我有提到的数据集。如何获得每个ID的列标题列表?
我尝试了以下操作:
'colnames<-'(t(apply(dat == 1, 1, function(x) c(`colnames`(dat)[x], rep(NA, 4-sum(x))))),
paste("LearningA", 1:3))
res <- apply(df, 1, function(x) {
out <- character(4) # create a 4-length vector of NAs
tmp <- `colnames`(df)[which(x==1)] # store the column names in a tmp field
`out`[1:length(tmp)] <- tmp # overwrite the relevant positions
out
})
最佳答案
purrr
的一个选项:
library(purrr)
df %>% split(.$ID) %>% map(~names(.x)[!!.x][-1])
# $`1`
# [1] "LearningA"
#
# $`2`
# [1] "LearningC"
#
# $`3`
# [1] "LearningA" "LearningB" "LearningC"
#
# $`4`
# [1] "LearningA" "LearningB"
#
# $`5`
# character(0)
df %>% split(.$ID) %>% map(~which(!!.x[-1]))
# $`1`
# [1] 1
#
# $`2`
# [1] 3
#
# $`3`
# [1] 1 2 3
#
# $`4`
# [1] 1 2
#
# $`5`
# integer(0)
您可能已经在评论中提及了以下内容:
library(tidyverse)
df %>% gather(,,-1) %>%
group_by(ID,value) %>%
summarize(key=paste(key,collapse=", ")) %>%
spread(value,key)
# # A tibble: 5 x 5
# # Groups: ID [5]
# ID `0` `1` `2` `3`
# * <int> <chr> <chr> <chr> <chr>
# 1 1 LearningB, LearningC LearningA <NA> <NA>
# 2 2 LearningA, LearningB <NA> LearningC <NA>
# 3 3 <NA> LearningB LearningC LearningA
# 4 4 LearningC LearningA, LearningB <NA> <NA>
# 5 5 LearningA, LearningB, LearningC <NA> <NA> <NA>