R在purrr::map()内调用dplyr 1.0.0 filter()和purrr()

Question

下面的代码从远程URL读取数据，然后查找五个不同列子集中的所有列的NA行。输出表miss_recode给出了这些行的ID以及变量recode_cols，该变量是行子集全部为NA的标签。

suppressMessages(library(tidyverse))

urlRemote_path  <- "https://raw.githubusercontent.com/"
github_path <- "DSHerzberg/TOD-R/master/INPUT-FILES/"
fileName_path   <- "SO-data.csv"

input <- suppressMessages(read_csv(url(
  str_c(urlRemote_path, github_path, fileName_path)
)))

miss1 <- input %>%
  filter(across(c(i001:i035),
                ~ is.na(.))) %>% 
  mutate(recode_cols = "i001:i035")
miss2 <- input %>%
  filter(across(c(i036:i060),
                ~ is.na(.))) %>% 
  mutate(recode_cols = "i036:i060")
miss3 <- input %>%
  filter(across(c(i061:i100),
                ~ is.na(.))) %>% 
  mutate(recode_cols = "i061:i100")
miss4 <- input %>%
  filter(across(c(i101:i130),
                ~ is.na(.))) %>% 
  mutate(recode_cols = "i101:i130")
miss5 <- input %>%
  filter(across(c(i131:i165),
                ~ is.na(.))) %>% 
  mutate(recode_cols = "i131:i165")

miss_recode <- bind_rows(
  miss1, 
  miss2, 
  miss3, 
  miss4, 
  miss5
) %>% 
  select(ID, recode_cols)

我想用purrr::map合并代码。下一个片段显示了我的尝试，但它返回Error: Can't subset columns that don't exist.

vec <- c("i001:i035", "i036:i060", "i061:i100", "i101:i130", "i131:i165")

miss_recode_map <- vec %>% 
  map_df(~
        input %>%
        filter(across(c(!!sym(.x)),
                      ~ is.na(.))) %>% 
        mutate(recode_cols = .x) %>% 
          select(ID, recode_cols)
        )

很明显，我没有得到正确的NSE。这似乎是一个与across()相关的新问题，该问题现已在dplyr 1.0.0中提供。在本例中，似乎.x的一种用法需要引用vec的元素，而.x的另一种用法要求不用引号引用这些元素。

提前感谢您的帮助。

Answer 1

您不能将"i001:i035"转换为符号，您实际上需要对其进行解析。

library(dplyr)
library(rlang)

purrr::map_df(vec, ~input %>%
                    filter(across(!!parse_expr(.x),~ is.na(.))) %>%
                    mutate(recode_cols = .x) %>%
                    select(ID, recode_cols))

# A tibble: 8 x 2
#      ID recode_cols
#   <dbl> <chr>      
#1 201010 i036:i060  
#2 214063 i036:i060  
#3 262050 i036:i060  
#4 262063 i036:i060  
#5 205036 i061:i100  
#6 231007 i061:i100  
#7 208014 i101:i130  
#8 231014 i131:i165