how are you. For a while I've been working for a Gynecologist building her a data base. For the project I am using Firebase and JavaScript. The database is for her to keep track of their patients and she keeps reports on each one of them. I am almost done with the job, the UI is almost finished, the core functionalities of the database (save data, delete, retreive, and update) are up and running but I am stuck in one little thing. She asked me for a way to turn those reports she keeps in the database into a format like PDF so she can print them and give them in case needed to her patients. The thing is that Ive tried with html2pdf, a git repository that works kind of clunky, and tried looking for others but I still cant find one that works correctly. So I wanted to ask you guys if you know of some alternatives. I started thinking about using EXCEl or Word document. But either way it seems quite complicated. Thank you for your time.
Best to all.
I'm producing plenty of analyses in R and utilizing the .html Markdown format to present and communicate work. Often, my manager will need to correct/add to the text which accompanies the code blocks, and has practically no interaction with the code blocks. The analyses are typically produced by myself alone, so code collaboration is a low priority.
In an ideal world, he could open up the .html and edit the text in a browser, which I understand is not possible.
Are there any simple solutions for this? I am sure this is a common problem so there must be an easy solution I am overlooking. Here are the current solutions being considered:
Use Git (but my manager wouldn't like to learn Git)
Use Jupyter Notebooks (but I would prefer to stick with R Markdown for integration with RStudio and for the reproducible templates)
Knit the Markdown as a word document with manual version control on a shared network, allow tracking of changes in the word document, and copy-and-paste over changes made to the .Rmd file
The latter is least elegant but most likely to be used at the moment. If you have any suggestions, please let me know!
Here's a solution that is tailor-made your exact situation.
Use jupytext for bi-directional lossless interoperability between jupyter notebooks and R Markdown documents!
Maybe redoc is an option for you. Haven't tried it myself and it's still experimental but it would allow you to collaborate via Word. Basically the Word document can be edited and passed back to RMarkdown with all changes. See here.
I suggest you try trackdown https://claudiozandonella.github.io/trackdown/
trackdown offers a simple answer to collaborative writing and editing of R Markdown (or Sweave) documents. Using trackdown, the local .Rmd (or .Rnw) file is uploaded as plain-text in Google Drive where, thanks to the easily readable Markdown (or LaTeX) syntax and the well-known online interface offered by Google Docs, collaborators can easily contribute to the writing and editing of the narrative part of the document. After integrating all authors’ contributions, the final document can be downloaded and rendered locally.
Moreover, you can hide code chunks setting hide_code = TRUE (they will be automatically restored when downloaded). This prevents collaborators from inadvertently making changes to the code that might corrupt the file and it allows collaborators to focus only on the narrative text ignoring code jargon.
You can also upload the actual Output (i.e., the resulting complied document) in Google Drive together with the .Rmd (or .Rnw) document. This helps collaborators to evaluate the overall layout, figures and tables and it allows them to use comments on the pdf to propose and discuss suggestions.
I am in the midst of writing some scripts to perform data analysis on large excel sheets faster than by hand. However, my company has a strict quality review system where the program used needs to be validated and secure (i.e. no one can edit it, there is proof of what code was run, etc.). So essentially I would like my code to be able to be ran by my coworkers without them being able to edit the script. I was also interested in inserting prompts that they can fill in (e.g. "Which column would you like to analyze?")
Is all of this possible? I have read a few things online about file permissions but I know that these can easily be changed by the user. I also read about obfuscators but am entirely unfamiliar with their use.
One thought I have is to use Rmarkdown as a method of displaying which lines were run for which results. However, I believe that document could be edited as well? This would also leave the issue of the script itself being able to be edited.
I want to create Jupyter notebooks for teaching, which shall be delivered in two versions:
A full “textbook” with explanations in markdown cells and example code in code cells.
As above, but with most code cells being empty such that the students have to type all the code themselves.
Obviously, I do not want to do this manually in Jupyter, so I need a way to automatically clear those code cells (exceptions are rare and can be marked somehow).
Given that notebooks are stored as sources of Python objects, I could write a simple script to directly modify those.
However, this feels like I am re-inventing the wheel instead f using some existing, dedicated method – which what I am seeking in this question.
I briefly considered using NBGrader. However, while I am quite confident that this could solve my problem, it seems overkill for this purpose and require extra effort to make things work.
Have you checked out Chris Holdgraf's nbclean?
I try to write all data analysis reports using R Markdown, because I can have a reproducible document that I can share in several output formats (Pdf, html and MS Word).
However, most of my colleagues use MS Word and they have no idea about R, Markdown, etc.
One advantage of using R Markdown is that I can generate my report in MS Word and directly share it with my colleagues.
The disadvantage is that collaboration becomes cumbersome for me, because I receive feedback on MS Word as well (typically using track changes) and I have to manually introduce those changes back into the .rmd file.
So, my question is: how can I simplify the process (i.e. make it as automatic as possible) of getting the changes in the MS Word document into the .Rmd?
