1.8 Extracting / subsetting
Sometimes you want just part of an object. In some cases you will use square [ ] brackets or double square [[ ]] brackets, and in other cases you will use a dollar sign $.
1.8.1 Extracting elements from a vector
Given the following 3-element vector x,
x <- c(8, 4, 10)
x## [1] 8 4 10we can, for example, extract the 2nd element,
x[2]## [1] 4the first 2 elements,
x[1:2]## [1] 8 4the first and third elements,
x[c(1,3)]## [1] 8 10all but the first element of x,
x[-1]## [1] 4 10or the elements that meet a certain condition.
x[x > 5]## [1] 8 101.8.2 Extracting elements from a matrix or array
Similarly, we can extract elements from a matrix or array, but now we need multiple indices separated by commas. For example, given the following 2-dimensional matrix x,
x <- matrix(c(1,2,3,4,5,6), nrow = 2, ncol = 3)
x## [,1] [,2] [,3]
## [1,] 1 3 5
## [2,] 2 4 6we can, for example, extract the element in the 2nd row and 3rd column (the first index refers to the row, the second to the column),
x[2,3]## [1] 6the first row (make sure to include the comma!),
x[1,]## [1] 1 3 5or the third column (make sure to include the comma!).
x[,3]## [1] 5 6If you leave out the comma, you will get an answer not an error. For example:
x[3]## [1] 3But it is ambiguous to say “the 3rd element of a matrix” since you could go down columns or across rows. R has a default, but rather than try to remember what that is, just do not forget the comma and then there is no ambiguity.
NOTE: Best practice is to avoid coding shortcuts unless there is a clear need (like optimizing speed). Use clear, unambiguous code.
Subsetting an array is similar to subsetting a matrix. However, unlike a matrix, an array can have more than two dimensions so you must have as many indices as you have dimensions. For example, given the 3-dimensional array z,
z <- array(c(1,2,3,4,5,6,7,8), dim = c(2,2,2))
z## , , 1
##
## [,1] [,2]
## [1,] 1 3
## [2,] 2 4
##
## , , 2
##
## [,1] [,2]
## [1,] 5 7
## [2,] 6 8we can extract a single element,
z[2,1,2]## [1] 6a sub-vector,
z[1,,2]## [1] 5 7or a sub-matrix,
z[,2,]## [,1] [,2]
## [1,] 3 7
## [2,] 4 81.8.3 Extracting elements from a list
For a list, you can use single square [ ] brackets or double square [[ ]] brackets, depending on what you want to extract. For example, given the list x, containing a character string, a numeric vector, and the factor object y,
x <- list("5", c(1,2,3), y)
x## [[1]]
## [1] "5"
##
## [[2]]
## [1] 1 2 3
##
## [[3]]
## [1] Underweight Underweight Normal Overweight Normal
## Levels: Underweight Normal Overweightwe can use [ ] to extract a sub-list containing only, for example, the first element,
x[1]## [[1]]
## [1] "5"class(x[1])## [1] "list"or multiple elements,
x[c(1,3)]## [[1]]
## [1] "5"
##
## [[2]]
## [1] Underweight Underweight Normal Overweight Normal
## Levels: Underweight Normal Overweightclass(x[c(1,3)])## [1] "list"or we can use [[ ]] to extract a single element, which will have the class of that element.
x[[1]]## [1] "5"class(x[[1]])## [1] "character"x[[2]]## [1] 1 2 3class(x[[2]])## [1] "numeric"x[[3]]## [1] Underweight Underweight Normal Overweight Normal
## Levels: Underweight Normal Overweightclass(x[[3]])## [1] "factor"1.8.4 Extracting elements from a data frame
Recall that a data.frame is special type of list where each element is one of the columns. You can access the elements of a data.frame in a number of ways, including the $ method. Also, when subsetting we can use the column names. For example, given the data frame x,
x <- data.frame(outcome = c(1, 0, 1, 1),
exposure = factor(c("yes", "yes", "no", "no"),
levels = c("no", "yes"),
labels = c("No", "Yes")),
age = c(24, 55, 39, 18))
x## outcome exposure age
## 1 1 Yes 24
## 2 0 Yes 55
## 3 1 No 39
## 4 1 No 18we can extract a data.frame made up of a subset of columns using [ ],
x[1:2]## outcome exposure
## 1 1 Yes
## 2 0 Yes
## 3 1 No
## 4 1 Noclass(x[1:2])## [1] "data.frame"x[c("outcome", "exposure")]## outcome exposure
## 1 1 Yes
## 2 0 Yes
## 3 1 No
## 4 1 Noclass(x[c("outcome", "exposure")])## [1] "data.frame"a single column of the data.frame, returned as the class of that column, using [[ ]] or $.
x[[3]]## [1] 24 55 39 18class(x[[3]])## [1] "numeric"x[["age"]]## [1] 24 55 39 18class(x[["age"]])## [1] "numeric"x$age## [1] 24 55 39 18class(x$age)## [1] "numeric"When using the $ method, if the variable name has spaces, then enclose it in ` ` (not regular quotes) when extracting it. To illustrate, let’s change the names of this data.frame by assigning a new value to its names().
names(x) <- c("Outcome Level", "Exposure", "Age")
x## Outcome Level Exposure Age
## 1 1 Yes 24
## 2 0 Yes 55
## 3 1 No 39
## 4 1 No 18To extract the first column, whose name has a space, we must enclose the name in ` `.
x$`Outcome Level`## [1] 1 0 1 1You can also extract elements of a data.frame using matrix indexing. For example, you can extract the first column of x, returning a vector,
x[,1]## [1] 1 0 1 1class(x[,1])## [1] "numeric"the first row of x, returning a data.frame with 1 row,
x[1,]## Outcome Level Exposure Age
## 1 1 Yes 24class(x[1,])## [1] "data.frame"or the first column of x, returning a vector of the class of that column,
x[,1]## [1] 1 0 1 1class(x[,1])## [1] "numeric"or a data.frame if you include drop=F.
x[,1,drop=F]## Outcome Level
## 1 1
## 2 0
## 3 1
## 4 1class(x[,1,drop=F])## [1] "data.frame"If extracting more than 1 column, drop=F is not necessary to return a data.frame.
x[,1:2]## Outcome Level Exposure
## 1 1 Yes
## 2 0 Yes
## 3 1 No
## 4 1 Noclass(x[,1:2])## [1] "data.frame"In any of these column extraction via matrix-subsetting examples, you can use the column names.
x[, "Outcome Level", drop=F]## Outcome Level
## 1 1
## 2 0
## 3 1
## 4 1class(x[, "Outcome Level", drop=F])## [1] "data.frame"Some data.frame objects have rownames. By default, R just assigns numbers.
rownames(x)## [1] "1" "2" "3" "4"But suppose we have a data.frame with, say, participant IDs as the row names.
rownames(x) <- c("B239", "B211", "B101", "B439")
x## Outcome Level Exposure Age
## B239 1 Yes 24
## B211 0 Yes 55
## B101 1 No 39
## B439 1 No 18Then you can subset rows using row names.
x[c("B211", "B439"),]## Outcome Level Exposure Age
## B211 0 Yes 55
## B439 1 No 18You can also subset rows of a data.frame using logical statements about the values in the data.frame. For example, suppose we want to extract the rows with Exposure = “Yes”. We use the == (double equal sign) operator for the logical equals operator (see Section 1.13 for more on logical operators).
x[x$Exposure == "Yes",]## Outcome Level Exposure Age
## B239 1 Yes 24
## B211 0 Yes 55