R packages - Eran Raviv

R Packages Download Stats

Blog, Miscellaneous, RPosted on 05/26/2022

One big advantage of using open-source tools is the fantastic ecosystems that typically accompany them. Being able to tap into a massive open-source community, by way of downloading freely available code is decidedly useful. But, yes, there are downsides to downloads.

For one, there are too many packages out there. There are imperfect duplicates. You can easily end up downloading inferior code/package/module compared to existing other. Second, there is a matter of security. I myself try to refrain from downloading relatively new code, not yet tried-and-true. How do we know if a package is solid?

R tips and tricks – the pipe operator

Blog, Code, RPosted on 11/13/2017

The R language has improved over the years. Amidst numerous splendid augmentations, the magrittr package by Stefan Milton Bache allows us to write more readable code. It uses an ingenious piping convention which will be explained shortly. This post talks about when to use those pipes, and when to avoid using pipes in your code. I am all about ~~that bass~~ readability, but I am also about speed. Use the pipe operator, but watch the tradeoff.

R tips and tricks – Package Dependencies

Blog, CodePosted on 07/27/2017

In this post about the most popular machine learning R packages I showed the incredible- exponential growth displayed by R software, measured by the number of package downloads. Here is another graph which shows a more linear growth in R (and an impressive growth in python) as measured by % of question posted in stack overflow

R tips and tricks – Faster Loops

Blog, Code, RPosted on 12/12/2016

Insert or bind?

This is the first in a series of planned posts, sharing some R tips and tricks. I hope to cover topics which are not easily found elsewhere. This post has to do with loops in R. There are two ways to save values when looping:
1. You can predefine a vector and fill it, or
2. you can recursively bind the values.

Which one is faster?

Most popular machine learning R packages

Blog, Code, MiscellaneousPosted on 05/16/2016

The good thing about using open-source software is the community around it. There are very many R packages online, and recently CRAN package download logs were released. This means we can have a look at the number of downloads for each package, so to get a good feel for their relative popularity. I pulled the log files from the server and checked a few packages which are known to be related to machine learning. With this post you can see which are the community favorites, and get a feel for the R-software trend growth.