Which function to use: grep, replace, substr etc.?

Hello,

I have a simple question but I don't know which method is best to  
use for my
problem.

I have the following strings:

str1 <- "My_name_is_peter"
str2 <- "what_is_your_surname_peter"

I would like to apply predefined abbreviations for peter=p and  
name=n to
both strings
so that the new strings look like the followings:

str1: "My_n_is_p"
str2: "what_is_your_surn_p"

Which method is the best to use for that particular problem?

Note that "male" comes before "female" in your data frame.
---------------------------------------------------------------------------
Jeff Newmiller The ..... ..... Go Live...

syrvn <mentor_ at gmx.net> wrote:

Hi,

thanks for the tip! I do it as follows now but I still have a  
problem I do
not understand:


abbrvs <- data.frame(c("peter", "name", "male", "female"),
		 	 c("P", "N", "m", "f"))
						
colnames(abbrvs) <- c("pattern", "replacement")
	
str <- "My name is peter and I am male"

for(m in 1:nrow(abbrvs)) {
		str <- sub(abbrvs$pattern[m], abbrvs$replacement[m], str,  
fixed=TRUE)
		print(str)
	}
	

This works perfectly fine as I get: "My N is P and I am m"

However, when I replace male by female then I get the following: "My  
N is P
and I am fem"

but I want to have "My N is P and I am f".

Even with the parameter fixed=true I get the same result. Why is that?

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf Of David Winsemius
Sent: Sunday, October 16, 2011 1:59 PM
To: Jeff Newmiller
Cc: r-help at r-project.org; syrvn
Subject: Re: [R] Which function to use: grep, replace, substr etc.?


On Oct 16, 2011, at 1:32 PM, Jeff Newmiller wrote:

Note that "male" comes before "female" in your data frame.
---------------------------------------------------------------------------
Jeff Newmiller The ..... ..... Go Live...

syrvn <mentor_ at gmx.net> wrote:

Hi,

thanks for the tip! I do it as follows now but I still have a
problem I do
not understand:


abbrvs <- data.frame(c("peter", "name", "male", "female"),
		 	 c("P", "N", "m", "f"))

colnames(abbrvs) <- c("pattern", "replacement")

str <- "My name is peter and I am male"

for(m in 1:nrow(abbrvs)) {
		str <- sub(abbrvs$pattern[m], abbrvs$replacement[m], str,
fixed=TRUE)
		print(str)
	}


This works perfectly fine as I get: "My N is P and I am m"

However, when I replace male by female then I get the following: "My
N is P
and I am fem"

but I want to have "My N is P and I am f".

Even with the parameter fixed=true I get the same result. Why is that?

Because "male" is in "female? This reminds me of a comment on a
posting I made this morning on SO.
http://stackoverflow.com/questions/7782113/counting-keyword-occurrences-in-r

The problem was slightly different, but the greppish principle was
that in order to match only complete words, you need to specific "^",
"$" or " " at each end of the word:

dataset <- c("corn", "cornmeal", "corn on the cob", "meal")
grep("^corn$|^corn | corn$", dataset)
[1] 1 3

In such cases you may want to look at the gsubfn package. It offers
higher level matching functions and I think strapply might be more
efficient and expressive here. I can imagine construction in a loop
such as yours, but you would probably want to build a pattern outside
the sub() call.

After struggling to fix your loop (and your data.frame which
definitely should not be using factor variables), I am even more
convinced you should be learning "gubfn" facilities. (Tate out the
debugging print statements.)

 > abbrvs <- data.frame(c("peter", "name", "male", "female"),

+ 		 	 c(" P ", " N ", " m ", " f "), stringsAsFactors=FALSE)

 >
 > colnames(abbrvs) <- c("pattern", "replacement")

 > for(m in 1:nrow(abbrvs)) { patt <- paste("^",abbrvs$pattern[m], "$|

",
+                   abbrvs$pattern[m], " | ",
+                   abbrvs$pattern[m], "$", sep="")
+              print(c( patt, abbrvs$replacement[m]))
+ 		str <- sub(patt, abbrvs$replacement[m], str)
+ 		print(str)
+ 	}
[1] "^peter$| peter | peter$" " P "
[1] "My name is P and I am female"
[1] "^name$| name | name$" " N "
[1] "My N is P and I am female"
[1] "^male$| male | male$" " m "
[1] "My N is P and I am female"
[1] "^female$| female | female$" " f "
[1] "My N is P and I am f "

--

David Winsemius, MD
Heritage Laboratories
West Hartford, CT