仅当某个条件有效时如何在 R 中过滤

可能filter中的条件是-将sample_size小于10的group子集，判断该组中是否有any个"A"、"B"值，取反(!)，然后创建第二个表达式，其中group是"A&B"，将它们与&连接，然后取反(!)整个表达式以过滤掉这些情况

library(dplyr)
should_not_drop_group %>% 
   filter(!(!any(c("A", "B") %in% group[sample_size < 10]) & group == "A & B"))
   # or can be written as
   #filter(!(!any(group %in% c("A", "B") & sample_size < 10) & group == "A & B"))

-输出

# A tibble: 8 × 3
  group time   sample_size
  <chr> <chr>        <dbl>
1 A     Before           5
2 B     Before         100
3 C     Before         132
4 A & B Before         105
5 A     After          250
6 B     After           50
7 C     After          224
8 A & B After          300

第二种情况

should_drop_group %>% 
    filter(!(!any(c("A", "B") %in% group[sample_size < 10]) & group == "A & B"))
# A tibble: 6 × 3
  group time   sample_size
  <chr> <chr>        <dbl>
1 A     Before         500
2 B     Before         100
3 C     Before         132
4 A     After          250
5 B     After           50
6 C     After          224

如果我们想在多个数据集上重用它，那么创建一个函数并重用它

> f1 <- function(x, sample_size) 
   !(!any(c("A", "B") %in% x[sample_size < 10]) & x == "A & B")
> should_not_drop_group %>% 
   filter(if_any(group, f1, sample_size = sample_size))
# A tibble: 8 × 3
  group time   sample_size
  <chr> <chr>        <dbl>
1 A     Before           5
2 B     Before         100
3 C     Before         132
4 A & B Before         105
5 A     After          250
6 B     After           50
7 C     After          224
8 A & B After          300
> should_drop_group %>% 
   filter(if_any(group, f1, sample_size = sample_size))
# A tibble: 6 × 3
  group time   sample_size
  <chr> <chr>        <dbl>
1 A     Before         500
2 B     Before         100
3 C     Before         132
4 A     After          250
5 B     After           50
6 C     After          224