Eliminate rows using multiple if clauses

user_19594729 0
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Suppose we have the following database:

ID   x   y    
1    23  -3  
2    2   51  
3    -2  45  
4    NA   2  
5    NA  -2  
6    NA  NA

I want to eliminate all the rows with negative values on the columns x and y, but I want to keep the NAs (that are written as the special value in R).

The result should be the following:

ID   x   y    
2    2   51    
4    NA   2   
6    NA  NA

I have tried using:

database <- database[!(database$x < 0 && database$x != "NA" || database$y < 0 && database$y != "NA")]

But it does not work, as it gives the error

'length(x) = 2 > 1' in coercion to 'logical(1)'

Which, from what I have seen, should be a problem of the new R version. I have also tried using !is.na(), and substituting && and || to & and |, but it doesn't work.

Does anyone know how to solve this issue?

dataframe r
1 Answers

In your code, you are doing double negation, which is not necessary. Just flip the sign in the comparison statement (i.e. database$x < 0 to database$x > 0). Also, to index a dataframe, you need database[row, column], where in your code, you are missing the index for column.

database[(database$x > 0 | is.na(database$x)) & (database$y > 0 | is.na(database$y)),]

Or with the package dplyr:

library(dplyr)

database %>% filter(if_all(x:y, ~ .x >0 | is.na(.x)))

Output

  ID  x  y
2  2  2 51
4  4 NA  2
6  6 NA NA
user_166474960
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