It reminds me of my Excel learning days. It's not about what you understand but what you can creatively do. The most part of learning a new tool is being able to think natively in it.
If you give me a problem to solve, within 5 mins I would be sure if Excel can do it and, if yes, all the ways I can get it done in Excel. I am able to think creatively in Excel. All I think of is the input and the output. If Excel can handle the input and can display the output, then Excel (in almost all cases) can solve the problem. What functions or code or add-in to use is not a factor in my deciding whether Excel can solve a problem or not. If need be I will create new custom functions to get the solution.
Unfortunately, Excel can't handle some statistical and computing tasks well. Which are R's particular domain. So I have been slowly learning R since 2013. Slowly because I have been fixing all my problems with Excel instead of trying out R for practical jobs.
But now I am committing to adding R as one of my native tools. I will begin to use it more and run live projects through it. I like the unmatched charting tools it has and the ease of doing many complex analysis. I might even try out building a web app with it via the amazing Shiny (a package that lets one integrate with a web page and put up results of one's computation online, dynamically too).
So meet R and expect to see more posts on it from me.
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