3 ms·
> Needing to download a million random packages from grad students of the internet is a recipe for disaster. This is baloney. You don't need to rely on a milli
by clircle 6y ago
> Needing to download a million random packages from grad students of the internet is a recipe for disaster.
This is baloney. You don't need to rely on a million R packages. You really only need a good plotting library (the built-in one is fine, or use ggplot), a good data frame library (dplyr, data.table, or use build-in one), and a few extras to handle some weird rough edges (lubridate, forcats).
This takes you to 90% to your analysis goals.
Only novices are 'using a million random packages', which is probably the case for python as well.
- antipaul 6y agoIndeed. `library(tidyverse)` and I’m set for like 70-80% of use cases for data manipulation, exploratory data analysis, and statistics. Though to be complete, any ML project means python and scikit learn.
- phillc73 6y agoI also believe this is now being addressed by the pharmar[1] group with their riskmetric[2] package. [1] https://www.pharmar.org/ https://www.pharmar.org/ [2] https://github.com/pharmaR/riskmetric https://github.com/pharmaR/riskmetric