They say the best way to learn something is to teach it.
They also say the best way to teach something is to actually use it yourself.
You may have noticed a slowing down in Excel-related posts lately. That is because for my current research projects I am rarely using Excel. I am finding it more difficult to provide creative, helpful content without the daily use of Excel.
At the same time, however, I have plunged into new areas – including R.
Please don’t panic
“R! Yeah! Excel sucks! People should just use R or Python.”
1,000 times no. This is such a silly accusation.
Excel is just one tool in the analyst’s toolkit. It is especially helpful when working with small, irregular datasets. Perfect, for example, if you work in an office and have to manage budgets and schedules, for example.
Very valuable tool indeed. But it would also be foolish to see every data analysis problem as an Excel problem. Some are better handled with other tools.
In my current situation (doing textual analysis of large amounts of SEC documents), Excel is not the best tool. So I am familiarizing myself with other tools, and maybe they can help you too.
It’s a free statistical programming language that is very popular and powerful. I like to use it with RStudio, a program which allows for a smoother user experience along with some enhanced back-end capabilities to base R. The intro-level version of RStudio is also free.
Here is a helpful video from Udacity on downloading RStudio for Windows (Mac will be very similar):
First, download R from the R Project homepage.
Then, download the free version of RStudio.
Important – you must download R and RStudio. RStudio needs the base R package to function.
Until next time…
Ever used R? Have ideas on how it could help you? Questions? Comments? Let me know.
I hope to start sharing some of the cool things I have learned to do in R, but installing is a good first start.