How to do it…

The missing values are represented in R by NA. When we download data, it may have missing data and this is represented in R by NA:

z = c( 1,2,3, NA,5,NA) # NA in R is missing Data

To detect missing values, we can use the install.packages() function or is.na(), as shown:

complete.cases(z) # function to detect NA
is.na(z) # function to detect NA

To remove the NA values from our data, we can type the following in our active R session console window:

clean <- complete.cases(z)
z[clean] # used to remove NA from data

Please note the use of square brackets ([ ]) instead of parentheses.

In R, not a number is abbreviated as NaN. The following lines will generate NaN values:

##NaN
0/0
m <- c(2/3,3/3,0/0)
m

The is.finite, is.infinite, or is.nan functions will generate logical values (TRUE or FALSE).

is.finite(m)
is.infinite(m)
is.nan(m)

The following line will generate inf as a special value in R:

## infinite
k = 1/0

How it works…

complete.cases(z) is a logical vector indicating complete cases that have no missing value (NA). On the other hand, is.na(z) indicates which elements are missing. In both cases, the argument is our data, a vector, or a matrix.

R also allows its users to check if any element in a matrix or a vector is NA by using the anyNA() function. We can coerce or assign NA to any element of a vector using the square brackets ([ ]). The [3] input instructs R to assign NA to the third element of the dk vector.