下面是我的两个数据帧，df1和df2
df1 <- data.frame(id=c("632592651","633322173","634703802","634927873","635812953","636004739","636101211","636157799","636263106","636752420"),text=c("asdf","cat","dog","mouse","elephant","goose","rat","mice","kitty","kitten"),response=c("y","y","y","n","n","y","y","n","n","y"))
id text response
1 632592651 asdf y
2 633322173 cat y
3 634703802 dog y
4 634927873 mouse n
5 635812953 elephant n
6 636004739 goose y
7 636101211 rat y
8 636157799 mice n
9 636263106 kitty n
10 636752420 kitten y
df2 <- data.frame(id=c("632592651","633322173","634703802","634927873","635812953","636004739","636101211","636157799","636263106","636752420","636809222","2004722036","2004894388","2005045755","2005535472","2005630542","2005788781","2005809679","2005838317","2005866692"),
text=c("asdf_xyz","cat","dog","mouse","elephant","goose","rat","mice","kitty","kitten","tiger_xyz","lion","leopard","ostrich","kangaroo","platypus","fish","reptile","mammals","amphibians_xyz"),
volume=c("1234","432","324","333","2223","412346","7456","3456","2345","2345","6","345","23","2","4778","234","8675","3459","8","9"))
id text volume
1 632592651 asdf_xyz 1234
2 633322173 cat 432
3 634703802 dog 324
4 634927873 mouse 333
5 635812953 elephant 2223
6 636004739 goose 412346
7 636101211 rat 7456
8 636157799 mice 3456
9 636263106 kitty 2345
10 636752420 kitten 2345
11 636809222 tiger_xyz 6
12 2004722036 lion 345
13 2004894388 leopard 23
14 2005045755 ostrich 2
15 2005535472 kangaroo 4778
16 2005630542 platypus 234
17 2005788781 fish 8675
18 2005809679 reptile 3459
19 2005838317 mammals 8
20 2005866692 amphibians_xyz 9
如何将不匹配项从df2的id1:20行更改为NA(即所有项都与df1不匹配)，并将id1的"text"(即asdf\u xyz)列更改为NA？
我试过了
library(dplyr)
df3 <- df2 %>%
anti_join(df1, by=c("id"))
id text volume
1 636809222 tiger_xyz 6
2 2004722036 lion 345
3 2004894388 leopard 23
4 2005045755 ostrich 2
5 2005535472 kangaroo 4778
6 2005630542 platypus 234
7 2005788781 fish 8675
8 2005809679 reptile 3459
9 2005838317 mammals 8
10 2005866692 amphibians_xyz 9
df3$id[df3$id != 0] <- NA
df3$text[df3$text != 0] <- NA
df3$volume[df3$volume != 0] <- NA
(一个接一个地这样做，因为我找不到如何将数据帧的整个值更改为NA的解决方案)
id text volume
1 <NA> <NA> <NA>
2 <NA> <NA> <NA>
3 <NA> <NA> <NA>
4 <NA> <NA> <NA>
5 <NA> <NA> <NA>
6 <NA> <NA> <NA>
7 <NA> <NA> <NA>
8 <NA> <NA> <NA>
9 <NA> <NA> <NA>
10 <NA> <NA> <NA>
and df4 (solution from How to return row values that match column 'id' in both df1 and df2 but not column 'text' and return NA to the mismatch in column 'text'?)
inner_join(x = df1,
y = df2,
by = "id") %>%
mutate_if(is.factor, as.character) %>%
mutate(text = ifelse(test = text.x != text.y,
yes = NA,
no = text.x)) %>%
select(id, text, response, volume)
id text response volume
1 632592651 <NA> y 1234
2 633322173 cat y 432
3 634703802 dog y 324
4 634927873 mouse n 333
5 635812953 elephant n 2223
6 636004739 goose y 412346
7 636101211 rat y 7456
8 636157799 mice n 3456
9 636263106 kitty n 2345
10 636752420 kitten y 2345
但不确定如何用df3和df4替换df2.所需输出如下所示:
id text volume
1 632592651 NA 1234
2 633322173 cat 432
3 634703802 dog 324
4 634927873 mouse 333
5 635812953 elephant 2223
6 636004739 goose 412346
7 636101211 rat 7456
8 636157799 mice 3456
9 636263106 kitty 2345
10 636752420 kitten 2345
11 NA NA NA
12 NA NA NA
13 NA NA NA
14 NA NA NA
15 NA NA NA
16 NA NA NA
17 NA NA NA
18 NA NA NA
19 NA NA NA
20 NA NA NA
有人能帮忙吗？
第2部分:
对于我请求的第二部分，我想从joined\u df创建另一个数据帧，它只出现在df1中(称为found\u in\u df1).输出示例:
在_df1中找到_:
# id text volume
# 1: 632592651 <NA> 1234
# 2: 633322173 cat 432
# 3: 634703802 dog 324
# 4: 634927873 mouse 333
# 5: 635812953 elephant 2223
# 6: 636004739 goose 412346
# 7: 636101211 rat 7456
# 8: 636157799 mice 3456
# 9: 636263106 kitty 2345
#10: 636752420 kitten 2345
The solution is given in How to return row values that match column 'id' in both df1 and df2 but not column 'text' and return NA to the mismatch in column 'text'? but I'm looking for an alternative approach, i.e., is it possible to write a script to say retrieve from joined_df using df1 to give found_in_df1 since we have df1 and joined_df?