And when the data gets bigger, there's data.table[1], which performs amazingly well at certain tasks (vectorized ops ftw!), though the syntax can get a little c

And when the data gets bigger, there's data.table[1], which performs amazingly well at certain tasks (vectorized ops ftw!), though the syntax can get a little clunky (if you squint at it hard, it's SQL-ish). On my 2012 macbook pro, I'm able to do (some) transformations of tables containing 10s of millions of rows in only a few seconds (and sometimes faster). It's possible to use dplyr and data.table together, as well, to good effect[2]. [1] https://github.com/Rdatatable/data.table/wiki https://github.com/Rdatatable/data.table/wiki [&] https://github.com/Rdatatable/data.table/wiki/Benchmarks-%3A-Grouping https://github.com/Rdatatable/data.table/wiki/Benchmarks-%3A... [2] http://stackoverflow.com/questions/21435339/data-table-vs-dplyr-can-one-do-something-well-the-other-cant-or-does-poorly/27840349#27840349 http://stackoverflow.com/questions/21435339/data-table-vs-dp... [&] https://twitter.com/hadleywickham/status/553169339751215104 https://twitter.com/hadleywickham/status/553169339751215104