When working with the data, sooner or later (rather sooner) you need a way to choose a subset. It can be based on some logical condition, specific index or some sampling technique.
This scenario provides you with R capabilities of filtering data from simple collections to data frames.
Filtering data in R
When working with the vector data there is a simple way to use logical condition to filter it.
Let us create a vector of sequential numbers:
a <- 1:10
To get only values larger than 4
 should be used for the condition:
a[a > 4]
The same rule could be applied to the char vector and the condition of strings of the length 2.
b <- c("ab", "bc", "abc", "ac", "def")
b[nchar(b) == 2]
Conditions and parenthesis can be used for lists too. Just remember that because list can store elements of different types, the condition needs to make sense for all of them.
A <- as.list(1:10)
A[A > 4]