I have a data frame like this:
group student exam_passed subject
A 01 Y Math
A 01 N Science
A 01 Y Japanese
A 02 N Math
A 02 Y Science
B 01 Y Japanese
C 02 N Math
What I would like to achieve is the below result:
group student exam_passed subject_Math subject_Science subject_Japanese
A 01 Y 1 0 0
A 01 N 0 1 0
A 01 Y 0 0 1
A 02 N 1 0 0
A 02 Y 0 1 0
B 01 Y 0 0 1
C 02 N 1 0 0
Here is the test data frame:
df <- data.frame(
group = c('A', 'A', 'A', 'A', 'A', 'B', 'C'),
student = c('01', '01', '01', '02', '02', '01', '02'),
exam_pass = c('Y', 'N', 'Y', 'N', 'Y', 'Y', 'N'),
subject = c('Math', 'Science', 'Japanese', 'Math', 'Science', 'Japanese', 'Math')
)
I have tried for loop, however, the original data is too large to deal with, and
mltools::one_hot(df, col = 'subject')
doesn't work either because of the this error:
Error in `[.data.frame`(dt, , cols, with = FALSE) :
unused argument (with = FALSE)
Could anyone help me with this? Thanks!
require(tidyr)
require(dplyr)
df %>% mutate(value = 1) %>% spread(subject, value, fill = 0 )
group student exam_pass Japanese Math Science
1 A 01 N 0 0 1
2 A 01 Y 1 1 0
3 A 02 N 0 1 0
4 A 02 Y 0 0 1
5 B 01 Y 1 0 0
6 C 02 N 0 1 0