在所有dplyr结构中使用的函数中访问列名

你很接近。你可以加一个 mutate()

mtcars %>% 
  sample_n(30) %>%
  select(colnames(mtcars)[2:5]) %>%
  summarise_all(list(~ list(funx(.)))) %>% 
  gather() %>% 
  unnest() %>% 
  arrange(pvalue) %>% 
  rename(Parameter = key) %>% 
  mutate(Parameter = ifelse(Transform == "T", paste0("log10_", Parameter), Parameter)) %>% 
  select(Parameter, pvalue)

#  Parameter     pvalue
#  log10_cyl 0.00000000
# log10_drat 0.01389723
#       disp 0.02771770
#   log10_hp 0.08493466

回答在一个单独的职位,因为解决方案是不同的。获取 print() purrr::map_dfr 构建结果的数据帧。我做的小改动是为了抓住列名, col_name ,并指定数据帧。我尝试了一些方法来获取列名使用您原来的功能,但结果不成功。

logtest_pval <- function(col, df) {

  col_name <- col
  x <- df %>% pull(!!col)

  logchoice <- ifelse(max(x) < 400, TRUE, FALSE)
  logtest <- log10(x)
  remaining <- length(logtest[which(!is.na(logtest) & is.finite(logtest))])

  x <- if(remaining > 0.75*length(x)) {suppressWarnings(log10(x)) } else { x }
  x <- x[which(!is.na(x) & is.finite(x))]
  y <- diptest::dip.test(x)

  z <- 
    tibble(
      transform = logchoice,
      column = ifelse(logchoice, paste0("log10_", col_name), col_name),
      pvalue = y$p.value
    )

  print(paste0(z, collapse = " | "))
  return(z)
}

然后可以构建数据帧:

purrr::map_dfr(
  .x = names(mtcars), # the columns to use
  .f = logtest_pval,  # the function to use
  df = mtcars         # additional arguments needed
)

df <-
  mtcars %>% 
  select_if(is.numeric)

pvalues <-
  map_dfr(names(df), logtest_pval, df)