[R] Discovering patterns in textual strings

[Bert Gunter]

"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 <reichmanj using 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.4567 using gmail.com>
> Sent: Friday, May 4, 2018 5:41 PM
> To: reichmanj using sbcglobal.net
> Cc: R-help <R-help using 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 <reichmanj using 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 using 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.
>
>

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