R Programming Language

What Is R Programming Language?

What Is R?
The R is an open source programming language and widely used for statistical computing, graphics, data analytics and scientific research.

The R programming language is most commonly used for developing the statistical software and data analysis.

The R programming was created by Robert Gentleman and Ross Ihaka at the University of Auckland, New Zealand in August 1993; 24 years Ago.
The currently managing and developing all the features and other related to R  - R Development Core Team and Its popularity is grown recent years.

The R programming supports dynamic typing, parallel computing and integration with big data technologies.

What Are the Data Types in R?
The R programming language has a wide variety of data types including scalars, vectors (numerical, character, and logical), matrices, data frames and lists.

The frequently used data types are −
ü  Vectors
ü  Matrices-numeric, character
ü  Arrays
ü  Data Frames
ü  Lists
ü  Factors
ü  Useful Functions

The simplest of these above objects is - Vector Object and there are six data types of these atomic vectors, also termed as six classes of vectors. The other R-Objects are built upon the atomic vectors.

What Are Use of with () and BY () functions in R?
The with () function is used to apply an expression for a given dataset and its looks like –

#with(data,expression)


The by () function is used for applying a function each level of factors and its looks like –
#by(data,factorlist,function)


Why Use R for Statistical Computing and Graphics?
ü  R is open source programming and free!
ü  R runs on all platforms
ü  R is most popular and currently increasing its popularity

How R commands are written?
By using the “#” at the starting of the line of code and its looks like “#division” commands is written.

What Is the use of sample () and subset () functions in R?
The sample () function is used to generate a random sample of the size n from a dataset.

The subset () function is used to select the variables and observations
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