Introduction to R Programming

R is a programming language developed by Ross Ihaka and Robert Gentleman in 1993.  It includes machine learning algorithm, linear regression, time series, statistical inference to name a few. Most of the R libraries are written in R, but for heavy computational tasks, C, C++ and Fortran codes are preferred.

Data analysis with R is done in a series of steps; programming, transforming, discovering, modeling and then communicating the results. R can communicate with other languages. It is possible to call Python, Java, or C++ in R. The world of big data is also accessible to R. You can connect R with different databases like Spark or Hadoop.

  • Program: R is a clear and accessible programming tool
  • Transform: R is made up of a collection of libraries designed specifically for data science
  • Discover: Investigate the data, refine your hypothesis and analyze them
  • Model: R provides a wide array of tools to capture the right model for your data
  • Communicate: Integrate codes, graphs, and outputs to a report with R Markdown or build Shiny apps to share with the world

R is not only entrusted by academics, but many large companies also use the R programming language, including Uber, Google, Airbnb, Facebook and so on.

What is R used for?

  • Statistical inference
  • Data analysis
  • Machine learning algorithm