a<-c(TRUE,FALSE,TRUE,FALSE,TRUE,FALSE)
b<-c(TRUE,FALSE,TRUE,FALSE,FALSE,FALSE)
c<-c(TRUE,TRUE,TRUE,FALSE,TRUE,FALSE)
costumer<-c("one","two","three","four","five","six")
df<-data.frame(costumer,a,b,c)
That's an example code. It looks like this printed:
costumer a b c
1 one TRUE TRUE TRUE
2 two FALSE FALSE TRUE
3 three TRUE TRUE TRUE
4 four FALSE FALSE FALSE
5 five TRUE FALSE TRUE
6 six FALSE FALSE FALSE
I want to create a new column df$items that contains only the column names that are TRUE
for each row in the data. Something like this:
costumer a b c items
1 one TRUE TRUE TRUE a,b,c
2 two FALSE FALSE TRUE c
3 three TRUE TRUE TRUE a,b,c
4 four FALSE FALSE FALSE
5 five TRUE FALSE TRUE
6 six FALSE FALSE FALSE
I thought of using apply function or use which
for selecting indexes, but couldn't figure it out. Can anyone help me?
df$items = apply(df[2:4], 1, function(x) toString(names(df[2:4])[x]))
df
# custumer a b c items
# 1 one TRUE TRUE TRUE a, b, c
# 2 two FALSE FALSE TRUE c
# 3 three TRUE TRUE TRUE a, b, c
# 4 four FALSE FALSE FALSE
# 5 five TRUE FALSE TRUE a, c
# 6 six FALSE FALSE FALSE
You could use
df$items <- apply(df, 1, function(x) toString(names(df)[which(x == TRUE)]))
Output
# custumer a b c items
# 1 one TRUE TRUE TRUE a, b, c
# 2 two FALSE FALSE TRUE c
# 3 three TRUE TRUE TRUE a, b, c
# 4 four FALSE FALSE FALSE
# 5 five TRUE FALSE TRUE a, c
# 6 six FALSE FALSE FALSE
df$items <- apply(df, 1, function(x) paste0(names(df)[x == TRUE], collapse = ","))
df
custumer a b c items
1 one TRUE TRUE TRUE a,b,c
2 two FALSE FALSE TRUE c
3 three TRUE TRUE TRUE a,b,c
4 four FALSE FALSE FALSE
5 five TRUE FALSE TRUE a,c
6 six FALSE FALSE FALSE
We can use pivot_longer
to reshape to 'long' format and then do a group by paste
library(dplyr)
library(tidyr)
library(stringr)
df %>%
pivot_longer(cols = a:c) %>%
group_by(costumer) %>%
summarise(items = toString(name[value])) %>%
left_join(df)
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