根据另一个数据框中的一组规则在数据框中创建一组变量

Question

这个问题听起来有点笼统，但我认为一个例子会更清楚：

我有以下两个数据框

数据1

group1     group2       group3     Level 
cat         cat          dog        1
dog         parrot       cat        1
mouse       dolphin      dolphin    1
red         blue         blue       2
green       yellow       green      2
black       purple       cat        2

数据2

var1        level    Score
cat           1        1
dog           1        1
mouse         1        1
dolphin       1        0
parrot        1        1
red           2        1
blue          2        1
green         2        1
purple        2        1
cat           2        0
black         2        0
yellow        2        1

我想修改 data1，其中包含 3 个新列(每个组 1、组 2 和组 3 一个(，根据"级别"的水平(级别是一个因素(，我在 data2 的"分数"列中找到的值。所以基本上我想获得这样的东西：

group1     group2       group3     Level      var1     var2     var3
cat         cat          dog        1          1        1        1
dog         parrot       cat        1          1        1        1
mouse       dolphin      dolphin    1          1        0        0
red         blue         blue       2          1        1        1
green       yellow       green      2          1        1        1
black       purple       cat        2          0        1        0

---

示例数据

df1 <- structure(list(
group1 = c("cat", "dog", "mouse", "red", "green", "black"),
group2 = c("cat", "parrot", "dolphin", "blue", "yellow", "purple"),
group3 = c("dog", "cat", "dolphin", "blue", "green", "cat"),
Level = structure(c(1L, 1L, 1L, 2L, 2L, 2L), .Label = c("1", "2"), class = "factor")),
row.names = c(NA, -6L), class = "data.frame")
df2 <- structure(list(
var1 = c("cat", "dog", "mouse", "dolphin", "parrot", "red", "blue", "green", "purple", "cat", "black", "yellow"),
level = structure(c(1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("1", "2"), class = "factor"),
Score = c(1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 1L)),
row.names = c(NA, -12L), class = "data.frame")

Answer 1

我们可以将第一个数据集透视为"long"格式，与第二个数据集连接，然后将其透视回"宽"格式

library(dplyr)
library(tidyr)
library(stringr)
df1 %>%
mutate(rn = row_number()) %>%
pivot_longer(cols  = -c(rn, Level), values_to = 'var1') %>% 
rename(level = Level) %>% 
left_join(df2) %>% 
mutate(name = str_replace(name, 'group', 'varn')) %>% 
na.omit %>%
select(-level, -var1) %>% 
pivot_wider(names_from = name, values_from = Score, values_fill = list(Score = 0)) %>% 
select(-rn) %>% 
bind_cols(df1, .)
#   group1  group2  group3 Level varn1 varn2 varn3
#1    cat     cat     dog     1     1     1     1
#2    dog  parrot     cat     1     1     0     1
#3  mouse dolphin dolphin     1     1     0     0
#4    red    blue    blue     2     1     1     1
#5  green  yellow   green     2     1     0     1
#6  black  purple     cat     2     0     1     0

Answer 2

我按purrr::reduce()递归地将df2合并到df1三次。在这一部分中，我复制了df2三次，并分别更改了它们的第一列名称以匹配df1列名称。

library(tidyverse)
df2 %>%
list %>% rep(3) %>%
imap(~ setNames(.x, c(str_c("group", .y), "Level", str_c("Score", .y)))) %>%
reduce(left_join, .init = df1)
#   group1  group2  group3 Level Score1 Score2 Score3
# 1    cat     cat     dog     1      1      1      1
# 2    dog  parrot     cat     1      1      1      1
# 3  mouse dolphin dolphin     1      1      0      0
# 4    red    blue    blue     2      1      1      1
# 5  green  yellow   green     2      1      1      1
# 6  black  purple     cat     2      0      1      0