[R] things that are difficult/impossible to do in SAS or SPSSbut simple in R

hadley wickham h.wickham at gmail.com
Thu Jan 17 14:51:48 CET 2008

> Previously I used SAS for 23 years and now R/S-Plus for 17.  SAS is
> effective for large datasets (in my work > 500,000 subjects) but except
> for that, R is far superior to SAS for data management and manipulation.
>   Just four of the reasons are that you can
> - merge data frames multiple ways and compare the results
> - deal with arrays (lists) of datasets using high-level operators
> - easily do complex calculations on serial data such as find the highest
> blood pressure per subject that is measured before something else is
> measured
> - sense the type of a variable (character, factor, date, discrete
> numeric, continuous numeric, etc.) while analyzing it, and tailor the
> analysis to the type of variable

And one more:

 * you can trust that R will do the correct thing with missing values
(propagate them by default)



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