R programming in data analytics Analytics Online Course
What is R programming in data analytics?
R is a programming language possessing an extensive catalogue consisting of graphical and statistical methods. It includes some major learnings like machine learning algorithms, time series, linear regressions, etc. While talking about the R programming language, computational tasks like C++ and Fortran codes are taken into consideration. Data analytics with R language is done using 4 simple steps:
- Program: R programming is a clear and accessible programming tool
- Transform: R helps in making a collection of libraries that is meant for data science
- Discover: It helps in investigating the data and refining your hypothesis for analysis
- Model: It provides with a wide array of tools for capturing of right model for the data
- Communicate: R programming language is used for integrating codes, output, and graphs.
Why use this programming language?
- Data analysis software: Anyone like data analysts, data scientists need to make sense of data then they can make use of R for analytics statistics and predictive modelling.
- Programming language: Being an object-oriented language that is created by statisticians, it provides objects and functions for allowing users to explore, model, and visualize
- Statistical analysis: All the standard statistical methods are easy to analyse using R, and in this cutting-edge world, predictive modelling is new in R and all development techniques are used in R first.
- Community: R programming language has brought so many communities of scientists and statisticians together in this world for performing this language. Having over 2 million users, it has a vibrant online community.
R language is worth all its popularity and it is going upscale only. It allows the wide practice of graphical techniques and in the future, R programming language will be used even more. Whether it is automating tasks or designing algorithms, R programming language is used in all fields..