Here is a small pack of some engaging news from R’s world gathered from Twitter in the last week.
http://www.storybench.org/convert-google-doc-rmarkdown-publish-github-pages/ - title speaks for itself - it shows how to convert GoogleDocs to Rmarkdown format.
http://blog.jumpingrivers.com/posts/2017/speed_package_installation/ - in short - options(Ncpus = 6) - allows to use multicores in install.packages, which can significantly speed up the packages’ installation process.
https://www.tidyverse.org/articles/2017/11/withr-2.1.0/ - allows a user to call code in a special environment with some global variables alerted. I think that the first example of the usage of with_par shows the principle quite well.
https://github.com/kcf-jackson/jsReact/ - integrate JS with R. It’s worth to follow that link and check the GIFs.
http://forcats.tidyverse.org/ - simplify the usage of the factor type in R.
- http://ropenscilabs.github.io/r-docker-tutorial/ - another tutorial about using Docker with R. I think that maybe I too often put articles about Docker here (it’s not R specific!), but I believe that it’s significant topic. With Docker, you can implement things more efficiently, without worrying about system dependencies on your clients’ machines (they only need to have Docker client installed). You can also use https://www.shinyproxy.io/ to deploy shiny apps easily.
https://romain.rbind.io/blog/2017/10/24/fast-counting-na/ - technical post about memory representation of the NA values, and how it can be used to count the number of NAs a little bit faster.
- https://blog.codecentric.de/en/2017/11/explore-predictive-maintenance-flexdashboard/ - how to create an app to summarize the results of the machine learning model (https://shiring.shinyapps.io/fraud_example_dashboard/ - direct link to the app).