I want to extract the first (or last) n characters of a string. This would be the equivalent to Excel's LEFT() and RIGHT(). A small example:
# create a string
a <- paste('left', 'right', sep = '')
a
# [1] "leftright"
I would like to produce b, a string which is equal to the first 4 letters of a:
b
# [1] "left"
What should I do?
See ?substr
R> substr(a, 1, 4)
[1] "left"
The stringr package provides the str_sub function, which is a bit easier to use than substr, especially if you want to extract right portions of your string :
R> str_sub("leftright",1,4)
[1] "left"
R> str_sub("leftright",-5,-1)
[1] "right"
You can easily obtain Right() and Left() functions starting from the Rbase package:
right function
right = function (string, char) {
substr(string,nchar(string)-(char-1),nchar(string))
}
left function
left = function (string,char) {
substr(string,1,char)
}
you can use those two custom-functions exactly as left() and right() in excel.
Hope you will find it useful
Make it simple and use R basic functions:
# To get the LEFT part:
> substr(a, 1, 4)
[1] "left"
>
# To get the MIDDLE part:
> substr(a, 3, 7)
[1] "ftrig"
>
# To get the RIGHT part:
> substr(a, 5, 10)
[1] "right"
The substr() function tells you where start and stop substr(x, start, stop)
For those coming from Microsoft Excel or Google Sheets, you would have seen functions like LEFT(), RIGHT(), and MID(). I have created a package known as forstringr and its development version is currently on Github.
if(!require("devtools")){
install.packages("devtools")
}
devtools::install_github("gbganalyst/forstringr")
library(forstringr)
the str_left(): This counts from the left and then extract n characters
the str_right()- This counts from the right and then extract n characters
the str_mid()- This extract characters from the middle
Examples:
x <- "some text in a string"
str_left(x, 4)
[1] "some"
str_right(x, 6)
[1] "string"
str_mid(x, 6, 4)
[1] "text"
Related
I want to find the pattern from any position in any given string such that the pattern repeats for a threshold number of times at least.
For example for the string "a0cc0vaaaabaaaabaaaabaa00bvw" the pattern should come out to be "aaaab". Another example: for the string "ff00f0f0f0f0f0f0f0f0000" the pattern should be "0f".
In both cases threshold has been taken as 3 i.e. the pattern should be repeated for at least 3 times.
If someone can suggest an optimized method in R for finding a solution to this problem, please do share with me. Currently I am achieving this by using 3 nested loops, and it's taking a lot of time.
Thanks!
Use regular expressions, which are made for this type of stuff. There may be more optimized ways of doing it, but in terms of easy to write code, it's hard to beat. The data:
vec <- c("a0cc0vaaaabaaaabaaaabaa00bvw","ff00f0f0f0f0f0f0f0f0000")
The function that does the matching:
find_rep_path <- function(vec, reps) {
regexp <- paste0(c("(.+)", rep("\\1", reps - 1L)), collapse="")
match <- regmatches(vec, regexpr(regexp, vec, perl=T))
substr(match, 1, nchar(match) / reps)
}
And some tests:
sapply(vec, find_rep_path, reps=3L)
# a0cc0vaaaabaaaabaaaabaa00bvw ff00f0f0f0f0f0f0f0f0000
# "aaaab" "0f0f"
sapply(vec, find_rep_path, reps=5L)
# $a0cc0vaaaabaaaabaaaabaa00bvw
# character(0)
#
# $ff00f0f0f0f0f0f0f0f0000
# [1] "0f"
Note that with threshold as 3, the actual longest pattern for the second string is 0f0f, not 0f (reverts to 0f at threshold 5). In order to do this, I use back references (\\1), and repeat these as many time as necessary to reach threshold. I need to then substr the result because annoyingly base R doesn't have an easy way to get just the captured sub expressions when using perl compatible regular expressions. There is probably a not too hard way to do this, but the substr approach works well in this example.
