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Other than the excellent SO answer here, and the Roxygen manual and vignette, is there any particularly thorough guide to using Roxygen?
I'm working on a guide (but it's still incomplete).
A more comprehensive set of vignettes have been added to the package, and were made available on CRAN as of version 4.0.0.
The user2010 tutorial that was presented by the roxygen authors is available here. It's not really a thorough guide, but still very useful I think.
Even with the refrences above, I still had trouble finding a good kickstarter example until I found this other
Github page.
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So if I am a newbie programmer in Julia and not sure how to really get started or keep getting stuck with language-specific things, what are my resources to help me answer my Julia related programming questions.
There's so many! See the list below:
Julia docs: https://docs.julialang.org/en/v1/
Julia Slack: https://slackinvite.julialang.org
Julia Discourse: https://discourse.julialang.org
JuliaAcademy: https://juliaacademy.com
Posting question on StackOverflow with the julia tag.
In general, the community is here to help! Please feel free to use some or all of these resources.
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There's a feature in VS Code's GitLense extension that I'm trying to find the equivalent for with Atom. It's the current line blame feature.
I have installed the Atom blame package which works, but is slow to load for large files with a large number of commits on them.
Is there anything in Atom or any package that will show blame for just the current line?
Eh, just didn't search hard enough. I just found this package which is fairly close. While it's not inline (displays via tooltip) it is fast, and has a link to the commit on the web as a bonus.
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I would like to get Facebook ad spend data into R for analysis. This is similar to data about adspend that is available from Google Analytics (metric ga:adCost).
I read about the package Rfacebook but I dont think it supports this data retrieval.
Is there any other package or way to get this data into R? I am not familiar with Java etc, so it would be a pity if this can't be done in R.
Thanks
this seems to be what you are working for:
https://github.com/cardcorp/fbRads
slides and examples are here:
https://drive.google.com/file/d/0ByjOYacj5XqBWHlwWUdJcjdrSDQ/view
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I'm trying to learn to write elegant Standard ML code by reading others' code or projects. Does anyone know of some good code/projects?
I found the MLton compiler to be a great source for learning the module system.
The Twelf theorem prover also has a lot of high quality examples.
The standardml github account has a number of projects of varying quality. Somehow my sml-ext library ended up there. I'm not sure how.
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Can someone help me with some tutorials on how I can learn to formulate optimization problems in R?
I am mainly looking for 2d optimization problems. Until now I have found a lot of info on optimization algorithms, however almost nothing on how to implement them with 1 or 2 examples.
Well, the R task guides are always a good place to start.
In addition, there was a recent article on the optimx package in R
Also, if you load up some packages listed in the task guide, then you will probably find some useful vignettes (I've learned an awful lot of stats from those vignettes over the years).