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Browsing commandlinefu.com today, I came across this little one-liner to display which commands I use most often.
$ history | awk '{a[$2]++}END{for(i in a){print a[i] " " i}}' \ | sort -rn | head
Here’s what I got:
283 ls 236 cd 52 cat 40 vim 36 sudo 27 ssh 27 rm 23 git 21 screen 21 R
Yep, seems legit. I navigate and look at files a whole bunch (ls, cd, cat), and I do a butt tonne of editing (vim). I sudo like a boss, hop onto various servers (ssh), clean up after myself (rm), commit commit commit (git), tuck away interactive sessions for later (screen), and of course, do mad stats (R).
Now, my bash.rc set up is set to save the 1000 most recent commands. Given that it is Friday afternoon and I’m avoiding real work while waiting for the softball game to start, I thought I’d have a look at my whole usage distribution. So, lets just collect it up into a file comme ca:
$history | awk '{a[$2]++}END{for(i in a){print a[i] " " i}}' \ | sort -rn > cmd_hist.txt
Then crack open an R session and have a look:
Cool. Looks like my command usage pattern is roughly power-law distributed! Now, to . publish . my findings . in . Nature!
The R bits:
cmd<-read.table('cmd_hist.txt') par(cex=1.2) plot(log(1:length(cmd[,1])),log(cmd[,1]), pch=20, xlab='log(Rank)', ylab='log(frequency)') fit<-lm(log(cmd[,1])~log(1:length(cmd[,1]))) abline(fit,lty=2)
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