函数返回lapply嵌套lapply中的函数？

Question

我以为我在处理代码时很优雅，直到遇到了lapply函数的问题。我用dput输出样本。请注意，我使用的是data.table而不是data.frame。

full_data <- structure(list(FireplaceQu = c("Gd", "Gd", "TA", "TA", "Gd", 
"None", "Gd", "Gd", "None", "None", "None", "None", "Gd", "Gd", 
"Gd", "None"), BsmtQual = c("TA", "Gd", "Gd", "TA", "Gd", "TA", 
"Ex", "TA", "TA", "TA", "TA", "Ex", "TA", "Ex", "Ex", "Gd"), 
    CentralAir = c("Y", "Y", "Y", "Y", "Y", "Y", "Y", "Y", "N", 
    "N", "Y", "Y", "Y", "Y", "Y", "Y")), .Names = c("FireplaceQu", 
"BsmtQual", "CentralAir"), class = "data.frame", row.names = c(NA, 
-16L))

library(data.table)
setDT(full_data)


cols = c('FireplaceQu', 'BsmtQual', 'CentralAir')

FireplaceQu=c('None','Po','Fa','TA','Gd','Ex')
BsmtQual=c('None','Po','Fa','TA','Gd','Ex')
CentralAir=NA

cust_levels <- list(FireplaceQu, BsmtQual, CentralAir)

# I modified a function from SO to sort based on set levels instead of by using default sort function.
# https://stackoverflow.com/questions/38620424/label-encoder-functionality-in-r
# function which returns function which will encode vectors with values  of 'vec' 
lev_index = 1
label_encoder = function(vec){
    levels = cust_levels[[lev_index]]
    lev_index = lev_index + 1
    function(x){
        match(x, levels)
    }
}

full_data[, (cols) := lapply(.SD, lapply(.SD, label_encoder)), .SDcols = cols]

我知道我可以让它在for循环中工作，但是我想我会尝试使用lapply函数。我很困惑如何将它与返回一个函数作为值，而不是需要计算的函数一起使用。

我最终希望根据cust_levels的顺序创建整数值。奖金，如果我能摆脱lev_index！

示例输入：

FireplaceQu BsmtQual CentralAir
         None       Gd          Y
           TA       Gd          Y
           TA       Gd          Y
           Gd       TA          Y

示例输出：

FireplaceQu BsmtQual CentralAir
         1       5          NA
         4       5          NA
         4       5          NA
         5       4          NA

Answer 1

你可以用mapply来做这件事

full_data[, (cols) := mapply(match, .SD, cust_levels, SIMPLIFY = FALSE), .SDcols = cols]

# > full_data
#     FireplaceQu BsmtQual CentralAir
#  1:           5        4         NA
#  2:           5        5         NA
#  3:           4        5         NA
#  4:           4        4         NA
#  5:           5        5         NA
#  6:           1        4         NA
#  7:           5        6         NA
#  8:           5        4         NA
#  9:           1        4         NA
# 10:           1        4         NA
# 11:           1        4         NA
# 12:           1        6         NA
# 13:           5        4         NA
# 14:           5        6         NA
# 15:           5        6         NA
# 16:           1        5         NA