Introduction to R

Introduction to R

  • R
  • 4 mins read

R programming language was developed as an extension of the Scheme language in the year 1993 by Ross Ihaka and Robert Gentleman. The R language came into the industry as a multi-faceted tool, serving usage in the programming, statistics, and manipulation as well as visualization domains. It is a freely available open-source language with a vast reach to all of its users. It also comes in integration with the command-line interface.  

About R Environment

The possibility of setting up R in multiple environments, that is, Linux, macOS as well as Windows makes it a platform-independent language, thereby, increasing the reach of the language to a larger audience. In addition to this, there is an easy interconversion called portability, that is allowed within the different available environments. 

R Compatibility

The compatibility of this language with other languages is also very easy and high. It can be easily integrated into other languages’ code snippets. R also proves to be an efficient tool for report generation as well as summarization of the available data in varied types of formats, for instance, CSV, pdf, or HTML. 

R as a Language

The R language supports a swift command line interpreter, wherein if any user presses 5-3, she will be replied with the number 8 instantly. 

Taking into account the simplicity of the language, various components like objects for object-oriented programming approaches, packages for data analysis and visualizations as well as tools for data science are all coherently available. R is a wide resource for a large number of packages and more than 10k+ available libraries. 

R has now encompassed so many domains, including, healthcare, academia, analytics as well as financial and media services. It has come a long way in the field of technology. It is widely used by some of the prevailing companies, like Facebook and Google. 

Why choose R?

  1. Extensive data storage with easy support available with Hadoop, Spark, etc. 
  2. Easy data handling mechanisms, inclusive of big data handling. 
  3. A collection of data analysis tools to carry out the procurement of the relevant data and its manipulation. 
  4. An integrated set of data visualization tools to identify the patterns and trends in the huge data provided. 
  5. An easy programming interface, including innumerable packages, libraries, and supports for functions to carry out the specified tasks. 

Executing a basic program in R

In order to understand how R works, we can simply run an R program from any online compiler available online. For instance, you could run the following link on the web browser ​​ to open a simple online R compiler and print a basic line onto the console screen. 

Simply run the code 

print("Hello World!")


The string “Hello World!” will be displayed on the console.

R files can be executed by simply downloading any available easy editor, like R Studio, Rattle as well as Tinn-R. The code snippet is saved with the 

Applications of R 

  1. The varied applications of R begin with the integration of a large number of databases and extend up until the availability of a large number of data science tools and libraries. Therefore, the language has been majorly developed keeping in mind the enhancement of advancements in the data analytics domain. 
  2. R is one of the most popular languages used for carrying out the Data Mining process, that is identifying the trends and patterns in the data provided. 
  3. R is an integrated tool to carry out the transformation of the data along with providing insightful details during its discovery. Efficient models are also available to get great accuracy to communicate to the world. 
  4. Statistical computations are widely available in R, with new methods being added in its set frequently
R Application structure.

However, there are some drawbacks, like the consumption of all memory and being a bit slower in comparison to other competitive languages, yet, R has now become a tool for future techies and business analysts. It is a progressive tool that will continue to solve problems further.