Question

我有一个数据表如下：

   user                time follow_group
1:    1 2017-09-01 00:01:01            1
2:    1 2017-09-01 00:01:20            1
3:    1 2017-09-01 00:03:01            1
4:    1 2017-09-01 00:10:01            2
5:    1 2017-09-01 00:11:01            2
6:    2 2017-09-01 00:01:03            1
7:    2 2017-09-01 00:01:08            1
8:    2 2017-09-01 00:03:01            1

由此我想为每个用户提供具有最高follow_group的所有记录

所以我做的是

data[max(follow_group), , by = list(user)]

但这给我一个错误

Error in `[.data.table`(data, max(follow_group),  : 
  'by' or 'keyby' is supplied but not j

感谢任何帮助。谢谢。

Answer 1

您可以使用data.table：

执行此操作

library(data.table)
setDT(df)[, .SD[follow_group == max(follow_group)], by = user]

或dplyr：

library(dplyr)
df %>%
  group_by(user) %>%
  filter(follow_group == max(follow_group))

<强>结果：

   user                time follow_group
1:    1 2017-09-01 00:10:01            2
2:    1 2017-09-01 00:11:01            2
3:    2 2017-09-01 00:01:03            1
4:    2 2017-09-01 00:01:08            1
5:    2 2017-09-01 00:03:01            1

# A tibble: 5 x 3
# Groups:   user [2]
   user                time follow_group
  <int>               <chr>        <int>
1     1 2017-09-01 00:10:01            2
2     1 2017-09-01 00:11:01            2
3     2 2017-09-01 00:01:03            1
4     2 2017-09-01 00:01:08            1
5     2 2017-09-01 00:03:01            1

数据：

df = structure(list(user = c(1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L), time = c("2017-09-01 00:01:01", "2017-09-01 00:01:20", "2017-09-01 00:03:01", "2017-09-01 00:10:01", "2017-09-01 00:11:01", "2017-09-01 00:01:03", "2017-09-01 00:01:08", "2017-09-01 00:03:01"), follow_group = c(1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L)), class = "data.frame", .Names = c("user", "time", "follow_group"), row.names = c(NA, -8L))

如何为每个组获取具有最大值的所有记录

1 个答案: