在具有多个数据框的列表上使用包“bestNormalize”进行数据转换[重复]

Question

我想转换我的数据，但我不太确定哪种方法最好。因此，我使用包“bestNormalize”。

它在数据框的一列上运行良好，但是我有两个数据框的列表（每个数据框有 9 列），我想将函数“bestNormalize”应用于每一列。我尝试映射，但它不起作用。

此外，我想将包的其他函数（数据转换，例如使用函数“yeojohnson”）与我将“bestNormalize”函数应用于每个数据帧的每一列的方式相同。

有人知道这是如何工作的吗？提前致谢。

install.packages("bestNormalize")
library(bestNormalize)

install.packages("purrr")
library(purrr)

# Data
a <- data.frame(
  met1 = rnorm(n = 100, mean = 0, sd = 1),
  met2 = rnorm(n = 100, mean = 0, sd = 1),
  met3 = rnorm(n = 100, mean = 0, sd = 1),
  met4 = rnorm(n = 100, mean = 0, sd = 1),
  met5 = rnorm(n = 100, mean = 0, sd = 1),
  met6 = rnorm(n = 100, mean = 0, sd = 1),
  met7 = rnorm(n = 100, mean = 0, sd = 1),
  met8 = rnorm(n = 100, mean = 0, sd = 1),
  met9 = rnorm(n = 100, mean = 0, sd = 1)
)


y <- data.frame(
  met1 = rnorm(n = 100, mean = 0, sd = 1),
  met2 = rnorm(n = 100, mean = 0, sd = 1),
  met3 = rnorm(n = 100, mean = 0, sd = 1),
  met4 = rnorm(n = 100, mean = 0, sd = 1),
  met5 = rnorm(n = 100, mean = 0, sd = 1),
  met6 = rnorm(n = 100, mean = 0, sd = 1),
  met7 = rnorm(n = 100, mean = 0, sd = 1),
  met8 = rnorm(n = 100, mean = 0, sd = 1),
  met9 = rnorm(n = 100, mean = 0, sd = 1)
)


my_list <- list(a, y)
 
# Works:
bestNormalize::bestNormalize(my_list[[1]]$met1)

# Does not work:
stand_dat_men <- my_list  %>% purrr::map(~mutate_at(.x, .vars = vars(met1:met9), ~bestNormalize(.)))

Answer 1

bestNormalize 返回一个“bestNormalize”类的对象，你可以将它存储在一个列表中。您也可以在此处使用summarise 而不是mutate。

library(dplyr) 
library(bestNormalize)

output <- purrr::map(my_list, ~.x %>% summarise_at(vars(met1:met9), 
                               ~list(bestNormalize(.))))

summarise_at 现在已替换为 across。

output <- purrr::map(my_list, ~.x %>% summarise(across(met1:met9, 
                               ~list(bestNormalize(.)))))