So, I've started using R for some stuff I'm doing at work. I have to say that I'm basically treating it as a non visual spreadsheet. Seems everything I've used it for so far, I could have done with excel. Am I doing it wrong?
Not doing it wrong, but only using a subset of R. For instance, R has powerful data manipulation ability that can get your data to use the subset of R that does what Excel does. R also has a huge library of packages that go way beyond what Excel can do, especially for statistics. Sure, you can do an ols regression in Excel, but you can you do a complicated machine learning model?
I should have been clearer. I've never been "good" at using Excel. So far, I've really only done things that I would think you could do in Excel. Might be a touch overkill, but I'm not sure. I am curious which data manipulation items you are referring to. Any good pointers?
I am going through the Machine Learning for Hackers book, though. So far it has been interesting. I guess I never realized that machine learning is essentially statistics. (Or am I looking at that incorrectly, too?)
The biggest draw to me is actually the non-visual part of it. I don't get hung up on silly visual things such as column width. Or, where to put the plots I make.
Granted, this has its own downsides. But so far I'm loving it. And yes, being able to essentially save off just what I did so that I can rerun the same tasks again later on a new data set is really really nice.
