Why Choose R for Data Science?

Why Choose R for Data Science?

An exponential increase in the use and relevance of data in today’s day and age has led to a rise in demand for exemplary data scientists. The need to use advanced tools in data science is at an all-time high, and R is one such important tool for data science. R for data science can be employed in statistical analysis and in various other processes. R, with its versatility and functionalities, is highly popular and a major part of several data science course syllabuses. But why choose R for data science? Well, this article will give you the answer to that very question.

R in Data Science

R was created in the 1990s by Ross Ihaka and Robert Gentleman at the University of Auckland in New Zealand. It is based on the S language developed at Bell Laboratories by John Chambers. R contains a collection of over 10,000 packages in its CRAN repository. These packages appeal to various statistical applications. It should also be noted that prior knowledge of statistics might be needed to get the best out of the language. A few points to remember about R in data science is:

  • Open-source software
  • Used for data analysis
  • Provides an environment for statistical analysis
  • A programming language that is constantly made better by a highly active community.

Why Choose R for Data Science?

There is a pressing and immediate need to analyze and decipher data from massive datasets, and nearly every enterprise, big or small, is facing this need. To transform unstructured data into a structured form, specialized tools are needed and R is one such tool. R provides an intensive environment for you to analyze, process, transform and visualize information, and this is pivotal for data scientists to carry out their responsibilities. 

R is an advanced language that is majorly used for performing complex statistical modeling. R supports operations on arrays, matrices, and vectors. R is extremely famous for its graphical libraries that help delineate aesthetic graphs and make them intractable for the users. Data extraction, which is a major part of data science is greatly supported and elevated by R. R does this by allowing users to interface R code with database management systems. R, along with providing several choices for advanced data analysis, also provides numerous packages for image processing. These reasons justify why most data scientists opt R for data science.

Data science is the most lucrative field of the present age, and the high demand and salaries act as proof of this claim. To become a remarkable data scientist, it is necessary to understand how crucial R is for data science and its added benefits. Praxis understands the importance of these needs and is proud to present our PGP in Data Science. This program, which is amongst the top data science courses in Bangalore and top data science courses in Kolkata is curated in a way to equip you with all the tools necessary to kickstart your career as a data scientist. Our astounding placement records are just an added bonus to what we believe is the right first step for you to start your new career.

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