poorman VS awesome-R

You might find the poorman package interesting: https://github.com/nathaneastwood/poorman

It's true that their packages are heavy on dependencies, and if that is a concern, you have alternatives: - poorman: no dependencies, same syntax as dplyr, but only includes basic verbs. - datawizard: low dependencies, slightly different syntax, has base-R implementations of most of dplyr / tidyr functions, plus some other goodies likes scaling, mean-centering, rank transforming, ... - And of course, data.table: 0 dependencies, ultra-fast (everything is written in optimized C under the hood), can manipulate much bigger data than the Tidyverse, and can do everything the tidyverse can when it comes to data wrangling (however, sometimes the tidyverse has convenience functions that make some operations shorter than with data.table). The downside is that data.table's syntax requires more efforts to learn / is less intuitive to read for neophytes.

Won't cover newer ones, but Awesome R has a good list as does this site.

First we looked for a project to play with. Checked the r projects, then looked at the awesome-R list and found r-yaml. We thought a library dealing with YAML files will be simple to install and test.

I can't really decipher what exactly do you want/mean but here you go: https://github.com/qinwf/awesome-R