R - 在两组列中搜索两个条件

Question

我有一个名为 fruits 的数据框，其中每行最多有 3 个具有相应颜色的水果。 Color1 与 Fruit1 搭配，Color2 与 Fruit2 搭配，Color3 与 Fruit3 搭配。

  Color1 Color2 Color3 Fruit1 Fruit2 Fruit3
1    red  green  green  apple  mango   kiwi
2 yellow  green    red banana   plum  mango
3  green    red         grape  apple       
4 yellow                apple              

使用 dplyr，我可以返回包含苹果的行（1、3 和 4）。我可以返回带有红色（1、2 和 3）的行。

red <- filter_at(fruits, vars(Color1:Color3), any_vars(. == "red"))
apple <- filter_at(fruits, vars(Fruit1:Fruit3), any_vars(. == "apple"))

但是我如何只返回红苹果，即只返回第一行（Color1 = red，Fruit1 = apple）和第三行（Color2 = red，Fruit2 = apple）？

谢谢。

附言这是表格的代码

Color1 <- c("red", "yellow", "green", "yellow")
Color2 <- c("green", "green", "red", "")
Color3 <- c("green", "red", "", "")
Fruit1 <- c("apple", "banana", "grape", "apple")
Fruit2 <- c("mango", "plum", "apple", "")
Fruit3 <- c("kiwi", "mango", "", "")

fruits <- data.frame (Color1, Color2, Color3, Fruit1, Fruit2, Fruit3)

Answer 1

这是使用 tidyverse/purrr 的替代解决方案：

这将匹配以相同数字结尾的列（即Color1 和Fruit1、Color20 和Fruit20）

假设每种颜色都有匹配的水果，否则索引（.[1] 和 .[2] 将失败）。如果需要，您还可以将“red”和“apple”替换为不同的值。

subset_func <- function(data, num) {
  
  out <- data %>% 
    mutate(id = row_number()) %>% 
    select(id, ends_with(num)) %>% 
    filter(.[2] == "red" & .[3] == "apple") 

  data %>% 
    mutate(id = row_number()) %>% 
    filter(id %in% out$id) %>% 
    select(-id)
  
}

map_df(as.character(1:3), ~subset_func(fruits, .)) 

这给了我们：

  Color1 Color2 Color3 Fruit1 Fruit2 Fruit3
1    red  green  green  apple  mango   kiwi
3  green    red      .  grape  apple      .

Answer 2

我觉得您的数据可能不太理想。 （不是tidy）。

如果您先整理数据，您尝试完成的任务可能会更容易。

library(tidyverse)
Color1 <- c("red", "yellow", "green", "yellow") 
Color2 <- c("green", "green", "red", "") 
Color3 <- c("green", "red", "", "") 
Fruit1 <- c("apple", "banana", "grape", "apple") 
Fruit2 <- c("mango", "plum", "apple", "") 
Fruit3 <- c("kiwi", "mango", "", "") 
fruits <- data.frame (Color1, Color2, Color3, Fruit1, Fruit2, Fruit3) 

long_fruits <- fruits %>% 
  ## following r2evans suggestion to include row identifier in order to allow re-pivoting if needed
  rownames_to_column("row_id") %>%
  pivot_longer(-"row_id", names_to = c(".value", "ID"), names_pattern = "(\\w+)(\\d+)")

long_fruits
#> # A tibble: 12 × 4
#>    row_id ID    Color    Fruit   
#>    <chr>  <chr> <chr>    <chr>   
#>  1 1      1     "red"    "apple" 
#>  2 1      2     "green"  "mango" 
#>  3 1      3     "green"  "kiwi"  
#>  4 2      1     "yellow" "banana"
#>  5 2      2     "green"  "plum"  
#>  6 2      3     "red"    "mango" 
#>  7 3      1     "green"  "grape" 
#>  8 3      2     "red"    "apple" 
#>  9 3      3     ""       ""      
#> 10 4      1     "yellow" "apple" 
#> 11 4      2     ""       ""      
#> 12 4      3     ""       ""

long_fruits %>%
  filter(Fruit == "apple", Color == "red")
#> # A tibble: 2 × 4
#>   row_id ID    Color Fruit
#>   <chr>  <chr> <chr> <chr>
#> 1 1      1     red   apple
#> 2 3      2     red   apple

^{由reprex package (v2.0.1) 于 2021 年 12 月 21 日创建}

Answer 3

您可以独立处理列集，创建逻辑矩阵，然后将它们与& 进行逻辑组合。

前期：

• 如果您的数据中有NA 值，则需要一些模组才能正常工作；
• 这假定所有列的顺序相同；例如，如果您的列的顺序是“Color1, Color2, Color3”和“Fruit3, Fruit2, Fruit1”，那么这将无法正确配对。

假设dplyr：

select(fruits, starts_with("Color")) == "red"
#   Color1 Color2 Color3
# 1   TRUE  FALSE  FALSE
# 2  FALSE  FALSE   TRUE
# 3  FALSE   TRUE  FALSE
# 4  FALSE  FALSE  FALSE
select(fruits, starts_with("Fruit")) == "apple"
#   Fruit1 Fruit2 Fruit3
# 1   TRUE  FALSE  FALSE
# 2  FALSE  FALSE  FALSE
# 3  FALSE   TRUE  FALSE
# 4   TRUE  FALSE  FALSE
select(fruits, starts_with("Color")) == "red" & select(fruits, starts_with("Fruit")) == "apple"
#   Color1 Color2 Color3
# 1   TRUE  FALSE  FALSE
# 2  FALSE  FALSE  FALSE
# 3  FALSE   TRUE  FALSE
# 4  FALSE  FALSE  FALSE

从这里开始，

fruits %>%
  filter(
    rowSums(
      select(., starts_with("Color")) == "red" &
        select(., starts_with("Fruit")) == "apple"
    ) > 0)
#   Color1 Color2 Color3 Fruit1 Fruit2 Fruit3
# 1    red  green  green  apple  mango   kiwi
# 3  green    red      .  grape  apple      .

---

数据。因为我一开始没有你的，所以我首先用. 制作了这个（因为阅读空栏比我最初有时间花费更多的精力）。

fruits <- structure(list(Color1 = c("red", "yellow", "green", "yellow"), Color2 = c("green", "green", "red", "."), Color3 = c("green", "red", ".", "."), Fruit1 = c("apple", "banana", "grape", "apple"), Fruit2 = c("mango", "plum", "apple", "."), Fruit3 = c("kiwi", "mango", ".", ".")), class = "data.frame", row.names = c("1", "2", "3", "4"))