"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.