Difficulty: beginner
Estimated Time: 10 minutes

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.

You've completed Filtering data in R scenario.

You've learnt how to:

  • define logical condition
  • indexing
  • filtering

Find out about working with files in the in the next scenario of the course.

Don’t stop now! The next scenario will only take about 10 minutes to complete.

Filtering data in R

Step 1 of 7

Logical conditions

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 a

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 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[A > 4]