What Is R Language?

R is a specialized programming language for statistical computing and data visualization, making it a popular choice for data scientists and business and data analysts. Although R doesn’t offer the same wide variety of functionality as general-purpose programming languages, R is a statistical language with built-in analytical and graphic functionalities that allow it to excel in areas including data visualization and statistical analysis. 

R was built by statisticians, meaning the syntax is more domain-specific and may have a steep learning curve initially. This makes it more challenging to learn than other high-level languages you may be familiar with, such as Python. Although it could take you more time to learn R, it’s a worthwhile commitment for those interested in pursuing a career in a data-oriented field. Throughout this article, you’ll find excellent resources and information to help you start learning to program with R.

What is the definition of R language?

This open-source statistical programming language provides a software environment conducive to both graphics and statistical computer operations, making it popular for use in statistics and data science alike. Being open-source means the language isn’t proprietary, making it widely available. This also means that you and other programmers can develop custom libraries you can use in your own projects. 

You can use this free programming language to tackle tasks such as statistical analysis, data mining, and machine learning. R is also a cross-platform language, allowing you to use the language whether you’re on a Mac OS, Windows, or Linux system. 

What are the different R environments?

You can use R in several integrated development environments (IDE) software applications designed for efficient programming. While RStudio is the most popular IDE for R, other options include Jupyter Notebook, PyCharm, and Eclipse StatET.

How can you learn R?

You have several options for learning how to program using R, including online courses and certifications, challenges, bootcamps, or through college and university degree programs.

Online courses and certifications

You can find resources online, some of which are free, to help you learn how to program using R. In some cases, online courses will offer a certificate upon completion. Online courses offer an excellent option if you need flexibility and want to learn R without making a significant time or financial commitment. 

For example, on Coursera, you can earn an IBM Data Analytics with Excel and R Professional Certificate, which can help you attain in-demand skills for a career in data analytics.

Bootcamps

Another option you can explore for learning R is bootcamps. Compared to pursuing a degree, enrolling in an R bootcamp is typically less expensive and can be finished quicker. When you enroll in bootcamps, you’ll have valuable opportunities to gain hands-on practice while working on projects and building your portfolio, which you can later use to demonstrate your skills to employers. Since bootcamps are intensive, they can help you build your programming skills in a short amount of time.

Degree programs

Through a college or university degree program in computer science or data science, you can learn how to program in R. Though this is a significant time and financial commitment, getting a degree is a common path for learning how to code. While you will have the opportunity to develop technical skills, you will also learn theoretical information, whereas online courses and bootcamps are more skill-specific. 

Timeline for learning R 

How long it will take you to learn R depends on factors such as how much time you dedicate to practicing and the amount of previous programming experience you have. You may be able to learn the basic commands of R relatively quickly, but developing competency in more complex libraries can take time. 

However, if you’re new to programming, it may take you several months to feel comfortable working with the R language and gaining a more comprehensive understanding of the language can take several years. Daily practice can help accelerate the learning process. If you choose to take the bootcamp route, typical bootcamps last between 12 to 24 weeks. 

How you can use R

You can use R in numerous ways, depending on the task you're trying to accomplish. Here are some of the things you can do with knowledge of R:

• Data visualizations: R’s ggplot2 package is one of its popular libraries and an excellent tool for creating data visualizations. The visualizations you create to represent your data using R are useful in helping others better understand the data.

• Machine learning: With R, you can build machine learning models to make predictions using data. 

• Data analysis: Another useful tool in R for manipulating, exploring, and performing calculations on data sets is tidyverse, a package that includes tidyr and dplyr. Tidyverse has a variety of packages that simplify the data analysis process. With R, you can import data from Excel, text, and CSV files for analysis.

Benefits of knowing R

Several factors contribute to making R a worthwhile language to learn. R users make up a large, diverse community with people from all kinds of backgrounds, such as business analysts, statisticians, and other programmers. This robust community leads to the continuous development of thousands of different packages for natural language processing, stock market analysis, and much more.

Additionally, the specific statistical functions in R offer advanced data analytics and visualization features. These might be especially helpful in certain industries, such as research or data science. 

Who should learn R? 

While R is especially popular in data science, it’s useful in multiple fields. If you’re interested in pursuing a career that uses statistical analysis, R will be a valuable addition to your skill set. While not a comprehensive list, several careers you might pursue that benefit from R knowledge include:

• Data scientist

• Business analyst

• Data analyst

• Software programmer

• Data architect

• Statistical analyst

• Meteorologist

• Market analyst

• Operations analyst

Get started with Coursera

R is a popular open-source programming language to manage, analyze, and visualize data. If you’re interested in a data-driven career, learning R through a traditional university course, online bootcamp, or certification program can help you build relevant professional skills. 

To start learning, you can find highly-rated courses to develop your skills in R. Google’s Data Analysis with R Programming can help you learn more about the data visualization capabilities in R and cover fundamental concepts. Another great option is Data Science: Foundations using R Specialization from Johns Hopkins University. This course is designed to help you learn how to set up RStudio, as well as how to clean, analyze, and visualize data.