Top 10 Reasons to Learn R

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Top 10 Reasons to Learn R

Why R could be the language for your next Big Data project.

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The R programming language is one of the most popular programming languages right now. As such, the comparison is quite often made between R and other popular programming languages, such as R vs. Python and R vs. Matlab.

R has an exhaustive number of packages. It is open source and completely free to use. Active community support for the statistical programming language is also available. These are just some of the several reasons to get started with R today.

If you’re looking forward to starting learning R, then here is our list of the 10 top reasons to positively influence your decision. If you haven’t yet decided to go with R yet, then these might help you make up your mind. So, without further ado, off we go:

You may also like: Learn R: Hello World with R.

1. Backed by a Huge, Active Community

Having a supportive, expanding community is for sure one of the biggest advocating factors for picking up the R programming language.

Finding solutions to complex, real-world problems is a challenging task. While some parts of it, depending on the intensity of the problem, might be easy to figure out, others might seem daunting.

No matter whether you’re using R for financial applications or realizing data science projects or something else entirely, the humongous, active, and mushrooming R community is always there to help you out with ideas, innovations, and online discussion boards.

Having a supportive community is not only good for helping you tackle problems, but it also presents the opportunity to connect with like-minded people.

You can share your ideas with the community and also collaborate to produce products that can help you and other members of the community.

2. Comprehensive Library Support

There are over 10k packages and hundreds of thousands of built-in functions targeting different requirements available in the R programming language.

Other than the professional packages offered for data manipulation, data visualization, machine learning, and statistical modeling, there are numerous other packages that are simply there to toy around with and feed the imagination of the people with bright ideas.

Chances are that whatever you want to accomplish with R, there might be more than one package available for you. And if there isn’t, you can create and publish one. After all, R is an open source, digital asset, and who doesn’t like a helping hand?

3. Cross-Platform Compatibility

One of the biggest advantages of the R programming language is its ability to support a wide array of operating systems. It can be used on a variety of software and hardware configurations with no modifications.

Despite the different environments the R is subjected to perform on, the programming language gives out a pleasingly seamless operation. This enables providers the freedom to choose different operating systems, hardware and software configuration than their clients and still succeed in delivering stellar results.

4. Data Visualization at its Best

Data visualization has always been an important part of processing data and churning out important details from it. In the present data-savvy world, the importance of data visualization has reached new frontiers.

The R programming language is a majestic option for visualizing data. Thanks to its high-quality graphics, the R programming language is notably used in the pharmaceutical industry. However, it isn’t limited to that.

R packages, such as ggplot2, ggvis, and plotly help in creating robust and detailed data visualizations. Packages like these create high-quality, print-ready graphs, histograms, pie charts, scatter plots, Venn diagrams, and so much more.

5. Develop Interactive, Powerful Web Apps With Shiny

The R programming language has a package called Shiny that helps users create powerful web applications directly from data analysis software. To make things even better, you can host any web app created using Shiny on cloud services like AWS, Google Cloud, and Microsoft Azure.

With Shiny by your side, you can create striking dashboard designs as well as intuitive web pages right from the R console.

6. Go-to Option for Statistical Analysis and Data Science

Some of the points mentioned on this list of top 10 reasons to learn R, such as a highly active community, make up for advocating the programming language’s capacity for data science projects.

There is no scarcity of bankable reasons for using R for data science projects, including having powerful infrastructure support. Now, R can be considered as a statistical software for the statisticians by the statisticians. So, naturally, it is apt for accomplishing statistical analysis.

Ranging from building complex statistical models to finding out simple measures of central tendency, R is the go-to option for many different types of statistical analysis.

As an added benefit, simple R functions can be used for building complex machine learning models to the likes of Gaussian Process Regression, Poisson Regression, and Random Forest.

7. High Market Demand With High-Paying Roles

There has been a surge in the demand of data analysts, data scientists, financial analysts, and quantitative analysts. These are just some of the many career avenues feasible with R added to your skills arsenal.

According to this Quora Q&A string, the R programming language has become the most popular analytics tool in the world. It also explores the many career possibilities available with R.

With the increased focus on data and data analysis, the significance of R is projected to increase over time. That also means that opportunities for the experienced are going to be bigger and better. Hence, it is high time to pick up R and start exploring for better professional opportunities.

8. Major Companies Trust R

Anything that is used by famous international organizations is likely to gain attraction from the general public. There is no scarcity to the number of reputed companies that have picked up R to ease their business endeavors. Here are some of the most notable examples:

  • Facebook employs R for accomplishing behavioral analysis pertaining to profile pictures and status updates.
  • Google finds R useful for understanding advertising effectiveness and economic forecasting.
  • The American automaker Ford uses R for improving vehicle designs.
  • Twitter leverages the R programming language for data visualization and semantic clustering.

Being used by some of the most famous organizations not only adds to the popularity enjoyed by the R programming language, but it also increases the preference received by the same among smaller and medium-sized businesses as well as professional individuals that look up to such elite firms.

9. Multi-Domain Applications

There are several industries and domains benefitting from R, ranging from organizations specializing in data science to pharmaceutical firms. 

The following are just some of the many industrial uses of R:

  • For analyzing fraudulent transactions and building econometric models in the financial domain.
  • For chum management, personalize advertising, and subscriber profiling by telecom firms.
  • For performing genomic analysis in computational biology.

10. Open Source Distribution

The popularity of a piece of software, web technology, or programming language greatly depends on the way it is distributed. While a proprietary paid product brings peace of mind and reliability, it, on the downside, strictly avoids tinkering by the fascinated-minded.

Open source software and products are always popular among the masses. So, now that we have upgraded to Web 2.0 and Web 3.0 might be around the corner, the popularity enjoyed by open source and free software has also risen to a grander scale.

This is because the Internet is no longer a novelty item; it has become an essential commodity for one and all. Everyone has social media profiles, like to surf the web, download software and tools, and, if possible, toy with them.

In the present time, any quality product that is available for free and open source is likely to gain traction. This is true in the case of the R programming language, which is also a free, open-source commodity that you can modify as per your requirements.

Distribution under the GNU license allows the R programming language to be readily installed and getting started with by anyone. Being open source lets the tinkers modify the existing code as well as add their very own innovations and catalyze the mushrooming community support.

After Note!

So, that was all! We have successfully completed our list of the top 10 reasons to learn R. However, you need to understand one thing if you haven’t started with R yet.

Although, it is not a difficult programming language to learn. It demands a good background in mathematics, machine learning, statistics, and data analysis.

You need to be resolute in understanding and developing competence in the programming language first. Afterward, you are free to explore the endless opportunities that R programming language has to offer. All the best!

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big data ,hello world ,r ,r programming ,tutorial

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