CODEWITHSUNDEEP
rfilterdplyr
Grig
Grig

Reputation: 119

Dataset filtering by single column and multiple factors

this is probably a simple question but I could not find a solution even after scouting for Q&A for a quite long time and reading all the cheat-sheets I could find.

Let's say I have the following dataset

participant <- c(1, 1, 2, 2, 3,3 ,4,4)
trial <- c(1, 2, 2, 3, 4, 2, 3, 4) 
page <- c(1, 2, 2, 5, 6, 2, 1, 2) 
test <- data.frame(participant, trial, page)

I want to remove from my dataset specific trials and/or pages within trials, for specific participants.

So, for example, let's assume I want to remove from my dataset Trial 2 and Page 2 for Participant 1 only.

I tried this, but it removes the participant completely

test <- dplyr::filter(test, participant != "1" & trial != "2" & page != "2")

How can I remove only values in relation to another value? Thanks!

Upvotes: 0

Views: 29

Answers (1)

divibisan
divibisan

Reputation: 12155

dplyr::filter only keeps rows for which the provided condition is true. Your thinking was correct that a simple way to do this is to make a conditional statement that matches the row you want to remove, and then invert it to select the other rows. The problem is the way inverting == to != interacts with the AND operator &

You give the condition participant != "1" & trial != "2" & page != "2" which is true only if ALL the following conditions are true (since you used &):

  • participant is not 1
  • trial is not 2
  • page is not 2

So if a row doesn't meet ANY of those criteria (for example, every row where participant == 1), it will be removed

Since you want to do is make a conditional statement that matches the rows you want to remove, and then invert it by using the NOT operator ! around the entire statement in parentheses:

dplyr::filter(test, !(participant == 1 & trial == 2 & page == 2))

  participant trial page
1           1     1    1
2           2     2    2
3           2     3    5
4           3     4    6
5           3     2    2
6           4     3    1
7           4     4    2

Upvotes: 1

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