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R for Data Science – Part 1 – Introduction

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INTRODUCTION TO R

This is the first part of the series “R for Data Science”. The series is as follows:

R is an open source software and programming language built for statistical computing, graphics and machine learning. In recent years, R has gained data miners’ attention due to its wide variety of statistical and graphical techniques. It provides ease for creating mathematical symbols and formulas along with the production of well-designed plots. Apart from this, R is supported by various (operating) systems like Unix, Windows and MacOS. R has source code primarily in C, Fortran and R.

APPLICATIONS OF R

R is a comprehensible and uncomplicated programming language. It allows user to perform the most complicated code even in few lines.  R emerges as a powerful tool as it has its own pre-defined functions and packages. According to a 2014 survey, R is one of the most powerful and popular programming languages used by data scientists today.

With such benefits, R has many applications:

  • Exploratory Data Analysis
  • Experimental Analysis
  • Data and Big-Data Visualization
  • Semantic Clustering
  • Machine Learning
  • Data Modelling
  • Data Mining

And many more.

Installation of  R  – RStudio

RStudio is an Integrated Development Environment (IDE) which allows to run the R program in user friendly way. It consists of four window panel which makes easier for user to access more features at a time. Four window panel includes Code Editor, R Console screen where you can directly run the program, third screen has Workspace and History, fourth panel contains Files, Plots(all the plotted graphs and images are display here), Packages and help menu.

This is how RStudio screen looks like:

 

 

You can download R and RStudio from the following links:

https://cran.r-project.org
https://www.rstudio.com


We will learn about basic syntax and functions in next post. Stay tuned 🙂

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Trisha Singhal

Trisha Singhal

Dedicated Learner.

Reach out if want to talk and work in the field of Data Science and Machine Learning. In addition to this, I'm a Third Year Undergraduate pursuing Bachelor's degree in Computer Science and Engineering.

Linkedin : https://www.linkedin.com/in/trishasinghal
Trisha Singhal

Trisha Singhal

Dedicated Learner. Reach out if want to talk and work in the field of Data Science and Machine Learning. In addition to this, I'm a Third Year Undergraduate pursuing Bachelor's degree in Computer Science and Engineering. Linkedin : https://www.linkedin.com/in/trishasinghal

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