R 匹配两个数据帧并替换其中一个数据帧中的相应条目

我有以下两个数据帧：

df = data.frame(From=c("Mike","Elena","Mike","Mark","Alice","Joana"),
                To=c("Jasmine","Mariah","Erik","Jack","Joana","Mike"),
                Number=1:6, stringsAsFactors = FALSE)
df2 = data.frame(ID=c("1738799","657940","13253","97980","6569874","64839","8494","2773"), 
                 Name=c("Mike","Elena","Mark","Alice","Joana","Mariah","Erik","Jack"),
                 stringsAsFactors = FALSE)

数据帧

df2

包含与

df

中大多数名称相关联的

ID

。我想用相应的

ID

替换

df

中的名称。这样：

> df
  From             To   Number
  1738799     Jasmine        1
  657940        64839        2
  1738799        8494        3
  13253          2773        4
  97980       6569874        5
  6569874     1738799        6

---

在base R中，您可以执行以下操作：

df3 <- df
nms <- do.call(setNames, unname(df2))
df3[1:2]<- lapply(df[1:2], function(x) ifelse(is.na(a<-nms[x]), x, a))
df3
     From      To Number
1 1738799 Jasmine      1
2  657940   64839      2
3 1738799    8494      3
4   13253    2773      4
5   97980 6569874      5
6 6569874 1738799      6

---

df3您还可以使用以下
tidyverse
解决方案：

library(dplyr)
library(purrr)


df %>%
  map_if(~ is.character(.x), ~ ifelse(!is.na(match(.x, df2$Name)),
                                      str_replace(., .x, df2$ID[match(.x, df2$Name)]), 
                                      .x)) %>%
  bind_cols()


# A tibble: 6 x 3
  From    To      Number
  <chr>   <chr>    <int>
1 1738799 Jasmine      1
2 657940  64839        2
3 1738799 8494         3
4 13253   2773         4
5 97980   6569874      5
6 6569874 1738799      6

库（dplyr）
图书馆（purrr）
df%>%
map_if（~is.character（.x），~ifelse（！is.na（match（.x，df2$Name）），
str_replace（，.x，df2$ID[匹配（.x，df2$Name）]，
.x））%>%
bind_cols（）
#一个tibble:6x3
从到数字
1738799茉莉花1
2 657940  64839        2
3 1738799 8494         3
4 13253   2773         4
5 97980   6569874      5
6 6569874 1738799      6
我们可以在
tidyverse

library(dplyr)
library(tibble)
df %>%
    mutate(across(From:To, ~ coalesce(deframe(df2[2:1])[.], .)))
#     From      To Number
#1 1738799 Jasmine      1
#2  657940   64839      2
#3 1738799    8494      3
#4   13253    2773      4
#5   97980 6569874      5
#6 6569874 1738799      6


或者使用
baser
（
r4.1.0
）

基本R选项

transform(
  df,
  To = with(df2, {
    m <- ID[match(To, Name)]
    ifelse(is.na(m), To, m)
  })
)

df
#     From      To Number
#1 1738799 Jasmine      1
#2  657940   64839      2
#3 1738799    8494      3
#4   13253    2773      4
#5   97980 6569874      5
#6 6569874 1738799      6

transform(
  df,
  To = with(df2, {
    m <- ID[match(To, Name)]
    ifelse(is.na(m), To, m)
  })
)

   From      To Number
1  Mike Jasmine      1
2 Elena   64839      2
3  Mike    8494      3
4  Mark    2773      4
5 Alice 6569874      5
6 Joana 1738799      6