[R] Help request: Parsing docx files for key words and appending to a spreadsheet

[CALUM POLWART]

textreadr would be the obvious approach.

When you say it is depreciated do you mean it's not available on cran?
Sometimes maintaining a package on cran in just a pain in the ass.

devtools::install_github("trinker/textreadr")


Should let you install it.

In theory docx files are actually just zip files (you can unzip them) and
you may find there is then a specific file in the zip that is readable with
on of R's General text file readers.

Alternatively, read_docx from:
https://www.rdocumentation.org/packages/qdapTools

May be worth a look.

What platform are you on. Certainly options to command line convert files
to txt and do from there.


On Fri, 29 Dec 2023, 18:25 Roy Mendelssohn - NOAA Federal via R-help, <
r-help using r-project.org> wrote:

> Hi Andy:
>
> I don’t have an answer but I do have what I hope is some friendly advice.
> Generally the more information you can provide,  the more likely you will
> get help that is useful.  In your case you say that you tried several
> packages and they didn’t do what you wanted.  Providing that code,  as well
> as why they didn’t do what you wanted (be specific)  would greatly
> facilitate things.
>
> Happy new year,
>
> -Roy
>
>
> > On Dec 29, 2023, at 10:14 AM, Andy <phaedrusv using gmail.com> wrote:
> >
> > Hello
> >
> > I am trying to work through a problem, but feel like I've gone down a
> rabbit hole. I'd very much appreciate any help.
> >
> > The task: I have several directories of multiple (some directories, up
> to 2,500+) *.docx files (newspaper articles downloaded from Lexis+) that I
> want to iterate through to append to a spreadsheet only those articles that
> satisfy a condition (i.e., a specific keyword is present for >= 50%
> coverage of the subject matter). Lexis+ has a very specific structure and
> keywords are given in the row "Subject".
> >
> > I'd like to be able to accomplish the following:
> >
> > (1) Append the title, the month, the author, the number of words, and
> page number(s) to a spreadsheet
> >
> > (2) Read each article and extract keywords (in the docs, these are
> listed in 'Subject' section as a list of keywords with a percentage showing
> the extent to which the keyword features in the article (e.g., FAST FASHION
> (72%)) and to append the keyword and the % coverage to the same row in the
> spreadsheet. However, I want to ensure that the keyword coverage meets the
> threshold of >= 50%; if not, then pass onto the next article in the
> directory. Rinse and repeat for the entire directory.
> >
> > So far, I've tried working through some Stack Overflow-based solutions,
> but most seem to use the textreadr package, which is now deprecated; others
> use either the officer or the officedown packages. However, these packages
> don't appear to do what I want the program to do, at least not in any of
> the examples I have found, nor in the vignettes and relevant package
> manuals I've looked at.
> >
> > The first point is, is what I am intending to do even possible using R?
> If it is, then where do I start with this? If these docx files were
> converted to UTF-8 plain text, would that make the task easier?
> >
> > I am not a confident coder, and am really only just getting my head
> around R so appreciate a steep learning curve ahead, but of course, I don't
> know what I don't know, so any pointers in the right direction would be a
> big help.
> >
> > Many thanks in anticipation
> >
> > Andy
> >
> > ______________________________________________
> > 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.
>
> ______________________________________________
> 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.
>

	[[alternative HTML version deleted]]