如何仅按组将具有最低和最高值的行保留在特定列中？ [英] How do I only keep the rows with the lowest and highest value in a certain column, by groups?

问题描述

简而言之，我该怎么做

structure(list(id = c(1, 2, 3, 4, 5, 6), user = c(1, 1, 1, 2, 
2, 2), value = c(1, 3, 5, 2, 5, 9)), .Names = c("id", "user", 
"value"), row.names = c(NA, -6L), class = "data.frame")

对此？

structure(list(id = c(1, 3, 4, 6), user = c(1, 1, 2, 2), value = c(1, 
5, 2, 9)), .Names = c("id", "user", "value"), row.names = c(NA, 
-4L), class = "data.frame")

含义是，对于每个用户，只需保留与最低和最高值相对应的两行。

Meaning, for each user, need to keep only the two rows corresponding to the lowest and highest value.

如果可能的话，我想使用 dplyr 解决方案。否则，任何解决方案都可以。

I'd like a solution using dplyr, if possible. Otherwise, any solution is fine.

推荐答案

我们可以将 slice 与 which.min / which.max 按用户分组后

We can use slice with which.min/which.max after grouping by 'user'

library(dplyr)
df1 %>%
   group_by(user) %>%
   slice(c(which.min(value), which.max(value)))
#   id  user value
#  <dbl> <dbl> <dbl>
#1     1     1     1
#2     3     1     5
#3     4     2     2
#4     6     2     9

---

或者另一个选择是 arrange 和切片。按用户分组后，排列将值按升序排列，每个用户和切片的第一个最后一行

---

Or another option is arrange with slice. After grouping by 'user', arrange the 'value' in ascending for each 'user' and slice the first and last row

df1 %>% 
     group_by(user) %>%
     arrange(value) %>% 
     slice(c(1, n()))

---

如果存在最小值和/或最大值'值'并且想要保留所有 min 和 max 行，请使用 filter

---

If there are ties for min and/or max 'value' and wanted to keep all the min and max rows, use filter

df1 %>%
     group_by(user) %>% 
     filter(value %in% c(min(value), max(value)))

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