General R Programming Interview Questions

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R is a statistical programming tool that is especially equipped to handle large volumes of data.

Working with large amounts of data and producing publication-ready charts and visualizations is easy with R. So are all kinds of data analysis, mining, and modeling tasks.

Since it was initially designed by statisticians for statistical purposes, R is exceptionally well suited to data science, an important field in today's world.

While R's primary function is statistical analysis and graphics, its use goes beyond that and extends to AI, machine learning, financial analysis, and much more.

Consistently ranked as one of the most popular programming languages china lists ​​in the world, not to mention one of the highest-paying, R has been around since the early 1990s and is still going strong.

But what is R? Read on to learn more about the R programming language, including its history, who uses it, and possible career paths if you have R skills .

What is R?
R is a statistical computing and graphics system. This system consists of two parts: the R language itself (which is what most people are referring to when they talk about R) and a runtime environment.

R is an interpreted language, meaning that users access its functions through a command-line interpreter.

Unlike languages ​​like Python or Java, R is not a general-purpose programming language. Instead, it is considered a domain-specific language (DSL), meaning its features and usage are designed for a specific domain or usage area.

In the case of R, this is statistical computing and analysis. By extension, R is commonly used for all kinds of data science tasks.

R is equipped with a large set of functions that allow data visualization, so that users can analyze the data, model it according to their needs, and then create graphs. In addition to the graphical functions built into the language, there are numerous add-ons or modules that facilitate this.

How popular is the R programming language?
R is a very popular programming language, especially in certain fields such as data science, academic research, and statistics.