Dataframe 列循环和基于 R 中条件的字符串连接（pref dplyr）

Question

我有一个 2 列数据框。第一列包含 class 项的单个条目（在本例中为蔬菜）。第二列是进货 new_item，它们是不同类别的杂货（肉类、水果、蔬菜等）。

library(tidyverse)
current <- tibble::tribble(
             ~prev_veg,   ~new_item,
             "cabbage",   "lettuce",
                    NA,     "apple",
                    NA,     "beef",
                    NA,   "spinach",
                    NA,  "broccoli",
                    NA,     "mango"
             )
current

我想遍历新的项目列，只将蔬菜添加到 prev_veg。任何新的蔬菜项目都需要添加到现有列表中。重要的是，我有一个包含所有可能出现在该列表中的蔬菜的向量。所需的数据框如下。

target_veg <- c("cabbage","lettuce", "spinach", "broccoli"

    desired <- tibble::tribble(
      ~prev_veg,   ~new_item,
      "cabbage",   "lettuce",
      "cabbage, lettuce",     "apple",
      "cabbage, lettuce", "strawbery",
      "cabbage, lettuce",   "spinach",
      "cabbage, lettuce, spinach",  "broccoli",
      "cabbage, lettuce, spinach, broccoli",     "mango"
    )

desired

最后，这个数据框中还有多个其他数据列我没有包括在这里（只包括相关列）。请理想地寻找 dplyr 解决方案。

Answer 1

current <- tibble::tribble(
  ~prev_veg, ~new_item,
  "cabbage", "lettuce",
  NA, "apple",
  NA, "beef",
  NA, "spinach",
  NA, "broccoli",
  NA, "mango"
)
target_veg <- c("cabbage", "lettuce", "spinach", "broccoli")

library(dplyr, warn.conflicts = FALSE)
library(purrr)

current %>%
  mutate(
    prev_veg = accumulate(
      head(new_item, -1),
      ~ if_else(.y %in% target_veg, paste(.x, .y, sep = ", "), .x),
      .init = prev_veg[1]
    )
  )
#> # A tibble: 6 × 2
#>   prev_veg                            new_item
#>   <chr>                               <chr>   
#> 1 cabbage                             lettuce 
#> 2 cabbage, lettuce                    apple   
#> 3 cabbage, lettuce                    beef    
#> 4 cabbage, lettuce                    spinach 
#> 5 cabbage, lettuce, spinach           broccoli
#> 6 cabbage, lettuce, spinach, broccoli mango

^{由 reprex package (v2.0.1)}

于 2022-02-24 创建

Answer 2

这也可以通过使用 match 找到索引然后使用 rowwise 粘贴

来创建

library(dplyr)
library(tidyr)
current  %>%
   mutate(ind =  lag(match(new_item, target_veg))) %>% 
   fill(ind, .direction = "downup") %>%
   rowwise %>%
   mutate(ind = toString(target_veg[seq(ind)])) %>% 
   ungroup %>% 
   mutate(prev_veg = coalesce(prev_veg, ind), .keep = "unused")

-输出

# A tibble: 6 × 2
  prev_veg                            new_item
  <chr>                               <chr>   
1 cabbage                             lettuce 
2 cabbage, lettuce                    apple   
3 cabbage, lettuce                    beef    
4 cabbage, lettuce                    spinach 
5 cabbage, lettuce, spinach           broccoli
6 cabbage, lettuce, spinach, broccoli mango

注意：rowwise 可能比@IceCreamToucan 的 accumulate 慢。

Dataframe 列循环和基于 R 中条件的字符串连接（pref dplyr）

Dataframe column looping and string concatenation based on conditional in R (pref dplyr)

loops

r

dataframe

dplyr

tidyverse