根据另一个变量给出的阈值过滤值

Question

在下面的示例中，我尝试创建一个“输出”列，其中对于每个 ID，当 B == apple 时，对于优于或等于 A 值的所有 A 值，输出 == 1（否则为 0） .

df1 <- data.frame(ID = c("a", "a", "a", "b", "b", "b", "b", "c", "c", "c"), A = c(2, 1, 8, 4, 3, 12, 9, 142, 13, 8), B = c("apple"
, "orange", "kiwi", "orange", "apple", "kiwi", "pear", "kiwi", "apple", "orange"), output = c(1, 0, 1, 1, 1, 1, 1, 1, 1, 0))


df1
   ID   A      B output
1   a   2  apple      1
2   a   1 orange      0
3   a   8   kiwi      1
4   b   4 orange      1
5   b   3  apple      1
6   b  12   kiwi      1
7   b   9   pear      1
8   c 142   kiwi      1
9   c  13  apple      1
10  c   8 orange      0

我能想到的最好的办法是使用base-R

df1$A >= df1$A[df1$B== "apple" & df1$ID == "a"]

，但我无法弄清楚这里要遵循的逻辑...

理想情况下，我正在寻找 tidyverse 解决方案，但 base-R 解决方案也可以。

提前非常感谢！

Answer 1

尝试

split

> split(df1, ~ID) |> 
+   lapply(\(x) transform(x, out1=+with(x, A >= A[B == 'apple']))) |> 
+   do.call(what='rbind')
     ID   A      B output out1
a.1   a   2  apple      1    1
a.2   a   1 orange      0    0
a.3   a   8   kiwi      1    1
b.4   b   4 orange      1    1
b.5   b   3  apple      1    1
b.6   b  12   kiwi      1    1
b.7   b   9   pear      1    1
c.8   c 142   kiwi      1    1
c.9   c  13  apple      1    1
c.10  c   8 orange      0    0