Introduction to R
R and RStudio (its companion IDE, integrated development environment), together constitute one of the most popular tools used by researchers to analyze big data. Because it was first designed by statisticians for statistical purposes, R is a really nice language for data science. Wrangling massive amounts of information and producing publication-ready graphics and visualizations are more straightforward with R than other languages, and its use in data science remains strong.
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R is an open-source language, which means that anyone can contribute to its development, and the course of development has a life of its own, which its development is based on the collaborative effort of many many people.
Like Unix, it R is not as intuitive as say Python, but it is easier to learn than Unix, because the syntax is more uniform across the many R packages that are available for use. Like Unix, you will come to use specific packages, and the ones you use most often will become very familiar to you, like old friends.
R is an interpreted language, which means that users access its functions through a command-line interpreter. We will be using the RStudio IDE, but lets first see what it’s like to use R at the command line.
Type R. into yout your terminal, and run a couple of “calculator” commands.
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But we will not be using R from the terminal, we will be using the RStudio IDE.