R Language • Data

Subsetting Data/R Objects

R Language’s most powerful feature is indexing feature. Indexing feature plays an essential role to represent the data. During the data analysis stage its vital to extract and manipulate subset of the data.

Subsetting a Vector

The basic object of R is a vector. To extract the elements can use ’[’ operator.

> num <- c(1, 2, 3, 3, 3, 5, 6, 7, 8, 8, 9, 10) ## Create a vector
> num[1] ## Extract the first element 
[1] 1
> num[3] ## Extract the third element 
[1] 3

Not only one element, using ’[’ operator we can extract multiple elopements from the vector.

> ## Extract multiple elements
> num[2:5] 
[1] 2 3 3 3
> ## Extract multiple elements (un order sequence- access from indices
> num[c(2,3,1,6)])
[1] 2 3 1 5
> ## Extract multiple elements (duplicate indices)
> num[c(2, 2, 2)] 
[1] 2 2 2

Use of negative indices

> num
 [1]  1  2  3  3  3  5  6  7  8  8  9 10
> num[-1] ## Skip the first element
 [1]  2  3  3  3  5  6  7  8  8  9 10
> num[-c(1,3)] ## Skipt first and third elements
 [1]  2  3  3  5  6  7  8  8  9 10

Use of logic

> num_bool <- num > 3 ## Condition to check 
> num_bool ## Condition results 
 [1] FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
[12]  TRUE
> ## Extract the result adhering to the condition
> num[num_bool] 
[1]  5  6  7  8  8  9 10
> num[num > 8] ## More compact way to do
[1]  9 10

Subsetting a Matrix

Matrix can be subsetted in the usual way with their row and column indices.

> my_mat <- matrix(1:6, 2, 3) ## Create matrix
> colnames(my_mat) <- c("a","b","c") ## Assign name for columns 
> my_mat
     a b c
[1,] 1 3 5
[2,] 2 4 6

Accessing the row=1 and col=2.

> my_mat[1,] ## Extracting the first row
a b c 
1 3 5 
> my_mat[,2] ## Extracting the second column
[1] 3 4

Accessing the element using matrix indices points row=2,col=3 and row=1,col=1.

> my_mat[2,3] ## row=2,col=3 
c 
6 
> my_mat[1,1] ## row=1,col=1 
a 
1

While extracting the element from a matrix we would have seen in the above code the Matrix dimension has dropped. But during subsetting the object we have the option to turnoff by setting drop =FALSE.

> my_mat ## Matrix
     a b c
[1,] 1 3 5
[2,] 2 4 6
> my_mat[1, 2] ## Default drop = TRUE
b 
3 
> my_mat[1, 2, drop = FALSE] ## Set drop = FALSE
     b
[1,] 3
> my_mat[2,] ## row=2 | default drop = TRUE
a b c 
2 4 6 
> my_mat[2,, drop = FALSE] ## row=2 | default drop = FALSE
     a b c
[1,] 2 4 6

Subsetting Lists

Subsetting a list is almost like vectors. Since list can contain different objects within the list, to extract the elements we should use [[ or $ operator.

> ## Create a list
> my_list <- list(no = 1:10, id = 1001)
> my_list
$no
 [1]  1  2  3  4  5  6  7  8  9 10

$id
[1] 1001

> my_list[[1]] ## Use [[ operator to extract elements
 [1]  1  2  3  4  5  6  7  8  9 10
> my_list$no ## Use $ operator to extract elements
 [1]  1  2  3  4  5  6  7  8  9 10

Subsetting Data Frames

It similar to matrix, we need using the indices of row and column.

> df <- data.frame(num = 1:3, name = c('Renien', 'John', 'Joseph'))
> df ## Data frame created
  num   name
1   1 Renien
2   2   John
3   3 Joseph
> df[1,] ## Extract the first row
  num   name
1   1 Renien
> df[1,1] ## Extract the first row’s first column element 
[1] 1
> df[c(1,3),]	## Extract the first and third row
  num   name
1   1 Renien
3   3 Joseph
> df[1,1, drop = FALSE] ## Keep the dimension
  num
1   1

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