Using dplyr to filter on multiple columns

Question

I'm stumped on something that seems so silly. Is there an elegant dplyr way to filter out only the 2 rows where year == 2020 and quarter %in% 1:2.

I don't want to filter quarter for any other year besides 2020.

library(tibble)
library(dplyr)

df <- tibble(measure = rep(letters[1:4], 4),
             year = rep(2017:2020,4)) %>% 
  arrange(year) %>% 
  mutate(quarter = rep(1:4, 4))

df2 <- filter(df, measure != 2020 & quarter %in% 1:2)

^{Created on 2021-02-01 by the reprex package (v0.3.0)}

What i want is all but the last two rows:

```df2 <- filter(df, measure != 2020 & quarter %in% 1:2) ``` change 'measure' to 'year' ? — sophocles, Feb 01 '21 at 17:50
Does this answer your question? [dplyr filter with condition on multiple columns](https://stackoverflow.com/questions/43938863/dplyr-filter-with-condition-on-multiple-columns) — tjebo, Feb 01 '21 at 18:09

score 4 · Accepted Answer · answered Feb 01 '21 at 17:56

Try negating the entire expression of what you don't want:

dplyr::filter(df, !(year == 2020 & quarter %in% 1:2))

   measure year quarter
1        a 2017       1
2        a 2017       2
3        a 2017       3
4        a 2017       4
5        b 2018       1
6        b 2018       2
7        b 2018       3
8        b 2018       4
9        c 2019       1
10       c 2019       2
11       c 2019       3
12       c 2019       4
13       d 2020       3
14       d 2020       4

year == 2020 & quarter %in% 1:2 says to keep rows where the year is 2020 AND quarter is 1 or 2. The ! negates the entire expression so you exclude those rows.

FYI, you can also use dplyr::between(quarter, 1, 2)

Thank you, exactly what i needed! – laBouz Feb 01 '21 at 18:39 — laBouz, Feb 01 '21 at 18:39

Using dplyr to filter on multiple columns

1 Answers1