Turns thousands of dummy variables into multinomial variable - r

Question

I have a dataframe of the following sort:
a<-c('q','w')
b<-c(T,T)
d<-c(F,F)
.e<-c(T,F)
.f<-c(F,F)
.g<-c(F,T)
h<-c(F,F)
i<-c(F,T)
j<-c(T,T)
df<-data.frame(a,b,d,.e,.f,.g,h,i,j)
a b d .e .f .g h i j
1 q TRUE FALSE TRUE FALSE FALSE FALSE FALSE TRUE
2 w TRUE FALSE FALSE FALSE TRUE FALSE TRUE TRUE
I want to turn all variables starting with periods at the start into a single multinomial variable called Index such that the second row would have a value 1 for the Index column, the third row would have a value 2, etc. :
df$Index<-c('e','g')
a b d .e .f .g h i j Index
1 q TRUE FALSE TRUE FALSE FALSE FALSE FALSE TRUE e
2 w TRUE FALSE FALSE FALSE TRUE FALSE TRUE TRUE g
Although many rows can have a T for any of period-initial variable, each row can be T for only ONE period-initial variable.
If it were just a few items id do an ifelse statement:
df$Index <- ifelse(df$_10000, '10000',...
But there are 12000 of these. The names for all dummy variables begin with underscores, so I feel like there must be a better way. In pseudocode I would say something like:
for every row:
for every column beginning with '_':
if value == T:
assign the name of the column without '_' to a Column 'Index'
Thanks in advance

Answer 1

Sample data:
df <- cbind(a = letters[1:10], b = LETTERS[1:10],
data.frame(diag(10) == 1))
names(df)[-(1:2)] <- paste0("_", 1:10)
set.seed(42)
df <- df[sample(nrow(df)),]
head(df,3)
# a b _1 _2 _3 _4 _5 _6 _7 _8 _9 _10
# 1 a A TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
# 5 e E FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE
# 10 j J FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE
Execution:
df$Index <- apply(subset(df, select = grepl("^_", names(df))), 1,
function(z) which(z)[1])
df
# a b _1 _2 _3 _4 _5 _6 _7 _8 _9 _10 Index
# 1 a A TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 1
# 5 e E FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE 5
# 10 j J FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE 10
# 8 h H FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE 8
# 2 b B FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 2
# 4 d D FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE 4
# 6 f F FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE 6
# 9 i I FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE 9
# 7 g G FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE 7
# 3 c C FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 3
If there are more than one TRUE in a row of _-columns, the first found will be used, the remainder silently ignored. If there are none, Index will be NA for that row.