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Analyzing data requires a lot of research. But do you know something which can make it easier? R programming is used to create projects and models. These projects are dependent on data. Researchers use this programming language to create business models and perform data analysis functions.
R Programming is a rapidly developing language with many advantages. It is an option that has syntaxes that are easy to use. Thus, its users easily prefer the UI of R over other languages.
Some significant advantages of R programming include its versatility, open-source nature, diverse extensions, quality data visualization, etc.
All the advantages of R programming are listed below:
Open-Source Language
R is an open-source language accessible to anyone. Users do not need any paid licensing or permissions to access it. One can easily contribute and modify the source code.
Compatibility And Versatility
You can integrate R language with other languages such as C/C++, Java, and Python. It also allows you to pair it up with other DBMSs and technologies. Also, R is a platform-independent language. It enables you to run it on Linux, Windows, and Mac without any bugs.
Extensions
R has many extensions that provide the user with a premium experience. You need not explore different tools for different tasks while developing a business model or a machine learning project. Extensions that help in statistical modeling, data manipulation, and graphics are present. The user is free to use them for better modifications.
Data Visualization
As discussed above, with various extensions, you can create attractive reports with R wherever there is data. Plotting visually appealing and aesthetic graphs is supported by R.
Machine Learning
You can perform machine learning operations using R. Be it advanced artificial neural networks or regression and classification.
Statistics
R is widely used because it can develop statistical models as no other language can. R supports discrete and continuous probability distributions, making its horizon more favorable.
A Vast Array Of Packages
With more than 10,000 packages in its CRAN repository, R is loaded with data science and machine learning packages.
R is an open-source programming language used to develop data-backed models. As mentioned earlier, it is used not only for data science but big businesses and companies too. They use it to manage big sets of data and develop programs statistically. Big players like Google, Microsoft, Facebook, and Twitter use it in their daily processes. It is because the advantages of R programming are vast.
The ‘R Foundation for Statistical Computing’ maintains R. It is a popular option for doing analytical jobs and Data Science. Working with giant volumes of data appears simple with the language R.
It is a trendy language among developers due to the various advantages of R programming. Primarily used in data analysis, statistical operations, and machine learning but its use in the industry is not limited to this.
Its packages offer many services which are used by many businesses and industries. Some of them are listed below.
Healthcare
Manufacturing
Academic research
Retail
Social media
Financial services in fintech companies
FDA(Food and Drug Administration) and weather services
Anyone can learn R to build statistical models and graphs for various business and academic operations. Besides this, data science aspirants, statisticians, and students can opt for this language.
Is it easy to learn R?
Although it may seem a little complex, it becomes easy after gaining the required knowledge. If the user is determined enough, it is a rather simple language.
Do we need prior knowledge of programming language for R?
Yes, you need a basic knowledge of computer science. A basic understanding of programming is required to learn R.
What is CRAN?
The “Comprehensive R Archive Network” (CRAN) is a collection of sites that carry identical material, consisting of the R distribution(s), the contributed extensions, documentation for R, and binaries.
What is the future of R language?
It is currently one of the most demanding languages for data science and statisticians. There is rapid growth in the demand for this language as it is constantly evolving and highly efficient for data analytics.
Conclusion
In this blog, we learned about many advantages of R programming. This language can be handy for you if you are a data science student or want to build statistical models for your research. All the positive parts of the R Language we discussed put us a step ahead towards developing our interest in discovering R.
We recommend you visit these links for more information on the R language-
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