Substituting the results of a calculation - r

Question

I'm munging data, specifically, I've opened this pdf http://pubs.acs.org/doi/suppl/10.1021/ja105035r/suppl_file/ja105035r_si_001.pdf and scraped the data from table s4,
1a 1b 1a 1b
1 5.27 4.76 5.09 4.75
2 2.47 2.74 2.77 2.80
4 1.14 1.38 1.12 1.02
6 7.43 7.35 7.22-7.35a 7.25-7.36a
7 7.38 7.34 7.22-7.35a 7.25-7.36a
8 7.23 7.20 7.22-7.35a 7.25-7.36a
9(R) 4.16 3.89 4.12b 4.18b
9(S) 4.16 3.92 4.12b 4.18b
10 1.19 0.91 1.21 1.25
pasted it into notepad and saved it as a txt file.
s4 <- read.table("s4.txt", header=TRUE, stringsAsFactors=FALSE)
gives,
X1a X1b X1a.1 X1b.1
1 5.27 4.76 5.09 4.75
2 2.47 2.74 2.77 2.80
4 1.14 1.38 1.12 1.02
6 7.43 7.35 7.22-7.35a 7.25-7.36a
7 7.38 7.34 7.22-7.35a 7.25-7.36a
8 7.23 7.20 7.22-7.35a 7.25-7.36a
in order to use the data I need to change it all to numeric and remove the letters, thanks to this link R regex gsub separate letters and numbers I can use the following code,
gsub("([[:alpha:]])","",s4[,3])
I can get rid of the extraneous letters.
What I want to do now, and the point of the question, is to change the ranges,
"7.22-7.35" "7.22-7.35" "7.22-7.35"
with their means,
"7.29"
Could I use gsub for this? (or would I need to strsplit across the hyphen, combine into a vector and return the mean?).

Answer 1

You need a single regex in strsplit for this task (removing letters and splitting):
s4[] <- lapply(s4, function(x) {
if (is.numeric(x)) x
else sapply(strsplit(as.character(x), "-|[[:alpha:]]"),
function(y) mean(as.numeric(y)))
})
The result:
> s4
X1a X1b X1a.1 X1b.1
1 5.27 4.76 5.090 4.750
2 2.47 2.74 2.770 2.800
4 1.14 1.38 1.120 1.020
6 7.43 7.35 7.285 7.305
7 7.38 7.34 7.285 7.305
8 7.23 7.20 7.285 7.305

Answer 2

Here's an approach that seems to work right on the sample data:
df[] <- lapply(df, function(col){
col <- gsub("([[:alpha:]])","", col)
col <- ifelse(grepl("-", col), mean(as.numeric(unlist(strsplit(col[grepl("-", col)], "-")))), col)
as.numeric(col)
})
> df
# X1a X1b X1a.1 X1b.1
#1 5.27 4.76 5.090 4.750
#2 2.47 2.74 2.770 2.800
#4 1.14 1.38 1.120 1.020
#6 7.43 7.35 7.285 7.305
#7 7.38 7.34 7.285 7.305
#8 7.23 7.20 7.285 7.305
Disclaimer: It only works right if the ranges in each column are all the same (as in the sample data)

Answer 3

something like that :
mean(as.numeric(unlist(strsplit("7.22-7.35","-"))))
should work (and correspond to what you had in mind I guess)
or you can do :
eval(parse(text=paste0("mean(c(",gsub("-",",","7.22-7.35"),"))")))
but I'm not sure this is simpler...
To apply it to a vector :
vec<-c("7.22-7.35","7.22-7.35")
1st solution : sapply(vec, function(x) mean(as.numeric(unlist(strsplit(x,"-")))))
2nd solution : sapply(vec, function(x) eval(parse(text=paste0("mean(c(",gsub("-",",",x),"))"))))
In both cases, you'll get :
7.22-7.35 7.22-7.35
7.285 7.285

Answer 4

Also,
library(gsubfn)
indx <- !sapply(s4, is.numeric)
s4[indx] <- lapply(s4[indx], function(x)
sapply(strapply(x, '([0-9.]+)', ~as.numeric(x)), mean))
s4
# X1a X1b X1a.1 X1b.1
#1 5.27 4.76 5.090 4.750
#2 2.47 2.74 2.770 2.800
#4 1.14 1.38 1.120 1.020
#6 7.43 7.35 7.285 7.305
#7 7.38 7.34 7.285 7.305
#8 7.23 7.20 7.285 7.305