这是一个根据您希望最终数据集的外观重新格式化数据的功能。对于该函数,您提供数据框DF、变量var,以及按正确顺序colnames 和byitem 的列名向量来选择输出格式(默认为TRUE,它输出一个每个item 一行的数据框:
library(tidyverse)
df_transform = function(DF, var, colnames, byitem = TRUE){
if(byitem){
ID = sym("rowid")
}else{
ID = sym("id")
}
DF %>%
group_by(id = paste0("item", cumsum(grepl("item", var)))) %>%
mutate(rowid = replace(2:n(), 2:n(), setNames(colnames[1:(n()-1)], 2:n()))) %>%
filter(!grepl("item", var)) %>%
spread(!!ID, var)
}
输出:
> df_transform(df, var, c("price", "color", "date"))
# A tibble: 3 x 4
# Groups: id [3]
id color date price
<chr> <fct> <fct> <fct>
1 item1 red <NA> $600
2 item2 <NA> <NA> $70
3 item3 orange 10/11/2017 $430
> df_transform(df, var, c("price", "color", "date"), byitem = FALSE)
# A tibble: 3 x 4
rowid item1 item2 item3
<chr> <fct> <fct> <fct>
1 color red <NA> orange
2 date <NA> <NA> 10/11/2017
3 price $600 $70 $430
请注意,如果中间有缺失值,这将不起作用,因为列名是按位置分配的。
数据:
df <- structure(list(var = structure(c(5L, 2L, 9L, 6L, 3L, 7L, 1L,
8L, 4L), .Label = c("$430", "$600", "$70", "10/11/2017", "item_1",
"item_2", "item_3", "orange", "red"), class = "factor")), .Names = "var", class = "data.frame", row.names = c(NA,
-9L))