Data Analysis with R Programming

R programming language is one of many important tools in data analytics, especially for statistics purposes. This powerful statistical programming tool, that is written by Statisticians for Statisticians, is called as a king of statistical computing languages for analyzing and visualizing big data. For that reason, it would be nice to know about this programming language that rules Data Science. Let’s start with the basic!

Getting started

Compared to Python, another popular programming language in the data analytics world, R actually has slightly different characteristics. R is used by professionals who have a statistical-oriented approach to solving problems; for example scientists, statisticians, and engineers. Python is used by professionals looking for solutions in the data analytics or those who have to heavily mine data for answers; for example data scientists, machine learning specialists, and software developers. The comparison between R and Python is shown below.

If we are more familiar with Microsoft Excel or SQL, R also has a commonality with them such as they all use functions. In spreadsheets, we use functions in the formulas, and in SQL, we include them in queries. In R, we will use functions in the code. In terms of the differences, we can see the table below.

Now, hopefully we have started to understand R by connecting it to our current data analytics tool and will go deeper into R as a programming language. R is based on a programming language called S. In the 1970s, John Chambers created S for internal use at Bell Labs, a famous scientific research facility. In the 1990s, Ross Oaxaca and Robert Gentleman developed R at the University of Auckland, New Zealand. The title R refers to the first names of its two authors and plays on the single-letter title of its predecessor S.

RStudio, where we do the R programming including visualization, is an IDE or integrated development environment. Since R is open source, we can either install RStudio freely on our desktop or access the RStudio Cloud. RStudio and R are designed to manage large data sets, which spreadsheets might not be…