Also, as per the discussion in #G. Grothendieck's answer, here is the version with the cap on length of pattern, which is just adding the limit argument and the slight modification of the regexp.
find_rep_path <- function(vec, reps, limit) {
regexp <- paste0(c("(.{1,", limit,"})", rep("\\1", reps - 1L)), collapse="")
match <- regmatches(vec, regexpr(regexp, vec, perl=T))
substr(match, 1, nchar(match) / reps)
}
sapply(vec, find_rep_path, reps=3L, limit=3L)
# a0cc0vaaaabaaaabaaaabaa00bvw ff00f0f0f0f0f0f0f0f0000
# "a" "0f"
find.string finds substring of maximum length subject to (1) substring must be repeated consecutively at least th times and (2) substring length must be no longer than len.
reps <- function(s, n) paste(rep(s, n), collapse = "") # repeat s n times
find.string <- function(string, th = 3, len = floor(nchar(string)/th)) {
for(k in len:1) {
pat <- paste0("(.{", k, "})", reps("\\1", th-1))
r <- regexpr(pat, string, perl = TRUE)
if (attr(r, "capture.length") > 0) break
}
if (r > 0) substring(string, r, r + attr(r, "capture.length")-1) else ""
}
and here are some tests. The last test processes the entire text of James Joyce's Ulysses in 1.4 seconds on my laptop:
> find.string("a0cc0vaaaabaaaabaaaabaa00bvw")
[1] "aaaab"
> find.string("ff00f0f0f0f0f0f0f0f0000")
[1] "0f0f"
>
> joyce <- readLines("http://www.gutenberg.org/files/4300/4300-8.txt")
> joycec <- paste(joyce, collapse = " ")
> system.time(result <- find.string2(joycec, len = 25))
user system elapsed
1.36 0.00 1.39
> result
[1] " Hoopsa boyaboy hoopsa!"
ADDED
Although I developed my answer before having seen BrodieG's, as he points out they are very similar to each other. I have added some features of his to the above to get the solution below and tried the tests again. Unfortunately when I added the variation of his code the James Joyce example no longer works although it does work on the other two examples shown. The problem seems to be in adding the len constraint to the code and may represent a fundamental advantage of the code above (i.e. it can handle such a constraint and such constraints may be essential for very long strings).
find.string2 <- function(string, th = 3, len = floor(nchar(string)/th)) {
pat <- paste0(c("(.", "{1,", len, "})", rep("\\1", th-1)), collapse = "")
r <- regexpr(pat, string, perl = TRUE)
ifelse(r > 0, substring(string, r, r + attr(r, "capture.length")-1), "")
}
> find.string2("a0cc0vaaaabaaaabaaaabaa00bvw")
[1] "aaaab"
> find.string2("ff00f0f0f0f0f0f0f0f0000")
[1] "0f0f"
> system.time(result <- find.string2(joycec, len = 25))
user system elapsed
0 0 0
> result
[1] "w"
REVISED The James Joyce test that was supposed to be testing find.string2 was actually using find.string. This is now fixed.
Not optimized (even it is fast) function , but I think it is more R way to do this.
Get all patterns of certains length > threshold : vectorized using mapply and substr
Get the occurrence of these patterns and extract the one with maximum occurrence : vectorized using str_locate_all.
Repeat 1-2 this for all lengths and tkae the one with maximum occurrence.
Here my code. I am creating 2 functions ( steps 1-2) and step 3:
library(stringr)
ss = "ff00f0f0f0f0f0f0f0f0000"
ss <- "a0cc0vaaaabaaaabaaaabaa00bvw"
find_pattern_length <-
function(length=1,ss){
patt = mapply(function(x,y) substr(ss,x,y),
1:(nchar(ss)-length),
(length+1):nchar(ss))
res = str_locate_all(ss,unique(patt))
ll = unlist(lapply(res,length))
list(patt = patt[which.max(ll)],
rep = max(ll))
}
get_pattern_threshold <-
function(ss,threshold =3 ){
res <-
sapply(seq(threshold,nchar(ss)),find_pattern_length,ss=ss)
res[,which.max(res['rep',])]
}
some tests:
get_pattern_threshold('ff00f0f0f0f0f0f0f0f0000',5)
$patt
[1] "0f0f0"
$rep
[1] 6
> get_pattern_threshold('ff00f0f0f0f0f0f0f0f0000',2)
$patt
[1] "f0"
$rep
[1] 18
Since you want at least three repetitions, there is a nice O(n^2) approach.
For each possible pattern length d cut string into parts of length d. In case of d=5 it would be:
a0cc0
vaaaa
baaaa
baaaa
baa00
bvw
Now look at each pairs of subsequent strings A[k] and A[k+1]. If they are equal then there is a pattern of at least two repetitions. Then go further (k+2, k+3) and so on. Finally you also check if suffix of A[k-1] and prefix of A[k+n] fit (where k+n is the first string that doesn't match).
Repeat it for each d starting from some upper bound (at most n/3).