Are there any tools out there that can help me out?
P.s.getting my colleagues to become R-literate is not an option :(
I haven't yet tried what I'm proposing, but here is how I plan to handle this, since I have exactly the same need. First, there are two distinct scenarios:
I am the lead author, or I am responsible for the statistical analysis: I will require all collaborators to learn and use markdown (not R Markdown, just generic markdown) and I'll instruct them not to touch any R code. I believe markdown is easy enough that anyone who is competent enough to collaborate on an article with data analysis is more than competent to learn markdown. For teaching them, the key features for people familiar with working with Microsoft Word and track changes are the following:
Basic markdown references: I would give them the core R Markdown references, which are their Pandoc Markdown documentation and their R Markdown cheat sheet.
Track changes: Collaborators would simply edit the markdown in plain text and submit their edited version. To view and reconcile differences, I would simply use a diff tool; I would find a good online one to teach my collaborators how to diff changes.
Comments between authors: I would select one of the options for markdown comments and teach my collaborators to use that when needed. The modified HTML comment (<!--- Pandoc-enhanced HTML comment -->) is the one I would probably use.
Reference management: I use Zotero, so I would use Better BibTeX for Zotero to handle references. The nice thing about this is that although I would have to handle the references myself, collaborators can directly add references to the Zotero group library. In fact, using citation keys, it should be simple for collaborators to learn how to insert references themselves into the markdown text.
I am NOT the lead author and I am NOT responsible for the statistical analysis: I would use whatever workflow the lead author uses (e.g. if the lead author uses Word with tracked changes, I'll use the same things).
I want to note that it seems that the only part that seems to be not so easy (compared to Microsoft Word normal working features) is replacing track changes with diff. I'm not aware of a tool that makes incorporating diff files as easy as how Word reconciles changes, but if such a tool exists, then the process should be more seamless.
I believe we would need to work on several packages in order to make true collaboration possible between users of Word and RMarkdown. I would be happy to collaborate with anyone interested in making this happen.
Adding a CriticMarkup plugin for RStudio. https://github.com/CriticMarkup/CriticMarkup-toolkit/
Having an R package that can scrape Word documents along with tracked changes. The officer package can already read Word documents, but not the tracked changes. It would also be extremely useful if this package could add simple RMarkdown formatting to the scrapes, e.g. for bold, subscripts and perhaps even tables to facilitate the subsequent matching of Word text to the RMarkdown file.
https://github.com/davidgohel/officer/issues/132
Write a package that can translate the scraped Tracked changes to CriticMarkup into the RMarkdown file.
Generate a key (paragraph)->(lines) that matches paragraphs scraped from Word (without any of the tracked changes) to lines in the RMarkdown. The problem is that we don't know what was generated using code, and what was directly written as Rmd. The first step would be to find lines in the RMarkdown file that should form paragraphs (exclude R chunks, but not inline R). Then, ensuring the order remains the same, compare these lines (remove newlines) to paragraphs scraped from the Word document, using a regexp symbol for "any char, any length" in the place of inline r chunks. Next, split paragraphs with inline chunks as into sub-paragraphs in order to be able to apply tracked changes and comments to either the inline code, before, or after the inline chunk more easily. Finally, the paragraphs that could not be matched were likely generated within code chunks and should be matched to the appropriate code chunks, determined from the order of the paragraphs.
Use the generated key, apply tracked changes (as CritcMarkup) to the RMarkdwown file. Any changes made to code chunks should be reported as a CrticMarkup comment around that code chunk (or group of code chunks if there is no markdown in between chunks).
I suggest you try trackdown https://claudiozandonella.github.io/trackdown/
trackdown offers a simple answer to collaborative writing and editing of R Markdown (or Sweave) documents. Using trackdown, the local .Rmd (or .Rnw) file is uploaded as plain-text in Google Drive where, thanks to the easily readable Markdown (or LaTeX) syntax and the well-known online interface offered by Google Docs, collaborators can easily contribute to the writing and editing of the narrative part of the document. After integrating all authors’ contributions, the final document can be downloaded and rendered locally.
Using Google Docs, anyone can collaborate on the document as no programming experience is required, they only have to focus on the narrative text ignoring code jargon.
Moreover, you can hide code chunks setting hide_code = TRUE (they will be automatically restored when downloaded). This prevents collaborators from inadvertently making changes to the code that might corrupt the file and it allows collaborators to focus only on the narrative text ignoring code jargon.
You can also upload the actual Output (i.e., the resulting complied document) in Google Drive together with the .Rmd (or .Rnw) document. This helps collaborators to evaluate the overall layout, figures and tables and it allows them to use comments on the pdf to propose and discuss suggestions.
I know this is an old post, but for future askers, there is now a package available that can do (mostly) this:
The {redoc} package can output to Word, and by storing the R code internally within the Word document, it can also dedoc() a Word file back into RMarkdown. It uses the Critic Markup syntax discussed in another answer.