I read about regex and came accross word boundaries. I found a question that is about the difference between \b and \B. Using the code from this question does not give the expected output. Here:
grep("\\bcat\\b", "The cat scattered his food all over the room.", value= TRUE)
# I expect "cat" but it returns the whole string.
grep("\\B-\\B", "Please enter the nine-digit id as it appears on your color - coded pass-key.", value= TRUE)
# I expect "-" but it returns the whole string.
I use the code as described in the question but with two backslashes as suggested here. Using one backslash does not work either. What am I doing wrong?
You can to use regexpr and regmatches to get the match. grep gives where it hits. You can also use sub.
x <- "The cat scattered his food all over the room."
regmatches(x, regexpr("\\bcat\\b", x))
#[1] "cat"
sub(".*(\\bcat\\b).*", "\\1", x)
#[1] "cat"
x <- "Please enter the nine-digit id as it appears on your color - coded pass-key."
regmatches(x, regexpr("\\B-\\B", x))
#[1] "-"
sub(".*(\\B-\\B).*", "\\1", x)
#[1] "-"
For more than 1 match use gregexpr:
x <- "1abc2"
regmatches(x, gregexpr("[0-9]", x))
#[[1]]
#[1] "1" "2"
grepreturns the whole string because it just looks to see if the match is present in the string. If you want to extract cat, you need to use other functions such as str_extractfrom package stringr:
str_extract("The cat scattered his food all over the room.", "\\bcat\\b")
[1] "cat"
The difference betweeen band Bis that bmarks word boundaries whereas Bis its negation. That is, \\bcat\\b matches only if cat is separated by white space whereas \\Bcat\\B matches only if cat is inside a word. For example:
str_extract_all("The forgot his education and scattered his food all over the room.", "\\Bcat\\B")
[[1]]
[1] "cat" "cat"
These two matches are from education and scattered.
Related
In this sample text:
turns <- tolower(c("Does him good to stir him up now and again .",
"When , when I see him he w's on the settees .",
"Yes it 's been eery for a long time .",
"blissful timing , indeed it was "))
I'd like to extract all words that contain the letters y and e no matter what position or combination, namely yesand eery, using str_extract from stringr:
This regex, in which I determine that y occur immediately before e, matches not surprisingly only yes but not eery:
unlist(str_extract_all(turns, "\\b([a-z]+)?ye([a-z]+)?\\b"))
[1] "yes"
Putting yand e into a character class doesn't get me the desired result either in that all words either with y or with e are matched:
unlist(str_extract_all(turns, "\\b([a-z]+)?[ye]([a-z]+)?\\b"))
[1] "does" "when" "when" "see" "he" "the" "settees" "yes" "been" "eery" "time" "indeed"
So what is the right solution?
You may use both base R and stringr approaches:
stringr::str_extract_all(turns, "\\b(?=\\p{L}*y)(?=\\p{L}*e)\\p{L}+\\b")
regmatches(turns, gregexpr("\\b(?=\\p{L}*y)(?=\\p{L}*e)\\p{L}+\\b", turns, perl=TRUE))
Or, without turning the strings to lower case, you may use a case insensitive matching with (?i):
stringr::str_extract_all(turns, "(?i)\\b(?=\\p{L}*y)(?=\\p{L}*e)\\p{L}+\\b")
regmatches(turns, gregexpr("\\b(?=\\p{L}*y)(?=\\p{L}*e)\\p{L}+\\b", turns, perl=TRUE, ignore.case=TRUE))
See the regex demo and the R demo. Also, if you want to make it a tiny bit more efficient, you may use principle of contrast in the lookahead patterns: match any letters but y in the first and all letters but the e in the second using character class substraction:
stringr::str_extract_all(turns, "(?i)\\b(?=[\\p{L}--[y]]*y)(?=[\\p{L}--[e]]*e)\\p{L}+\\b")
Details
(?i) - case insensitive modifier
\b - word boundary
(?=\p{L}*y) - after 0 or more Unicode letters, there must be y ([\p{L}--[y]]* matches any 0 or more letters but y up to the first y)
(?=\p{L}*e) - after 0 or more Unicode letters, there must be e ([\p{L}--[e]]* matches any 0 or more letters but e up to the first e)
\p{L}+ - 1 or more Unicode letters
\b - word boundary
In case there is no urgent need to use stringr::str_extract you can get words containing the letters y and e in base with strsplit and grepl like:
tt <- unlist(strsplit(turns, " "))
tt[grepl("y", tt) & grepl("e", tt)]
#[1] "yes" "eery"
In case you have letter chunks between words:
turns <- c("yes no ay ae 012y345e year.")
