This week I haven’t had a chance to go through the material provided for the R programming language. Since R is one of the most popular free (open-source) statistical language along with Python, both of which has a massive community of users, I am very excited to learn this language. More and more statisticians and developers are adopting R on Python for data analysis, as 1) it’s free, and 2) the data analysis capabilities of both of these languages are endless.
I had taken few R classes during my undergraduate, and back then we didn’t have R Studio. We used to write in R script in the old user interface, so with the introduction of R Studio, its much easier to learn R. It’s been a while since I last used R, and I’m really lookin forward to learn more of it.
There are few differences between R and SAS. We can say goodbye to semicolons (;) at the end of the statements in R while we it is required in SAS. Another difference between R and SAS is that R is extremely case sensitive. For example, the “if” statement accepts a string regardless of whether it’s lower-case, upper-case or both in SAS, however, it always has be in lowercase in R. In R, there are more data types, but in SAS it’s either numeric (float, integer) or character.
These are some of the very basic things I noted on R during the class.There’s more to learn in R, but I need to go through the class presentation slides and videos. I’ll probably write more about it in my next blog. But, I’m very excited to learn R as it is very widely adopted, hopefully it will be a bit easier to learn than SAS because I’ve already taken couple of classes in my undergraduate, and our professor also said that it’s easier to learn another language if you have already learnt one.