df$1
Error: unexpected numeric constant in "df$1"
> df$`1`
[1] -1.2035003 -1.2146266  0.3563335 -0.4372646 -0.9952423

In this case, df[,"1"] would also work. But back ticks work inside formulas!

> lm(`2`~`1`,data=df)

Call:
lm(formula = `2` ~ `1`, data = df)

Coefficients:
(Intercept)          `1`  
     0.4087      -0.3440  

[Edit] Dirk asks why one would give invalid names? I don't know! But I certainly encounter this problem in practice fairly often. For example, using hadley's reshape package:

> library(reshape)
> df$z <- c(1,1,2,2,2)
> recast(df,z~.,id.var="z")
Aggregation requires fun.aggregate: length used as default
  z (all)
1 1     4
2 2     6
> recast(df,z~.,id.var="z")$(all)
Error: unexpected '(' in "recast(df,z~.,id.var="z")$("
> recast(df,z~.,id.var="z")$`(all)`
Aggregation requires fun.aggregate: length used as default
[1] 4 6

Answer 5

To perform an operation on a number of variables in a data frame. This is stolen from subset.data.frame.

get.vars<-function(vars,data){
    nl <- as.list(1L:ncol(data))
    names(nl) <- names(data)
    vars <- eval(substitute(vars), nl, parent.frame())
    data[,vars]
    #do stuff here
}

get.vars(c(cyl:hwy,class),mpg)

Answer 6

Don't know how well known this is/isn't, but something that I've definitely taken advantage of are the pass-by-reference capabilities of environments.

zz <- new.env()
zz$foo <- c(1,2,3,4,5)
changer <- function(blah) {
   blah$foo <- 5
}
changer(zz)
zz$foo

For this example it doesn't make sense why it'd be useful, but if you're passing large objects around it can help.