tt <- regmatches(turns, gregexpr("\\b[[:alpha:]]+\\b", turns))[[1]]
tt[grepl("y", tt) & grepl("e", tt)]
#[1] "yes" "year"
(In R) How to split words by title case in a string like "WeLiveInCA" into "We Live In CA" without splitting abbreviations?
I know how to split the string at every uppercase letter, but doing that would split initialisms/abbreviations, like CA or USSR or even U.S.A. and I need to preserve those.
So I'm thinking some type of logical like if a word in a string isn't an initialism then split the word with a space where a lowercase character is followed by an uppercase character.
My snippet of code below splits words with spaces by capital letters, but it breaks initialisms like CA becomes C A undesirably.
s <- "WeLiveInCA"
trimws(gsub('([[:upper:]])', ' \\1', s))
# "We Live In C A"
or another example...
s <- c("IDon'tEatKittensFYI", "YouKnowYourABCs")
trimws(gsub('([[:upper:]])', ' \\1', s))
# "I Don't Eat Kittens F Y I" "You Know Your A B Cs"
The results I'd want would be:
"We Live In CA"
#
"I Don't Eat Kittens FYI" "You Know Your ABCs"
But this needs to be widely applicable (not just for my example)
Try with base R gregexpr/regmatches.
s <- c("WeLiveInCA", "IDon'tEatKittensFYI", "YouKnowYourABCs")
regmatches(s, gregexpr('[[:upper:]]+[^[:upper:]]*', s))
#[[1]]
#[1] "We" "Live" "In" "CA"
#
#[[2]]
#[1] "IDon't" "Eat" "Kittens" "FYI"
#
#[[3]]
#[1] "You" "Know" "Your" "ABCs"
Explanation.
[[:upper:]]+ matches one or more upper case letters;
[^[:upper:]]* matches zero or more occurrences of anything but upper case letters.
In sequence these two regular expressions match words starting with upper case letter(s) followed by something else.
I'm trying to extract twitter handles from tweets using R's stringr package. For example, suppose I want to get all words in a vector that begin with "A". I can do this like so
library(stringr)
# Get all words that begin with "A"
str_extract_all(c("hAi", "hi Ahello Ame"), "(?<=\\b)A[^\\s]+")
[[1]]
character(0)
[[2]]
[1] "Ahello" "Ame"
Great. Now let's try the same thing using "#" instead of "A"
str_extract_all(c("h#i", "hi #hello #me"), "(?<=\\b)\\#[^\\s]+")
[[1]]
[1] "#i"
[[2]]
character(0)
Why does this example give the opposite result that I was expecting and how can I fix it?
It looks like you probably mean
str_extract_all(c("h#i", "hi #hello #me", "#twitter"), "(?<=^|\\s)#[^\\s]+")
# [[1]]
# character(0)
# [[2]]
# [1] "#hello" "#me"
# [[3]]
# [1] "#twitter"
The \b in a regular expression is a boundary and it occurs "Between two characters in the string, where one is a word character and the other is not a word character." see here. Since an space and "#" are both non-word characters, there is no boundary before the "#".
With this revision you match either the start of the string or values that come after spaces.
