R is a powerful language used widely for data analysis and statistical
computing.and has many provisions to implement machine learning algorithms in a fast and simple manner. Born in 1990 R is getting prominence today because of its simplicity.
- R is data analysis software: Data scientists can use R for statistical analysis, data visualization, and
predictive modeling.
- R is a programming language: R is an object-oriented
language & provides objects, operators, and
functions that allow users to explore, model, and visualize data.
- R is an defacto environment for statistical analysis:
Standard statistical methods are easy to implement in R, and since much
of the cutting-edge research in statistics and predictive modeling is
done in R, newly developed techniques are often available in R first.
- R is an open-source software project: R’s open
interfaces allow it to integrate with other applications and systems.
- R community: The R project leadership has
grown to include more than 20 leading statisticians and computer
scientists from around the world, and thousands of contributors
have created add-on packages.
Take an example to understand the power of R language in today's collaborative open source world. The picture below shows heat map of a volcano is a R program of 15 lines that uses multiple R libraries developed by the community.
And here are the lines of R code that produced the above visualization :-
I will post more about R and why is it my ( actually all data scientist) favorite tool for data analysis. Mean while I am sharing a small tutorial for beginners to R that is available at https://www.analyticsvidhya.com
A Complete Tutorial to learn Data Science in R from Scratch
