It might be challenging to pick a programming language because there are so many accessible nowadays. Programmers frequently struggle with the problem of having too many excellent options. It’s enough to make folks freeze in place, helpless with uncertainty!
We give a study of the R programming language to counteract this potential cause of mental stagnation. This page explains what the R programming language is all about, what it can be used for, its fundamentals and benefits, and anything else we can think of to aid in your decision-making.
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What Is R?
The website of the R Foundation is the best resource for finding a comprehensive definition of the language. R is “… a language and environment for statistical computation and graphics,” according to R-Project.org. It’s an open-source programming language that’s frequently employed in statistical and data analysis software.
What Is R and What Are the Advantages?
There are several benefits to using the R programming language. The following is a list of some of its main advantages:
- It’s free to use. If you’re creating a new software, it’s a low-risk endeavour because no payments or licences are required.
- It’s independent of platforms. Developers only need to create one programme that can run on competing operating systems because R runs on all of them. R is cost-effective for yet another reason because of its independence!
- There are a lot of packages. For instance, the CRAN repository now has over 10,000 packages for the R programming language, and that number is steadily rising.
- For statistics, it’s fantastic. Today, statistics are very popular, and R excels in this area. Programmers favour it over other languages for creating statistical tools as a result.
- It fits the needs of machine learning. Regression and classification tasks in machine learning are well suited to R. Even the construction of artificial neural networks is supported by a variety of features and packages.
- You can manipulate data with R. Numerous programmes in R are available to help data analysts organise chaotic, unstructured data.
- R continues to expand. Thanks to a strong, supportive community, R keeps advancing, expanding, and updating.
Does R Have Any Drawbacks?
Which languages do not? We should also consider some of R’s less desirable characteristics while addressing the question, “What is R?”
- It is a challenging language. A high learning curve applies to R. The ideal candidates for this language are those who have prior programming expertise.
- It is less secure. R lacks fundamental security precautions. Thus, it’s not a wise option for developing applications that are safe for the web. Also, web browsers cannot embed R.
- It moves slowly. R is more cumbersome than Python or MATLAB, for example.
- This consumes a lot of memory. One of R’s weaknesses is memory management. Physical memory must be used to hold R’s data. However, if cloud-based memory becomes more prevalent, this disadvantage could soon become moot.
- It doesn’t have consistently high-quality documentation or packages. Documentation and software packages may be spotty, inconsistent, or lacking. That is the cost of using a language that is maintained and improved by the community rather than receiving official, dedicated support.
What Are the Most Popular R Packages?
Collections of R functions, sampled data, documentation, and produced code are referred to as R packages. These components are installed by default after installation and are kept in the R environment’s “library” directory.
R packages expand R’s functionality by enhancing the built-in features and grouping related R functions into a single entity. The R package also makes life much simpler for programmers because it is a reusable resource.
How Would You Like to Become a Data Scientist?
More data scientists are in demand from organisations today. Perhaps you are one of them. Data exploration, data visualisation, predictive analytics, and descriptive analytics approaches are all covered in Simplilearn’s Data Science With R Certification Course. You will gain knowledge of R packages, data structures, cluster analysis, forecasting, and numerous statistical concepts. You will also learn how to import and export data in R.
According to Glassdoor, a data scientist in the US can make an average salary of USD 117,212 per year. Payscale estimates that data scientists in India could earn an annual salary of 824,844 rupees.
Sum Up
This course has a promising future and is heavily utilised in research and development activity. It is also used for development and data management in emerging technologies like artificial intelligence or machine learning.
It draws both new and seasoned developers because of its enormous reach.
R programming training prepares you for the workplace and increases your adaptability for businesses. Numerous prestigious universities in Noida also provide R programming training. Therefore, if you’re interested, enrol today to earn your certification.
