Overview of R
What is R?
R is a popular programming language used for statistical computing and graphical presentation. Its most common use is to analyse and visualize data.
R is comprised of two parts: the R language itself (which is what most people mean when they talk about R) and a run-time environment.
R is an interpreted language, which means that users access its functions through a command-line interpreter.
Unlike languages such as Python and Java, R is not a general-purpose programming language. Instead, it is considered a domain-specific language (DSL), meaning its functions and use are designed for a specific area of use or domain.
R is equipped with a large set of functions that enable data visualizations, so users can analyse data, model it as required, and then create graphics.
When was R created?
R is a popular programming language, especially in certain fields such as data science, academic research, and statistics.
R was created in the early 1990s by University of Auckland statisticians Ross Ihaka and Robert Gentleman.
Ihaka and Gentleman, who were statistics professors at a university in New Zealand, noticed what Ihaka described as a “common need for improved software” in their computer science labs.
This realization led them to start creating R, which is based on the earlier S programming language.
Although the professors started working on R in the early 90s, version 1.0.0 was not officially released until February 2000. The latest version of R is 4.4.2, which was released on 31 October 2024.
What does R’s name mean?
The R language got its name for two reasons: because R is the first letter in the inventors’ names, and because R is a play on the name of its parent language S, which was originally developed by Bell Telephone Laboratories.
Is R a low or high-level language?
R is considered a high-level programming language. High-level languages like R are designed to be easily understood and written by humans, making them more accessible for statisticians, data analysts, and researchers.
Why Use R?
- It is a great resource for data analysis, data visualization, data science and machine learning
- It provides many statistical techniques (such as statistical tests, classification, clustering, and data reduction)
- It is easy to draw graphs in R, like pie charts, histograms, box plot, scatter plot, etc
- It works on different platforms (Windows, Mac, Linux)
- It is open-source and free
- It has many packages (libraries of functions) that can be used to solve different problems.
Who Uses R?
Plenty of professionals use R in their work, and the language is used across a variety of fields. Some of them are
- Data Science
- Statistics
- Finance
- Social Media
- Academia
Careers with R
- Data scientist
- Statistical engineer
- Data analyst
- R programmer
- Database administrator
- Researcher
- Financial analyst
- Machine learning scientist
- And more…
Which companies use R?
Here are just a few of the big-name companies that use R in their tech stack:
- Bank of America
- Amazon
- Accenture
- IBM
- Uber
- Deloitte
- The New York Times
- Ford
- HP
- And many more…
Should I Choose R or Python?
If you are looking to seriously pursue data science and analytics, you will eventually need to learn both languages. Python, a general-purpose language with a broad ecosystem, is sometimes favoured for its versatility, making it ideal for machine learning, AI, and integration with other tools. R, on the other hand, was specifically designed for statistical computing and graphics, making it a preferred choice for specialized statistical analyses and research.