A couple of things about your regex:
(?<=\b) is the same as \b because a word boundary is already a zero width assertion
\# is the same as #, as # is not a special regex metacharacter and you do not have to escape it
[^\s]+ is the same as \S+, almost all shorthand character classes have their negated counterparts in regex.
So, your regex, \b#\S+, matches #i in h#i because there is a word boundary between h (a letter, a word char) and # (a non-word char, not a letter, digit or underscore). Check this regex debugger.
\b is an ambiguous pattern whose meaning depends on the regex context. In your case, you might want to use \B, a non-word boundary, that is, \B#\S+, and it will match # that are either preceded with a non-word char or at the start of the string.
x <- c("h#i", "hi #hello #me")
regmatches(x, gregexpr("\\B#\\S+", x))
## => [[1]]
## character(0)
##
## [[2]]
## [1] "#hello" "#me"
See the regex demo.
If you want to get rid of this \b/\B ambiguity, use unambiguous word boundaries using lookarounds with stringr methods or base R regex functions with perl=TRUE argument:
regmatches(x, gregexpr("(?<!\\w)#\\S+", x, perl=TRUE))
regmatches(x, gregexpr("(?<!\\S)#\\S+", x, perl=TRUE))
where:
(?<!\w) - an unambiguous starting word boundary - is a negative lookbehind that makes sure there is a non-word char immediately to the left of the current location or start of string
(?<!\S) - a whitespace starting word boundary - is a negative lookbehind that makes sure there is a whitespace char immediately to the left of the current location or start of string.
See this regex demo and another regex demo here.
Note that the corresponding right hand boundaries are (?!\w) and (?!\S).
The answer above should suffice. This will remove the # symbol in case you are trying to get the users' names only.
str_extract_all(c("#tweeter tweet", "h#is", "tweet #tweeter2"), "(?<=\\B\\#)[^\\s]+")
[[1]]
[1] "tweeter"
[[2]]
character(0)
[[3]]
[1] "tweeter2"
While I am no expert with regex, it seems like the issue may be that the # symbol does not correspond to a word character, and thus matching the empty string at the beginning of a word (\\b) does not work because there is no empty string when # is preceding the word.
Here are two great regex resources in case you hadn't seen them:
stat545
Stringr's Regex page, also available as a vignette:
vignette("regular-expressions", package = "stringr")
i would like to get the count times that in a given string a word start with the letter given.
For example, in that phrase: "that pattern is great but pigs likes milk"
if i want to find the number of words starting with "g" there is only 1 "great", but right now i get 2 "great" and "pigs".
this is the code i use:
x <- "that pattern is great but pogintless"
sapply(regmatches(x, gregexpr("g", x)), length)
We need either a space or word boundary to avoid th letter from matching to characters other than the start of the word. In addition, it may be better to use ignore.case = TRUE as some words may begin with uppercase
lengths(regmatches(x, gregexpr("\\bg", x, ignore.case = TRUE)))
The above can be wrapped as a function
fLength <- function(str1, pat){
lengths(regmatches(str1, gregexpr(paste0("\\b", pat), str1, ignore.case = TRUE)))
}
fLength(x, "g")
#[1] 1
You can also do it with stringr library
library(stringr)
str_count(str_split(x," "),"\\bg")
Split the regex by space if the group of words is not matched.
If group of words is matched then keep them as it is.
text <- c('considerate and helpful','not bad at all','this is helpful')
pattern <- c('considerate and helpful','not bad')
Output :
considerate and helpful, not bad, at, all, this, is, helpful
Thank you for the help!
Of course, just put the words in front of \w+:
library("stringr")
text <- c('considerate and helpful','not bad at all','this is helpful')
parts <- str_extract_all(text, "considerate and helpful|not bad|\\w+")
parts
Which yields
[[1]]
[1] "considerate and helpful"
[[2]]
[1] "not bad" "at" "all"
[[3]]
[1] "this" "is" "helpful"
It does not split on whitespaces but rather extracts the "words".