如何使用purrr按类型对列表中的数据框基于id列执行全连接并输出列表格式

Here's a straightforward solution that leverages purrr for iteration and dplyr for joining, which aligns with your preference for using the purrr package:

Step 1: Load Required Libraries #

library(purrr)
library(dplyr)
library(stringr) # For string matching

Step 2: Define Your Input Data #

list_example <- list(type1_a_b = data.frame(id = 1:3, a = 1:3, b = 4:6), 
                     type1_c_d = data.frame(id = 1:5, c = 1:5, d = 5:9), 
                     type2_e_f = data.frame(id = c(1,3,4), e = 1:3, f = 4:6), 
                     type2_g_h = data.frame(id = c(2,3,4), g = 1:3, h = 5:7))
data_types <- c("type1", "type2")

Step 3: Execute Grouped Full Join #

result <- map(data_types, function(current_type) {
  # Filter list items whose names start with the current type
  list_example %>%
    keep(names(.) %>% str_detect(paste0("^", current_type))) %>%
    # Perform full join on all filtered data frames, using 'id' as the key
    reduce(full_join, by = "id")
}) %>%
  # Assign names to the result list matching your data_types vector
  set_names(data_types)

Step 4: Verify the Output #

When you print result, you'll get exactly the structured output you requested:

result
#> $type1
#>   id  a  b c d
#> 1  1  1  4 1 5
#> 2  2  2  5 2 6
#> 3  3  3  6 3 7
#> 4  4 NA NA 4 8
#> 5  5 NA NA 5 9
#> 
#> $type2
#>   id  e  f  g  h
#> 1  1  1  4 NA NA
#> 2  2 NA NA  1  5
#> 3  3  2  5  2  6
#> 4  4  3  6  3  7

How It Works #

• map() iterates over each value in data_types (i.e., "type1" and "type2"), running the inner logic for each group.
• keep() + str_detect() filters your list_example to only retain data frames whose names start with the current type (the regex ^current_type ensures we match prefixes correctly).
• reduce(full_join, by = "id") takes the filtered sub-list of data frames and repeatedly applies full_join to combine them all into one data frame, using "id" as the join key.
• set_names() ensures the final list has names matching your data_types vector, making it easy to reference each grouped result for later processing.

内容的提问来源于stack exchange，提问作者Polina B