OK, here am I back from my over a month’s time gap, of which there were two weeks of holydays and the rest was a huge lump of work, including the tasks for my job as well as some work at Moscow Open Data School. But now I hope I’ll be able to afford to spend some time on just learning.
Unfortunately, I couldn’t finish my Python MOOC, because of that sudden workload again. But I’m totally going to get back to it as soon as I can. Following Zach Sims’ (Codecademy) recommendation, I’m simply trying to gradually do the tasks Codecademy to refresh stuff in my mind and to keep digesting Python.
Right now though I’m focused on the Statistics course that has just begun at Coursera (by the way, those who are interested are welcome to join). I wonder how helpful it’s going to be, but there’s one thing I know for sure: I’ve got to learn how to process data in R. And well, the R course is actually integrated into this one, which is great.
While working on the first assignment, which was actually a very simple drill exercise to memorize some R commands, I faced one problem. The problem was that I couldn’t install and load a package in R (MS Windows 7) because of some troubles with administrator access to some saving functions (although I’m obviously the administrator). Or better to say, it did download the package, but it would refuse to save it in the R directory. As far as I know, some students in the same course also had troubles at this point, but they were different. In my case the solution was very simple. I just manually relocated the necessary package from where it was saved by default to where I needed it (namely, in the R library). And there’s also a way to install packages from a manually downloaded (from CRAN) .zip files through the menu (Packages > Install package(s) from local zip files). Well, at this stage this works perfectly well for me.
And here are some helpful links:
- Statistics One course (Coursera, began on 22 September)
- Computing for Data Analysis (Coursera, begins on 23 September), which is also about R
- R project (just in case)
- Great video tutorials on R (short, rather clear and simple)
- CRAN with a great number of packages and all kinds of helpful stuff
- R manuals for R