Thanks to the importance of data mining and statistical analysis, the R programming language is making a comeback.
In August 2021, R programming language reached its highest ranking ever on the TIOBE Index — the No. 8 spot. Even now, R is still ranked in the top 15 most popular programming languages.
What is R Programming Language Used For?
R is a programming language and software environment that can be used when working with data. It was developed for statistical computation and graphics, so it is primarily used by those who work in data roles.
Data scientists, data analysts, and more use it for machine learning, data mining, and other forms of data analysis. R can allow the user to manipulate and analyze data in many ways, from building machine learning models to storing and presenting data.
Many academic institutions use R for research purposes. However, it is also becoming a more popular language among other fields as well.
Technology companies like Google and Facebook are hiring more data scientists who need to know R. Furthermore, R has become a primary language for the healthcare industry, which also has more data roles to fill.
Is R Programming Language Easy to Learn?
R is made for people who love statistics. Having a strong background in mathematics, specifically in statistics, makes the program easier to use because some of the terminologies are similar.
It is also an interpreted language, so people who don’t have much experience in coding may also find it to be easier to learn.
Since it is also a popular programming language, there are more resources available for beginners who may not have much experience in traditional coding. If someone is struggling, then there are a variety of online programs available, like Woz U.
More people will have experience using it, so they can also turn to community sites for guidance and tips on projects.
What are the Benefits of Learning R?
R is a fully-fledged software, not just a tool. R can be used to do a variety of tasks — store data, analyze data, and create statistical models. Since data analysis and data mining are processes that require a variety of applications and ways to communicate, R is a perfect language to learn.
R can also be utilized through various operating systems like Linux and Microsoft Windows and can be used to communicate with other languages like Python or Java. This makes it more adaptable than other programming languages.
R vs Python
When it comes to data science, two of the top programming languages to learn are R and Python. Many jobs will often require the person applying to be proficient in one of the two languages since they are essential for working in data science.
Python is generally easier to learn, especially since a background in mathematics isn’t required. It has clean syntax and can be applied to areas other than data science. The programming language has many modules and libraries that can be used for data science. It also is better suited for machine learning.
R, meanwhile, is more extensive in its functions and methods. It is a better program for specific data science projects and bridges statistics with computer science in a more seamless manner. R was built for statistical analysis, which means that it just can’t be beaten when it comes to processes like data mining. It may be a bit harder to learn, but it reaps far greater rewards in the end.
Ultimately, learning either language can be incredibly beneficial for those who are interested in data science careers. Each carries its own strengths and weaknesses and it ultimately depends on the users’ goals.
Growth in Data Science
Data science is an emerging field in the tech sector. According to the 2020 U.S. Emerging Jobs Report by LinkedIn, data scientist and data engineer roles are expected to grow annually by 35%.
Data analysts and data scientists need to know languages that adequately handle multi-step processes. R is among one of the few programming languages that can allow data roles to analyze large amounts of data efficiently and easily.
In the next few years, digital skills will become increasingly important to qualify for data positions. Having a solid understanding of R will be a necessary skill to learn.
The Bottom Line
R is among one of the most popular languages for data science. It is adaptable and can allow users to perform several functions since it is software built specifically for analyzing data. It is also one of the best languages for machine learning and data mining.
R is among one of the most important skills to learn for data science careers. As data science careers only continue to grow in demand, knowing how to use R can give someone interested in data science the edge and qualifications for getting a job.
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