some updates

03_data_science_practice.Rmd

@@ -120,6 +120,12 @@ Emily Robinson, [Red Flags in Data Science Interviews](http://hookedondata.org/R
 
 ## R packages supporting robust workflow
 
+[**R project workflows**](https://github.com/jdblischak/r-project-workflows#readme): a GitHub repository compiled by jdblichak
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+* "This is a non-exhaustive list of R code that assists with the workflow of R projects. Some are R packages, others are Git repositories meant to be used as templates, and some are guides. Here "workflow" is broadly defined, and incldues one or more of the following: file organization, dependency management (e.g. like GNU Make), or report generation."
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 ### `{janitor}`
 
 [{janitor}](sfirke.github.io/janitor/index.html) -- "has simple functions for examining and cleaning dirty data. It was built with beginning and intermediate R users in mind and is optimized for user-friendliness. Advanced R users can already do everything covered here, but with janitor they can do it faster and save their thinking for the fun stuff."

89_RMarkdown.Rmd

@@ -111,8 +111,7 @@ Yihui Xie, [bookdown: Authoring Books and Technical Documents with R Markdown](h
 
 For academic conference-style posters.
 
-[github page](https://github.com/brentthorne/posterdown/blob/master/README.md)
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+[github page](https://github.com/brentthorne/posterdown#readme)
 
 <blockquote class="twitter-tweet" data-lang="en"><p lang="en" dir="ltr">My hyper-minimalist attempt at a “1-minute research poster.” (Main finding can be read in ~10 seconds, more detail in sidebar can be read in ~45seconds). <a href="https://twitter.com/hashtag/posterposter?src=hash&amp;ref_src=twsrc%5Etfw">#posterposter</a> (1/2) <a href="https://t.co/VcCcZwK9Xd">pic.twitter.com/VcCcZwK9Xd</a></p>&mdash; Mike Morrison (@mikemorrison) <a href="https://twitter.com/mikemorrison/status/1132687984938106882?ref_src=twsrc%5Etfw">May 26, 2019</a></blockquote>