![sort stata sort stata](https://usermanual.wiki/Document/briefguidetostatacommands1999.691995042-User-Guide-Page-1.png)
Which is still significantly slower than our Mata approach. We also report the most efficient method based in Stata (that uses bysort), If we were to choose a more complex hash method, it would take 18% of the time. Our variant takes roughly 3% of the time of egen group. Then, we compare five different variants of egen group: Method
![sort stata sort stata](http://1.bp.blogspot.com/-3rqiMsOHkVc/VcnbYzIxz9I/AAAAAAAAD_s/64c1xMeU8K4/s1600/2015-08-11_15h35_14.png)
#Sort stata how to
For more information, see this presentation from the 2017 Stata Conference (slides 14 and 15 show how to create faster alternatives to unique and xmiss with only a couple lines of code).
#Sort stata windows
![sort stata sort stata](https://gtools.readthedocs.io/en/master/benchmarks/quick.png)
In most cases it's much faster than both ftools and the standard Stata commands, as shown in the graph above. gtools, a package similar to ftools but written in C.Other user commands that are very useful for speeding up Stata with large datasets include: This package provides alternative implementations that solves this problem, speeding up these commands by 3x-10x: Some of the most common Stata commands (collapse, merge, sort, etc.) are not designed for large datasets. FTOOLS: A faster Stata for large datasets