I am trying to delete specific rows in my dataset based on values in multiple columns. A row should be deleted only when a condition in all 3 columns is met.
This is my code:
test_dff %>%
filter(contbr_nm != c('GAITHER, BARBARA', 'PANIC, RADIVOJE', 'KHAN, RAMYA') &
contbr_city != c('APO AE', 'PORSGRUNN', 'NEW YORK') &
contbr_zip != c('9309', '3924', '2586'))
This code should remove 12 rows in my table. Instead it removes a vast majority of them. I am suspecting, that it removes all the possible rows, whenever one of the conditions is met.
Is there a better solution, or do I have to use the approach, described here?
Do I need to specify each combination separately? Like so? This approach also deletes far too many rows, so it is also wrong.
test_dff %>%
filter((contbr_nm != 'GAITHER, BARBARA' & contbr_city != 'APO AE' & contbr_zip != '9309') &
(contbr_nm != 'PANIC, RADIVOJE' & contbr_city != 'PORSGRUNN' & contbr_zip != '3924') &
(contbr_nm != 'KHAN, RAMYA' & contbr_city != 'NEW YORK' & contbr_zip != '2586') )
If I focus on deleting rows only based on one variable, this piece of code works:
test_dff %>%
filter(contbr_zip != c('9309')) %>%
filter(contbr_zip != c('3924')) %>%
filter(contbr_zip != c('2586'))
Why does such an approach not work?
test_dff %>%
filter(contbr_zip != c('9309','3924','2586'))
Thanks a lot for your help.
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