Jeff: The previous solution I sent you was hugely inefficient and frankly kind of stupid. Here is a much better and simpler solution.
> z <- c("abc", "abc_def", "abc.def", "abc def", "abcd_ef", "abcd", "e","f") ## Create vector of patterns of same length as z, many of which are repeated > pats <- sub("^(.+)[. _].*","\\1",z) ## Now can use tapply() to get indices if desired ## Note that the patterns label the groups > tapply(seq_along(z),pats,I) $abc [1] 1 2 3 4 $abcd [1] 5 6 $e [1] 7 $f [1] 8 No need to reply. Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Sat, May 5, 2018 at 12:14 AM, Bert Gunter <bgunter.4...@gmail.com> wrote: > "Does that help?" > > No. I am not your private consultant. You need to reply to the list, which > I have cc'ed here, not just me. > > I am still somewhat confused by your specifications, but others may not > be. Part of my confusion stems from your failure to provide a reproducible > example (see e.g. the posting guide linked below). For example, I cannot > tell from your text whether the Abc and Bce strings contain one or more > spaces at the end. I shall assume they may but need not. > > Anyway, here is a reproducible example and solution that assumes that the > substrings/patterns of interest to you occur at the beginning of the > strings and may or may not be followed by one of "." "_" or " "(space) and > then possibly further text which should be ignored. Assuming that you are > familiar with regular expressions, maybe this will help to get you started > even if I have misunderstood your specifications. If you aren't familiar > with regex's, maybe the stringr package may provide a gentler interface > than using R's raw regex functionality. Or maybe someone else can suggest a > better approach (which is another reason why you should reply to the list, > not just me). > > z <- c("abc", > "abc_def", > "abc.def", > "abc def", > "abcd_ef", > "abcd", > "e","f") > > pats <- unique(sub("^(.+)[. _]+.*", "\\1", z)) > ## gives: > > pats > [1] "abc" "abcd" "e" "f" > > > This gives you the four separate patterns that you could then use to group > your records, perhaps by: > > > lapply(pats,function(x)grep(paste0("^", x,"([_. ]|$)"), z)) > [[1]] > [1] 1 2 3 4 > > [[2]] > [1] 5 6 > > [[3]] > [1] 7 > > [[4]] > [1] 8 > > That is, indices 1-4 in z are the first group; 5 and 6 are the second; etc. > > > > Cheers, > Bert > > Bert Gunter > > "The trouble with having an open mind is that people keep coming along and > sticking things into it." > -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) > > On Fri, May 4, 2018 at 9:00 PM, Jeff Reichman <reichm...@sbcglobal.net> > wrote: > >> Bert >> >> Thank you for the link. Figured there might be something >> >> Regarding your questions >> >> This is from a large 53 Billion records. The column in question are >> AdNames (Real Time Bidding data) >> >> #1. Generally yes, but not always >> >> #2 Separators could be underscores (_) or dots (.) as in 1.2.3_ABC ...... >> >> #3 Yes. So there could be Abc 123 could be a matching string >> >> This would not be considered a match ... >> abc_something >> this.is_a long stringwithabcinthemiddle >> >> The sequence(s) are always are at the beginning (or so it appears). Out >> of the 54 billion records I am able to pull (SparkR sql) 948,679 unique >> strings. It is from these unique strings that I (if possible) want to >> identify the "key" strings. >> >> 1. Abc_1232.niok7j9hd >> 2. Abc >> 3. Abc.2#348hfk2.njilo >> 4. Abc.2 >> 5. Abc.7 >> 6. BAdfr_kajdhf98#kjsdh >> 7. BAdrf_gofer >> 948679 .... >> >> >> So I may have a thousand individuals strings all of which have Abc as a >> common string, or Badrf. So I am looking to pull "Abc," "BAdrf", etc. So >> then I can go back and restructure the data to show that any record with >> Abc_1232.niok7j9hd if part of the Abc "Group," or Family ??? >> >> Does that help >> >> Jeff >> >> -----Original Message----- >> From: Bert Gunter <bgunter.4...@gmail.com> >> Sent: Friday, May 4, 2018 5:41 PM >> To: reichm...@sbcglobal.net >> Cc: R-help <R-help@r-project.org> >> Subject: Re: [R] Discovering patterns in textual strings >> >> The answer is, of course, using regular expressions and/or libraries >> therefor. However, I do not think you have defined your problem >> sufficiently. Some questions I have: >> >> 1. Do possible patterns to be matched always appear at the beginning of >> your strings? >> >> 2. Always together between specified separators ("_" in your example); >> or one of several specified separators; or otherwise? >> >> 3. Do spaces or other nonprinting characters occur in your strings? >> >> e.g. would >> >> abc_something >> this.is_a long stringwithabcinthemiddle >> >> be considered matching? >> There are undoubtedly other possibilities that I've missed. >> >> >> >> You may also find it useful to check this "task view" out for >> possibilities: >> https://cran.r-project.org/web/views/NaturalLanguageProcessing.html >> >> Cheers, >> Bert >> >> >> Bert Gunter >> >> "The trouble with having an open mind is that people keep coming along >> and sticking things into it." >> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) >> >> >> On Fri, May 4, 2018 at 3:25 PM, Jeff Reichman <reichm...@sbcglobal.net> >> wrote: >> > R Help Forum >> > >> > >> > >> > Is there a R library (or a way) that I can extract unique character >> > strings, or repeating patterns in textual strings. Say for example I >> > have the following records: >> > >> > >> > >> > Abc_1234_kjhksh_276 >> > >> > Abc >> > >> > Abc_1234_lakdofyo_324 >> > >> > Bce_876_skdhk_*&^%*& >> > >> > Bce >> > >> > Bce_454 >> > >> > >> > >> > And I would like to see the following results >> > >> > Abc >> > >> > Abc_1234 >> > >> > Bce >> > >> > >> > >> > >> > >> > Jeff Reichman >> > >> > >> > [[alternative HTML version deleted]] >> > >> > ______________________________________________ >> > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see >> > https://stat.ethz.ch/mailman/listinfo/r-help >> > PLEASE do read the posting guide >> > http://www.R-project.org/posting-guide.html >> > and provide commented, minimal, self-contained, reproducible code. >> >> > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.