R - Convert various dummy/logical variables into a single categorical variable/factor from their name

Question

My question has strong similarities with this one and this other one, but my dataset is a little bit different and I can\'t seem to make those solutions work. Please excuse me i

Answer 1

Try:

library(dplyr)
library(tidyr)

df %>% gather(type, value, -id) %>% na.omit() %>% select(-value) %>% arrange(id)

Which gives:

#  id       type
#1  1 conditionA
#2  2 conditionB
#3  3 conditionC
#4  4 conditionD
#5  5 conditionA

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Update

To handle the case you detailed in the comments, you could do the operation on the desired portion of the data frame and then left_join() the other columns:

df %>% 
  select(starts_with("condition"), id) %>% 
  gather(type, value, -id) %>% 
  na.omit() %>% 
  select(-value) %>% 
  left_join(., df %>% select(-starts_with("condition"))) %>%
  arrange(id)

Answer 2

library(tidyr)
library(dplyr)

df <- df %>%
  gather(type, count, -id)
df <- df[complete.cases(df),][,-3]
df[order(df$id),]
   id       type
1   1 conditionA
7   2 conditionB
13  3 conditionC
19  4 conditionD
5   5 conditionA

Answer 3

You can also try:

colnames(df)[2:5][max.col(!is.na(df[,2:5]))]
#[1] "conditionA" "conditionB" "conditionC" "conditionD" "conditionA"

The above works if one and only one column has a value other than NA for each row. If the values of a row can be all NAs, then you can try:

mat<-!is.na(df[,2:5])
colnames(df)[2:5][max.col(mat)*(NA^!rowSums(mat))]