Sorry for reply to the wrong person, I lost the original email. > > Farrel Buchinsky wrote: > >Is R an appropriate tool for data manipulation and data reshaping and data > >organizing? I think so but someone who recently joined our group thinks > >not. > >The new recruit believes that python or another language is a far better > >tool for developing data manipulation scripts that can be then used by > >several members of our research group. Her assessment is that R is useful > >only when it comes to data analysis and working with statistical models. >
I personally started to use R because I got tired of manually writing scripts for data manipulation and processing. The argument of your new recruit smells of ignorance and resistance to learning something new. Ask her _how_ did she assess R, how much time she spent on her assessment and whether did she actually try to run it and perform some concrete simple tasks. (Yes, R is somewhat "different", it has a steep learning curve, but the effort of learning it is worth it. And yes, R can be used in the same way as any other scripting language, i.e., it is not restricted to interactive work.) Take a look at plyr and reshape packages (http://had.co.nz/), I have a hunch that they would have saved me a lot of headache had I found out about them earlier :) I would also recommend investing in Phil Spector's book "Data manipulation with R", it will get you started much faster. I also find R's image files very convenient for sharing data (and code!) in a very compact format (single file, portable across architectures). When you quit your R session, all the variables and functions get saved in the image file, which you can take with you (or send to somebody else), start R again, load the image into a new session and continue from where you left. You won't get this kind of automatic persistence in any scripting language out of the box. > >So what do you think: > >1)R is a phenomenally powerful and flexible tool and since you are going to > >do analyses in R you might as well use it to read data in and merge it and > >reshape it to whatever you need. > >OR > >2) Are you crazy? Nobody in their right mind uses R to pipe the data around > >their lab and assemble it for analysis. I'd go with 1). R has also interfaces towards databases through RODBC, so you do not have to go through several conversions when you're about to process or plot data in R. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