You have n/3 possible lengths, then n/d strings of length d to check for each d. It should give complexity O(n (n/d) d)= O(n^2).
Maybe not optimal but I found this cutting idea quite neat ;)
For a bounded pattern (i.e not huge) it's best I think to just create all possible substrings first and then count them. This is if the sub-patterns can overlap. If not change the step fun in the loop.
pat="a0cc0vaaaabaaaabaaaabaa00bvw"
len=nchar(pat)
thr=3
reps=floor(len/2)
# all poss strings up to half length of pattern
library(stringr)
pat=str_split(pat, "")[[1]][-1]
str.vec=vector()
for(win in 2:reps)
{
str.vec= c(str.vec, rollapply(data=pat,width=win,FUN=paste0, collapse=""))
}
# the max length string repeated more than 3 times
tbl=table(str.vec)
tbl=tbl[tbl>=3]
tbl[which.max(nchar(names(tbl)))]
aaaabaa
3
NB Whilst I'm lazy and append/grow the str.vec here in a loop, for a larger problem I'm pretty sure the actual length of str.vec is predetermined by the length of the pattern if you care to work it out.
Here is my solution, it's not optimized (build vector with patterns <- c() ; pattern <- c(patterns, x) for example) and can be improve but simpler than yours, I think.
I can't understand which pattern exactly should (I just return the max) be returned but you can adjust the code to what you want exactly.
str <- "a0cc0vaaaabaaaabaaaabaa00bvw"
findPatternMax <- function(str){
nb <- nchar(str):1
length.patt <- rev(nb)
patterns <- c()
for (i in 1:length(nb)){
for (j in 1:nb[i]){
patterns <- c(patterns, substr(str, j, j+(length.patt[i]-1)))
}
}
patt.max <- names(which(table(patterns) == max(table(patterns))))
return(patt.max)
}
findPatternMax(str)
> findPatternMax(str)
[1] "a"
EDIT :
Maybe you want the returned pattern have a min length ?
then you can add a nchar.patt parameter for example :
nchar.patt <- 2 #For a pattern of 2 char min
nb <- nb[length.patt >= nchar.patt]
length.patt <- length.patt[length.patt >= nchar.patt]
Long strings in plots aren't always attractive. What's the shortest way of making an acronym in R? E.g., "Hello world" to "HW", and preferably to have unique acronyms.
There's function abbreviate, but it just removes some letters from the phrase, instead of taking first letters of each word.
An easy way would be to use a combination of strsplit, substr, and make.unique.
Here's an example function that can be written:
makeInitials <- function(charVec) {
make.unique(vapply(strsplit(toupper(charVec), " "),
function(x) paste(substr(x, 1, 1), collapse = ""),
vector("character", 1L)))
}
Test it out:
X <- c("Hello World", "Home Work", "holidays with children", "Hello Europe")
makeInitials(X)
# [1] "HW" "HW.1" "HWC" "HE"
That said, I do think that abbreviate should suffice, if you use some of its arguments:
abbreviate(X, minlength=1)
# Hello World Home Work holidays with children Hello Europe
# "HlW" "HmW" "hwc" "HE"
Using regex you can do following. The regex pattern ((?<=\\s).|^.) looks for any letter followed by space or first letter of the string. Then we just paste resulting vectors using collapse argument to get first letter based acronym. And as Ananda suggested, if you want to make unique pass the result through make.unique.
X <- c("Hello World", "Home Work", "holidays with children")
sapply(regmatches(X, gregexpr(pattern = "((?<=\\s).|^.)", text = X, perl = T)), paste, collapse = ".")
## [1] "H.W" "H.W" "h.w.c"
# If you want to make unique
make.unique(sapply(regmatches(X, gregexpr(pattern = "((?<=\\s).|^.)", text = X, perl = T)), paste, collapse = "."))
## [1] "H.W" "H.W.1" "h.w.c"
I have one string and a cell array of strings.
str = 'actaz';
dic = {'aaccttzz', 'ac', 'zt', 'ctu', 'bdu', 'zac', 'zaz', 'aac'};
I want to obtain:
idx = [2, 3, 6, 8];
I have written a very long code that:
finds the elements with length not greater than length(str);
removes the elements with characters not included in str;
finally, for each remaining element, checks the characters one by one
Essentially, it's an almost brute force code and runs very slowly. I wonder if there is a simple way to do it fast.
NB: I have just edited the question to make clear that characters can be repeated n times if they appear n times in str. Thanks Shai for pointing it out.
