Plotting git statistics

July 13, 2011
By

[This article was first published on Quantitative thoughts » EN, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Here’s a funny story – friend of my, avid gamer at that time, was going downhill on a bicycle when wonderful idea flashed his mind: I need to save the current status… Just in case if I crash, I will start again from the top of the hill.

If you are a developer (quantitative or software), then you can use such marvelous feature. I use GitHub for my software and data mining or quantitative projects. Yesterday I came up with an idea to check my statistics of git commits. You can easily find ready to use software, but I was eager to extend my knowledge about git features and keep my machine clean.

I built two scripts – one is Linux shell script to get the data and another one is to plot the data in R.
getstats.sh:

git log master --shortstat --pretty="format: %ai"|
sed -e 's/\+[0-9]*/,/g'|sed ':a;N;$!ba;s/ ,\n/,/g'|
sed 's/ files changed//g'|sed 's/ insertions(,)//g'|
sed 's/ deletions(-)//g' >gitstats.csv

This part of the code: git log master –shortstat –pretty=”format: %ai” dumps all necessary data and the rest of the code makes it ready for R consumption. I found this page helpful, when I tried to format the dump.

gitStats.R:

?View Code RSPLUS

require(ggplot2)
require(xts)
setwd('/home/git/Rproject/gitStats/') 
Sys.setenv(TZ="GMT")
tmp=as.matrix(read.table('gitstats.csv',sep=',',header=FALSE))
commits=xts(cbind(as.double(tmp[,2]),as.double(tmp[,3]),as.double(tmp[,4])),order.by=as.POSIXct(strptime(tmp[,1],'%Y-%m-%d %H:%M:%S')))
 
colnames(commits)=c('Changes','Insertion','Deletion')
tmp=data.frame(Date=as.Date(index(commits)),Changes=as.numeric(commits$Changes),Insertion=as.numeric(commits$Insertion),Deletion=as.numeric(commits$Deletion))
tmp=melt(tmp,id.vars=c('Date'))
png('gitStats.png',width=500)
print(ggplot(tmp,aes(Date,value,color=variable))+geom_jitter(alpha=.65,size=3))
dev.off()
 
#############daily aggregated data##############
factor=as.factor(format(index(commits),'%Y%m%d'))
tmp=cbind(as.numeric(aggregate(commits$Changes,factor,sum)),as.numeric(aggregate(commits$Insertion,factor,sum)),as.numeric(aggregate(commits$Deletion,factor,sum)))
tmp=data.frame(unique(as.Date(index(commits))),tmp)
colnames(tmp)=c('Date','Changes','Insertion','Deletion')
tmp=melt(tmp,id.vars=c('Date'))
png('gitStats2.png',width=500)
print(ggplot(tmp,aes(Date,value,color=variable))+geom_jitter(alpha=.65,size=3))
dev.off()

R script generates this nice plot below:

Photobucket

What does it shows? It shows my activity in master repository. There is two projects – one was suspended in March and another one is under heavy development. As you can see, there was a lot of insertion when the last project was committed and since then numbers of insertion declined. I will come back, when I generate more data.
Do you track your git activity?

Source code

To leave a comment for the author, please follow the link and comment on their blog: Quantitative thoughts » EN.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Tags: ,

Comments are closed.

Search R-bloggers

Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)