I have a collection of .pdf files with comments that were added in Adobe Acrobat. I would like to be able to analyze these comments, but I'm kind of stuck on extracting them. I've looked at the pdftools package, but it seems to only be able to extract the text and not the comments. Is there a method available for extracting the comments within R?
PyMuPDF (https://pymupdf.readthedocs.io/en/latest/) is the only python library I have found working.
Installation in Debian/Ubuntu-based distributions:
apt-get install python3-fitz
Script:
import fitz
doc = fitz.open("example.pdf")
for i in range(doc.pageCount):
page = doc[i]
for annot in page.annots():
print(annot.info["content"])
Did you try PoDoFo or another OpenSource tool that can access the PDF elements?
You can also look at Extracting PDF annotations/comments here on stackoverflow if you will do little programming
Screenshot of how >> Export the comments as an Excel file, then import it into R?
Eg: in PDF-X-change Editor, go to comment > summarize comments > export into whatever format you want. Similar in Adobe.
Related
My pdf looks like:
How do I make it show the actual pdf?
I loaded pdf-view from https://atom.io/packages/pdf-view and now when I open a pdf file i get it shown onscreen as a it's meant to be displayed. There is also a package named pdf-view-Plus which claims to be better than pdf-view. Just load the package and you should be ready to go.
Atom on his own cant read the PDF document as it is a binary file, in order to view the formatted document you must use a Atom package like https://atom.io/packages/pdf-view
You would need to install some other extension as Atom can't read PDFs on it's own. You could use something such as https://atom.io/packages/pdf-view.
I have a 174603 rows and 178 column dataframe, which I'm importing to Excel using openxlsx::saveWorkbook, (Using this package to obtain the aforementioned format of cells, with colors, header styles and so on). But the process is extremely slow, (depending on the amount of memory used by the machine it can take from 7 to 17 minutes!!) and I need a way to reduce this significantly (Doesn't need to be seconds, but anything bellow 5 min would be OK)
I've already searched other questions but they all seem to focus either in exporting to R (I have no problem with this) or writing non-formatted files to R (using write.csv and other options of the like)
Apparently I can't use xlsx package because of the settings on my computer (industrial computer, Check comments on This question)
Any suggestions regarding packages or other functionalities inside this package to make this run faster would be highly appreciated.
This question has some time ,but I had the same problem as you and came up with a solution worth mentioning.
There is package called writexl that has implemented a way to export a data frame to Excel using the C library libxlsxwriter. You can export to excel using the next code:
library(writexl)
writexl::write_xlsx(df, "Excel.xlsx",format_headers = TRUE)
The parameter format_headers only apply centered and bold titles, but I had edited the C code of the its source in github writexl library made by ropensci.
You can download it or clone it. Inside src folder you can edit write_xlsx.c file.
For example in the part that he is inserting the header format
//how to format headers (bold + center)
lxw_format * title = workbook_add_format(workbook);
format_set_bold(title);
format_set_align(title, LXW_ALIGN_CENTER);
you can add this lines to add background color to the header
format_set_pattern (title, LXW_PATTERN_SOLID);
format_set_bg_color(title, 0x8DC4E4);
There are lots of formating you can do searching in the libxlsxwriter library
When you have finished editing that file and given you have the source code in a folder called writexl, you can build and install the edited package by
shell("R CMD build writexl")
install.packages("writexl_1.2.tar.gz", repos = NULL)
Exporting again using the first chunk of code will generate the Excel with formats and faster than any other library I know about.
Hope this helps.
Have you tried ;
write.table(GroupsAlldata, file = 'Groupsalldata.txt')
in order to obtain it in txt format.
Then on Excel, you can simply transfer you can 'text to column' to put your data into a table
good luck
I have been practicing with tabulizer package in R and have following problem. Unfortunately I can't offer reproducible example, as pdf is firms property, but I will describe problem in detail.
I'm trying to read PDF that has start and end date in upperright corner. When I open PDF they look normal
Start: 01-Mar-2018
End: 31-Mar-2018
Now the fun part. When I highlight them and use Ctrl+C to copy them here is result when pasted to R.
:tttt: 11-rrr-8118
tt:: 11-rrr-8118
This is exactly same kind of nonsense that extract_text(path, pages=1) will give. A lot of t::ttttt:ttt... My question is that is there some security in this PDF or do I just need to figure out correct encoding or because this PDF is automatically created from system, there is some weird notation to everything?
I figured it out. This PDF is mainly created by metadata (didn't know) and great tool in R for accessing metadata in PDFs is pdftools.
library(pdftools)
pdf_info(path.pdf)
and you can wrangle out all the important metadata bits.
I would like to perform a line-by-line review of code written using RStudio.
I have two questions:
How do I export the script file as a PDF/text file?
How do I make sure that the exported script file includes the line numbers?
Thanks!
** Update: Considering that I wasn't trying to write a report straight from the R/RStudio interface, I realized I could easily open and print the code using Notepad ++. So, here's to remembering a software that most folks probably use for their coding anyway.
I found the answer to a similar question that I had for writing a script to a text file here https://statisticsglobe.com/r-save-all-console-input-output-to-file and wanted to share for others facing the same dilemma. Unfortunately, this method does not write out the line numbers though.
# Writing currently opened R script to file
fout = "filpath/filename.txt"
cat(readChar(rstudioapi::getSourceEditorContext()$path,
file.info(rstudioapi::getSourceEditorContext()$path)$size), file = fout)
Have you ever heard about Knitr?, and also look at this question.
I am new to R and have worked for a while as follows. I have the code writen in a word document, then I copy and paste the document with the code into R as to have the code run which works fine, however when the code is long (hundred pages) it takes a significant amount of time in R to start making the code run. This seems rather not a very effective working procedure and I am sure there are other forms to compile the R code.
On another hand one of then that comes to my mind is to import the content of word into R which I am unsure how to do. Have tried with read.table but it does not work, have look on internet as to how to import data, however most explanations are all for data tables etc or internet files in the form of data tables and similar. I have tried saving the document into csv. however word does not include csv have tried with Rich text format and XML package but again the instructions from the packages are for importing tables and similars. I am wondering if there is an effective way for R to import a word document as is in the word document.
Thank you
It's hard to say what the easiest solution would be, without examining the word document. Assuming it only contains code and nothing else, it should be pretty easy to convert it all to plain text from within Word. You can do that by going to File -> Save As, and use 'plain text' under 'Save as type'.
Then edit the filename extension to .R from .txt, download a proper text editor (I can recommend RStudio for R), and open your code in it. Then you will be able to run the code from inside the editor without using copy / paste.
No, read table won't do it.
Microsoft Word has its own format, which includes a lot of meta data over and above the text you enter into it. You'll need a reader/parser that understands the Word format.
A Java developer would use a library like Apache POI to read and parse it into word tokens and n-grams.
Look for Natural Language Processing tools, like this R module:
http://cran.r-project.org/web/views/NaturalLanguageProcessing.html