r - 仅当特定条件有效时如何在 R 中进行过滤？

Question

我有一个包含组的数据集——“A”、“B”、“C”和“A & B”——在两个时间点——“之前”和“之后”。如果任一时间点 A 或 B 的样本量低于 10 人，我只想包括“A 和 B”。否则，我想删除“A & B”组。我如何告诉 R 仅在满足其他条件时才删除该组？

这里有两个样本数据集——一个应该过滤掉 A 组和 B 组，另一个应该保留它:

library(dplyr)

#This should not filter out anything

should_not_drop_group <- tibble(group = rep(c("A", "B", "C", "A & B"), 2),
                    time = c(rep(c("Before"), 4), rep(c("After"), 4)),
                    sample_size = c(5, 100, 132, 105, 250, 50, 224, 300))


#This dataset should drop group A&B

should_drop_group <- tibble(group = rep(c("A", "B", "C", "A & B"), 2),
                                                  time = c(rep(c("Before"), 4), rep(c("After"), 4)),
                                                  sample_size = c(500, 100, 132, 600, 250, 50, 224, 300))

这就是我尝试无济于事的原因:

library(dplyr)

should_drop_group %>%
  filter_if(~any(sample_size[group  %in% c("A", "B")] < 10), group != "A & B" )

Answer 1

也许 filter 中的条件是 - 子集 group 其中 sample_size 小于 10，检查是否有 该组中 'A'、'B' 的任何 值，求反 (!)，然后创建第二个表达式，其中 group 是“A & B” , 用 & 连接它们，然后否定 (!) 整个表达式以过滤掉那些情况

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，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