You can sort the strings and then match them using regular expression. For your example the pattern will be ^a{0,2}c{0,1}t{0,1}z{0,1}$:
u = unique(str);
t = ['^' sprintf('%c{0,%d}', [u; histc(str,u)]) '$'];
s = cellfun(#sort, dic, 'uni', 0);
idx = find(~cellfun('isempty', regexp(s, t)));
I came up with this :
>> g=#(x,y) sum(x==y) <= sum(str==y);
>> h=#(t)sum(arrayfun(#(x)g(t,x),t))==length(t);
>> f=cellfun(#(x)h(x),dic);
>> find(f)
ans =
2 3 6
g & h: check if number of count of each letter in search string <= number of count in str.
f : finally use g and h for each element in dic
This question already has answers here:
How do I specify a dynamic position for the start of substring?
(4 answers)
Closed 5 years ago.
I have a list of strings in R which looks like:
WDN.TO
WDR.N
WDS.AX
WEC.AX
WEC.N
WED.TO
I want to get all the postfix of the strings starting from the character ".", the result should look like:
.TO
.N
.AX
.AX
.N
.TO
Anyone have any ideas?
Joshua's solution works fine. I'd use sub instead of gsub though. gsub is for substituting multiple occurrences of a pattern in a string - sub is for one occurrence. The pattern can be simplified a bit too:
> x <- c("WDN.TO","WDR.N","WDS.AX","WEC.AX","WEC.N","WED.TO")
> sub("^[^.]*", "", x)
[1] ".TO" ".N" ".AX" ".AX" ".N" ".TO"
...But if the strings are as regular as in the question, then simply stripping the first 3 characters should be enough:
> x <- c("WDN.TO","WDR.N","WDS.AX","WEC.AX","WEC.N","WED.TO")
> substring(x, 4)
[1] ".TO" ".N" ".AX" ".AX" ".N" ".TO"
Using gsub:
x <- c("WDN.TO","WDS.N")
# replace everything from the start of the string to the "." with "."
gsub("^.*\\.",".",x)
# [1] ".TO" ".N"
Using strsplit:
# strsplit returns a list; use sapply to get the 2nd obs of each list element
y <- sapply(strsplit(x,"\\."), `[`, 2)
# since we split on ".", we need to put it back
paste(".",y,sep="")
# [1] ".TO" ".N"
Strsplit might do it but in case the data set is too large it will show an error
subscript out of bounds
x <- c("WDN.TO","WDR.N","WDS.AX","WEC.AX","WEC.N","WED.TO")
y <- strsplit(x,".")[,2]
#output y= TO N AX AX N TO
I would like to convert the a string like be33szfuhm100060 into BESZFUHM0060.
In order to replace the small letters with capital letters I've so far used the gsub function.
test1=gsub("be","BE",test)
Is there a way to tell this function to replace the 3rd and 4th string element? If not, I would really appreciate if you could tell me another way to solve this problem. Maybe there is also a more general solution to change a string element at a certain position into a capital letter whatever the element is?
A couple of observations:
Cnverting a string to uppercase can be done with toupper, e.g.:
> toupper('be33szfuhm100060')
> [1] "BE33SZFUHM100060"
You could use substr to extract a substring by character positions and paste to concatenate strings:
> x <- 'be33szfuhm100060'
> paste(substr(x, 1, 2), substr(x, 5, nchar(x)), sep='')
[1] "beszfuhm100060"
As an alternative, if you are going to be doing this alot:
String <- function(x="") {
x <- as.character(paste(x, collapse=""))
class(x) <- c("String","character")
return(x)
}
"[.String" <- function(x,i,j,...,drop=TRUE) {
unlist(strsplit(x,""))[i]
}
"[<-.String" <- function(x,i,j,...,value) {
tmp <- x[]
tmp[i] <- String(value)
x <- String(tmp)
x
}
print.String <- function(x, ...) cat(x, "\n")
## try it out
> x <- String("be33szfuhm100060")
> x[3:4] <- character(0)
> x
beszfuhm100060
You can use substring to remove the third and fourth elements.
x <- "be33szfuhm100060"
paste(substring(x, 1, 2), substring(x, 5), sep = "")
If you know what portions of the string you want based on their position(s), use substr or substring. As I mentioned in my comment, you can use toupper to coerce characters to uppercase.
paste( toupper(substr(test,1, 2)),
toupper(substr(test,5,10)),
substr(test,12,nchar(test)),sep="")
# [1] "BESZFUHM00060"