Turn long dataset of classes taken into wide datas

Question

Say I have a dataset where rows are classes people took:

attendance <- data.frame(id = c(1, 1, 1, 2, 2),
                         class = c("Math", "English", "Math", "Reading", "Math"))  

I.e.,

     id  class  
   1 1   "Math" 
   2 1   "English"
   3 1   "Math"
   4 2   "Reading"
   5 2   "Math"

And I want to create a new dataset where rows are ids and the variables are class names, like this:

class.names <- names(table(attendance$class))
attedance2 <-  matrix(nrow=length(table(attendance$id)), 
                      ncol=length(class.names)) 
colnames(attedance2) <- class.names
attedance2 <- as.data.frame(attedance2)
attedance2$id <- unique(attendance$id)

I.e.,

     English  Math  Reading  id
   1    NA     NA      NA     1
   2    NA     NA      NA     2

I want to fill in the NAs with whether that particular id took that class or not. It can be Yes/No, 1/0, or counts of the classes

I.e.,

     English  Math  Reading  id
   1   "Yes"  "Yes"   "No"    1
   2   "No"   "Yes"   "Yes"   2

I'm familiar with dplyr, so it'd be easier for me if that was used in the solution but not necessary. Thank you for your help!

Answer 1

We can do this with base R

attendance$val <- "yes"
d1 <- reshape(attendance, idvar = 'id', direction = 'wide', timevar = 'class')
d1[is.na(d1)] <- "no"
names(d1) <- sub("val\\.", '', names(d1))
d1
#  id Math English Reading
#1  1  yes     yes      no
#4  2  yes      no     yes

---

Or with xtabs

xtabs(val ~id + class, transform(unique(attendance), val = 1))
#    class
# id  English Math Reading
#  1       1    1       0
#  2       0    1       1

NOTE: The binary can be easily converted to 'yes', 'no', but it is better to have either 1/0 or TRUE/FALSE

Answer 2

Using:

library(reshape2)
attendance$val <- 'yes'
dcast(unique(attendance), id ~ class, value.var = 'val', fill = 'no')

gives:

  id English Math Reading
1  1     yes  yes      no
2  2      no  yes     yes

A similar approach with data.table:

library(data.table)
dcast(unique(setDT(attendance))[,val:='yes'], id ~ class, value.var = 'val', fill = 'no')

Or with dplyr/tidyr:

library(dplyr)
library(tidyr)
attendance %>% 
  distinct() %>% 
  mutate(var = 'yes') %>% 
  spread(class, var, fill = 'no')

---

Another, somewhat more convoluted option might to reshape first and then replace the counts with yes and no (see here for an explanation about the default aggregate option of dcast):

 att2 <- dcast(attendance, id ~ class, value.var = 'class')

which gives:

  id English Math Reading
1  1       1    2       0
2  2       0    1       1

Now you can replace the count with:

# create index which counts are above zero
idx <- att2[,-1] > 0
# replace the non-zero values with 'yes'
att2[,-1][idx] <- 'yes'
# replace the zero values with 'no'
att2[,-1][!idx] <- 'no'

which finally gives:

> att2
  id English Math Reading
1  1     yes  yes      no
2  2      no  yes     yes