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Big Book of R

(www.bigbookofr.com)
288 points sebg | 2 comments | 10 Apr 25 17:34 UTC | HN request time: 0.584s | source
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cye131 ◴[10 Apr 25 23:51 UTC] No.43649039[source]▶
R especially dplyr/tidyverse is so underrated. Working in ML engineering, I see a lot of my coworkers suffering through pandas (or occasionally polars or even base Python without dataframes) to do basic analytics or debugging, it takes eons and gets complex so quickly that only the most rudimentary checks get done. Anyone working in data-adjacent engineering work would benefit from R/dplyr in their toolkit.
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1. vishnugupta ◴[11 Apr 25 03:44 UTC] No.43650319[source]▶
As someone who is learning probability and statistics for recreation, I wholeheartedly agree. I wish I had come across R and dplyr/tidyverse/ggplot2 back in college while learning probability and stats. They were quite boring and drudgery to study because I wasn't aware of R to play around with data.

Well, better late than never I guess.

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2. gnuly ◴[11 Apr 25 09:55 UTC] No.43652191[source]▶
R was the first thing we had in our syllabus for (shallow)Machine Learning.

the ease of doing `model <- lm(speed~dist, cars)` and then `predict(model, data.frame(dist = c(42)))` is unparalled.