Most Useful R Packages for Data Science

Ever wondered what are the most useful R packages for doing Data Science? Don’t have to wonder anymore, RStudio has collated a list of most useful R packages in its github repository titled “RStartHere“.

How did R Studio come up with the list for doing Data Science? RStudio used the iconic Data Science work flow image and identified R packages useful for each of the steps.

And made a call on whether the R package is useful by following criteria.

The package

runs fast, with few errors.

has an intuitive syntax that is easy to remember.

plays well with other packages; you do not need to munge your data into new forms to use the package.

is widely used and recommended by its users.

has a development website, or series of vignettes

.is developed in the open.

uses tests to ensure that it will be stable and bug free well into the future.

is stable and available from CRAN, or we are personally involved with the package and committed to its development.

The R Packages list contains awesome packages, not just the ones from RStudio’s tidyverse. And defnitely a few you may not have heard of. Enough describing, check out the awesome list of R packages for doing Data Science yourself.

https://github.com/rstudio/RStartHere

You can also have a look at the list of popular R packages that did not make it to the most useful for data science, either it is not a data science tool (like RCurl) or did not meet the above criteria, like MASS which has no development website and no vignette.