In this video, I'm introducing you to the R programming language. R is a powerful and popular programming language used for data analysis and scientific computing.
If you're interested in learning more about R programming, then this video is for you! I'll explain the basics of R programming and give you a preview of some of the features that make it such a versatile language. After watching this video, you'll have a better understanding of R programming and be ready to start using it in your day-to-day work!
#parnikatutorials #rprogramming #datascience
R is an open-source programming language that is widely used as a statistical software and data analysis tool. R generally comes with the Command-line interface. R is available across widely used platforms like Windows, Linux, and macOS. Also, the R programming language is the latest cutting-edge tool.
It was designed by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, and is currently developed by the R Development Core Team. R programming language is an implementation of the S programming language. It also combines with lexical scoping semantics inspired by Scheme. Moreover, the project conceives in 1992, with an initial version released in 1995 and a stable beta version in 2000.
R programming is used as a leading tool for machine learning, statistics, and data analysis. Objects, functions, and packages can easily be created by R.
It’s a platform-independent language. This means it can be applied to all operating system.
It’s an open-source free language. That means anyone can install it in any organization without purchasing a license.
R programming language is not only a statistic package but also allows us to integrate with other languages (C, C++). Thus, you can easily interact with many data sources and statistical packages.
The R programming language has a vast community of users and it’s growing day by day.
R is currently one of the most requested programming languages in the Data Science job market that makes it the hottest trend nowadays.
Basic Statistics: The most common basic statistics terms are the mean, mode, and median. These are all known as “Measures of Central Tendency.” So using the R language we can measure central tendency very easily.
Static graphics: R is rich with facilities for creating and developing interesting static graphics. R contains functionality for many plot types including graphic maps, mosaic plots, biplots, and the list goes on.
Probability distributions: Probability distributions play a vital role in statistics and by using R we can easily handle various types of probability distribution such as Binomial Distribution, Normal Distribution, Chi-squared Distribution and many more.
Data analysis: It provides a large, coherent and integrated collection of tools for data analysis.
R programming language is much slower than other programming languages such as Python and MATLAB.
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13 окт 2024
