Missing values in R are represented by NA. You can test for NA values with the is.na() function.
x <- c(1, 26, NA, 74, NA)
is.na(x)
#> [1] FALSE FALSE TRUE FALSE TRUE
Created on 2020-04-22 by the reprex package (v0.3.0)
The logical vector returned by this function can be used to subset your data frame.
However, missing values must always be handled with caution. Blindly removing all observations with missing data may result in large chunks of your dataset being eliminated.
Very often, it's important to understand the cause underlying the 'missingness'. The missing values may be unrepresented categories or other information that might be valuable in a machine learning context. The resource below describes different types of missing data and how it should be handled. Hope it helps.