{"id":32123,"date":"2022-01-11T17:15:24","date_gmt":"2022-01-11T16:15:24","guid":{"rendered":"http:\/\/54.194.80.134.nip.io\/?p=32123"},"modified":"2022-01-27T11:34:18","modified_gmt":"2022-01-27T10:34:18","slug":"a-beginners-guide-to-r-programming-language","status":"publish","type":"post","link":"https:\/\/www.cubeserv.com\/en\/a-beginners-guide-to-r-programming-language\/","title":{"rendered":"A Beginner\u2019s Guide to R Programming Language"},"content":{"rendered":"\t\t
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R programming language is one of the most popular languages when it comes to data science and statistical analysis. This is mainly because R was specifically built for statistical key figures and data analysis. While R was developed in the early 90s, it wasn\u2019t until the rise of data science that people started relying on it.<\/strong><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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In today’s article, we will comprehensively go through the R programming language. You will find out why R language can be an invaluable asset for you and you will learn how to set it up.\u00a0 Don’t worry if you have no prior knowledge in programming – I will explain everything to you from the scratch. So, let\u2019s get started.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Why Should You Use R?<\/h2>

When I first learned the R language, I was under the impression that it was only suitable for statistical work. However, as I advanced further, my initial impression of R turned out to be wrong. R has actually a lot more going on than just statistical work. Let’s see some of the top reasons why using R can be of great benefit to you.<\/p>

1. Easy to Adapt<\/h3>

Just like Python, R has a very user-friendly syntax . Even if you don’t have a programming background and you are only interested in using R\u00a0 for visualizations or analysis, you can easily learn to understand and work with the R language.
The documentation is top-notch, and it won’t be long till you start getting what you want out of the language even if you have only little or no programming skills. You can also use it for other tasks such as Automation, e.g., RPA<\/a>.<\/p>

2. Fast Data Analysis\/Visualization<\/h3>

One of the best things about R is that it’s fully packed with excellent libraries. As a matter of fact, there are over 7800 packages available that let you instantly do a variety of computational and visualization tasks. In addition, there are packages available for advanced analytics that are rarely found in other programming languages.
Moreover, R has great community support. Data scientists and statisticians all over the globe will be ready to provide support in case you need help. There are hundreds of online forums available that offer support.<\/p>

3. Convenient ML Algorithms Implementation<\/h3>

Implementing Machine Learning algorithms is very fast and efficient when it comes to R. You will not have to take care of everything from scratch like you would have to in JAVA. Instead, things are already created and optimized for you on the abstract level.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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The Basic Elements<\/h2>

If you would like to use the R language, it is essential to understand the basics.\u00a0 Therefore, we will now discuss some of the key features of R.<\/p>

Objects<\/h3>

Everything you see or create in R is basically an object. Don’t get confused with the term. There are no particular prerequisites for something being declared as an object. Whatever it is, if it exists in R, it’s an object. Further on, there are some classes of these objects that are listed below:<\/p>