R-基于多个条件匹配来自2个数据帧的值(当查找ID的顺序是随机的时)
嗨,我有两个数据帧:R-基于多个条件匹配来自2个数据帧的值(当查找ID的顺序是随机的时),r,data-manipulation,data-cleaning,R,Data Manipulation,Data Cleaning,嗨,我有两个数据帧: df1 = data.frame(PersonId1=c(1,2,3,4,5,6,7,8,9,10,1),PersonId2=c(11,12,13,14,15,16,17,18,19,20,11), Played_together = c(1,0,0,1,1,0,0,0,1,0,1), Event=c(1,1,1,1,2,2,2,2,2,2,2), Utility=c(20,-2,-5,10,30
df1 = data.frame(PersonId1=c(1,2,3,4,5,6,7,8,9,10,1),PersonId2=c(11,12,13,14,15,16,17,18,19,20,11),
Played_together = c(1,0,0,1,1,0,0,0,1,0,1),
Event=c(1,1,1,1,2,2,2,2,2,2,2),
Utility=c(20,-2,-5,10,30,2,1,.5,50,-1,60))
df2 = data.frame(PersonId1=c(11,15,9,1),PersonId2=c(1,5,19,11),
Played_together = c(1,1,1,1),
Event=c(1,2,2,2))
其中,df1如下所示:
PersonId1 PersonId2 Played_together Event Utility
1 1 11 1 1 20.0
2 2 12 0 1 -2.0
3 3 13 0 1 -5.0
4 4 14 1 1 10.0
5 5 15 1 2 30.0
6 6 16 0 2 2.0
7 7 17 0 2 1.0
8 8 18 0 2 0.5
9 9 19 1 2 50.0
10 10 20 0 2 -1.0
11 1 11 1 2 60.0
PersonId1 PersonId2 Played_together Event
1 11 1 1 1
2 15 5 1 2
3 9 19 1 2
4 1 11 1 2
PersonId1 PersonId2 Played_together Event Utility
1 11 1 1 1 20
2 15 5 1 2 30
3 9 19 1 2 50
4 1 11 1 2 60
df2看起来是这样的:
PersonId1 PersonId2 Played_together Event Utility
1 1 11 1 1 20.0
2 2 12 0 1 -2.0
3 3 13 0 1 -5.0
4 4 14 1 1 10.0
5 5 15 1 2 30.0
6 6 16 0 2 2.0
7 7 17 0 2 1.0
8 8 18 0 2 0.5
9 9 19 1 2 50.0
10 10 20 0 2 -1.0
11 1 11 1 2 60.0
PersonId1 PersonId2 Played_together Event
1 11 1 1 1
2 15 5 1 2
3 9 19 1 2
4 1 11 1 2
PersonId1 PersonId2 Played_together Event Utility
1 11 1 1 1 20
2 15 5 1 2 30
3 9 19 1 2 50
4 1 11 1 2 60
请注意,df2并不是简单地df1$一起玩==1。(对于eg PlayerId1=4和PlayerId2=14,df2中不存在
还要注意,虽然df2是df1的子集,但个体在df2中出现的顺序是随机的。例如,在第1行的df1中,我们看到事件1的playerid1=1和playerId2=11。但是在第1行的df2中,我们看到事件1的playerid1=11和playerId2=1。这两种情况完全相同,我想查找一下实用程序的值从df1到df2。必须对每个事件进行合并。最终输出应如下所示:
PersonId1 PersonId2 Played_together Event Utility
1 1 11 1 1 20.0
2 2 12 0 1 -2.0
3 3 13 0 1 -5.0
4 4 14 1 1 10.0
5 5 15 1 2 30.0
6 6 16 0 2 2.0
7 7 17 0 2 1.0
8 8 18 0 2 0.5
9 9 19 1 2 50.0
10 10 20 0 2 -1.0
11 1 11 1 2 60.0
PersonId1 PersonId2 Played_together Event
1 11 1 1 1
2 15 5 1 2
3 9 19 1 2
4 1 11 1 2
PersonId1 PersonId2 Played_together Event Utility
1 11 1 1 1 20
2 15 5 1 2 30
3 9 19 1 2 50
4 1 11 1 2 60
我知道R中存在合并函数,但我不知道当查找ID显示为随机时该怎么办。如果有人能帮我一点忙,我将不胜感激。提前感谢。以下是我为您准备的:
library(dplyr)
rbind(left_join(df2, df1,
by = c("PersonId2" = "PersonId1", "PersonId1" = "PersonId2",
"Played_together" = "Played_together", "Event" = "Event")),
left_join(df2, df1,
by = c("PersonId1" = "PersonId1", "PersonId2" = "PersonId2",
"Played_together" = "Played_together", "Event" = "Event"))) %>%
filter(!is.na(Utility))
基本上,您的数据有时会翻转personid。我们可以将两个连接绑定在一起,然后过滤掉那些具有实用程序NA
的行
您的输出如下所示:
PersonId1 PersonId2 Played_together Event Utility
1 11 1 1 1 20
2 15 5 1 2 30
3 9 19 1 2 50
4 1 11 1 2 60
一个解决方案是使用PersonId1
和PersonId2
的组合创建一个“团队”列,这样它可以为两个团队创建min(PersonId):max(PersonId)
。现在,加入Team
和Event
上的df1
和df2
以获得所需的数据
library(dplyr)
df2 %>% rowwise() %>%
mutate(Team = paste0(min(PersonId1,PersonId2), ":",max(PersonId1,PersonId2))) %>%
inner_join(df1 %>% rowwise() %>%
mutate(Team =
paste0(min(PersonId1,PersonId2), ":",max(PersonId1,PersonId2))),
by = c("Team", "Event")) %>%
select(PersonId1 = PersonId1.x, PersonId2 = PersonId2.x,
Played_together = Played_together.x, Event, Utility) %>%
as.data.frame()
# PersonId1 PersonId2 Played_together Event Utility
# 1 11 1 1 1 20
# 2 15 5 1 2 30
# 3 9 19 1 2 50
# 4 1 11 1 2 60
@Adam Warner非常感谢你的回答。效果非常好。只是一个新手快速跟进问题-在你的代码中,哪一部分负责反向personid?@Prometheus只是一种变通方法,但是你可以看到第一个左键连接我指定hey match personid2为personid1,然后我绑定另一个未反向的连接。因此如果你o不要过滤掉NAs。在personid1没有反转的情况下,你会得到NA的实用值。明白了。出于某种原因,我漏掉了Personid2=personid1。这非常有用。谢谢