library(tibble)
df <- tibble(ID = c(100000L, 100000L, 100000L, 100000L, 100001L, 100001L, 100001L, 100001L, 100002L, 100002L, 100002L, 100002L, 100003L, 100003L, 100003L), subject_result2 = c("OTHERPassedTerm1", "OTHERPassedTerm1", "OTHERPassedTerm1", "MATHPassedTerm1", "OTHERPassedTerm1", "OTHERPassedTerm1", "OTHERPassedTerm1", "OTHERFailedTerm1", "OTHERPassedTerm1", "OTHERPassedTerm1", "MATHPassedTerm1", "MATHFailedTerm1", "OTHERPassedTerm1", "MATHPassedTerm1", "OTHERPassedTerm1"))
# A tibble: 15 x 2
ID subject_result2
<int> <chr>
1 100000 OTHERPassedTerm1
2 100000 OTHERPassedTerm1
3 100000 OTHERPassedTerm1
4 100000 MATHPassedTerm1
5 100001 OTHERPassedTerm1
6 100001 OTHERPassedTerm1
7 100001 OTHERPassedTerm1
8 100001 OTHERFailedTerm1
9 100002 OTHERPassedTerm1
10 100002 OTHERPassedTerm1
11 100002 MATHPassedTerm1
12 100002 MATHFailedTerm1
13 100003 OTHERPassedTerm1
14 100003 MATHPassedTerm1
15 100003 OTHERPassedTerm1
subject_result2
基于每个
ID
. 类似于下面的内容,但此代码不起作用
library(dplyr)
df %>%
group_by(ID) %>%
distinct(subject_result2)
你能解决我的问题吗?谢谢
预期结果:
# <int> <chr>
#1 100000 OTHERPassedTerm1
#2 100000 MATHPassedTerm1
#3 100001 OTHERPassedTerm1
#4 100001 OTHERFailedTerm1
#5 100002 OTHERPassedTerm1
#6 100002 MATHPassedTerm1
#7 100002 MATHFailedTerm1
#8 100003 OTHERPassedTerm1
#9 100003 MATHPassedTerm1