Get Familiar with the Basics of R

Figure 1: R Project website
Figure 2: R Project download page

Clicking on the Packages tab in Section 3 will list all the packages available in R Studio, as shown in Figure 6.

Using R is very straightforward. On the console area, type ‘2 + 2’ and you will get ‘4’ as the output. Refer to Figure 7.

The R console supports all the basic math operations; so one can think of it as a calculator. You can try to do more calculations on the console.

Creating a variable is very straightforward too. To assign ‘2’ to variable ‘x’, use the following different ways:

> x <- 2


> x = 2


> assign(“x”,2)


> x <- y <- 2

One can see that there is no concept of data type declaration. The data type is assumed according to the value assigned to the variable.

Figure 3: R icon after installation
Figure 4: R Studio icon
Figure 5: R Studio default screen

As we assign the value, we can also see the Environment panel display the variable and value, as shown in Figure 8.

A rm command is used to remove the variable.

R supports basic data types to find the type of data in variable use class functions, as shown below:

> x <- 2

> class(x)

[1] “numeric”

The four major data types in R are numeric, character, date and logical. The following code shows how to use various data types:

> x<-”data”

> class(x)

[1] “character”

> nchar(x)

[1] 4

> d<-as.Date(“2017-12-01”)

> d

[1] “2017-12-01”

> class(d)

[1] “Date”

> b<-TRUE

> class(b)

[1] “logical”

Apart from basic data types, R supports data structures or objects like vectors, lists, arrays, matrices and data frames. These are the key objects or data structures in R.

Figure 6: Packages in R Studio
Figure 7: Using the console in R Studio
Figure 8: R Studio Environment and console

A vector stores data of the same type. It can be thought of as a standard array in most of the programming languages. A ‘c’ function is used to create a vector (‘c’ stands for ‘combine’).

The following code snippet shows the creation of a vector:

> v <- c(10,20,30,40)

> v

[1] 10 20 30 40

The most interesting thing about a vector is that any operation applied on it will be applied to individual elements of it. For example, ‘v + 10’ will increase the value of each element of a vector by 10.

> v + 10

[1] 20 30 40 50

This concept is difficult to digest for some, but it’s a very powerful concept in R. Vector has no dimensions; it is simply a vector and is not to be confused with vectors in mathematics which have dimensions. Vector can also be created by using the ‘:’ sign with start and end values; for example, to create a vector with values 1 to 10, use 1:10.

> a <- 1:10

> a

[1] 1 2 3 4 5 6 7 8 9 10

It is also possible to do some basic operations on vectors, but do remember that any operation applied on a vector is applied on individual elements of it. For example, if the addition operation is applied on two vectors, the individual elements of the vectors will be added:

> a<-1:5

> b<-21:25

> a+b

[1] 22 24 26 28 30

> a-b

[1] -20 -20 -20 -20 -20

> a*b

[1] 21 44 69 96 125

A list is like a vector, but can store arbitrary or any type of data. To create a list, the ‘list’ function is used, as follows:

> l <- list(1,2,3,”ABC”)

> l


[1] 1


[1] 2


[1] 3


[1] “ABC”

A list can be used to hold different types of objects. It can be used to store a vector, list, data frame or anything else.

An array is nothing but a multi-dimensional vector that can store data in rows and columns. An array function is used to create an array.

> arr <- array(21:24, dim=c(2,2))

> arr

[,1] [,2]

[1,] 21 23

[2,] 22 24

A data frame and matrix are used to hold tabular data. It can be thought of as an Excel sheet with rows and columns. The only difference between a data frame and matrix is that in the latter, every element should be of the same type. The following code shows how to create the data frame:

> x<-1:5

> y<-(“ABC”, “DEF”, “GHI”, “JKL”, “MNO”)

> z<-c(25,65,33,77,11)

> d <- data.frame(SrNo=x, Name=y, Percentage=z)

> d

SrNo       Name       Percentage

  1        1 ABC         25

  2        2 DEF         65

  3        3 GHI         33

  4        4 JKL         77

  5        5 MNO         11

So a data frame is nothing but a vector combined in the column format.

This article gives a basic idea of how data is handled by R. I leave the rest for you to explore.


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