Download mixedL.csv 

(see “CSV format” under “Files used in the examples”)

mixed_left <- read.csv('mixedL.csv')

mixed_left

   First Last Age Group    Veggie      Fruit

1  John Sims  30     A Artichoke      Apple

2  Mary Sims  25     A Asparagus    Apricot

3  John Kent  40     A              Avocado

4  John Sims  30     B  Broccoli     Banana

5  Mary Sims  25     B                    

6  John Kent  40     B            Blueberry

7  John Sims  30     C    Carrot     Cherry

8  Mary Sims  25     C    Celery  Cranberry

9  John Kent  40     C           Clementine

Option 1: Transform using reshape        

Option 2: Transform using reshape2 library        

Option 3: Transform using tidyr library        

Option 1: Transform using reshape

# From mixed_left to wide

wide <- reshape(data = mixed_left,

                idvar = c('First','Last','Age'),

                timevar = 'Group',

                v.names = c('Veggie','Fruit'),

                direction = 'wide')

wide

  First Last Age  Veggie.A Fruit.A Veggie.B   Fruit.B  Veggie.C   Fruit.C

1  John Sims  30 Artichoke   Apple Broccoli    Banana   Carrot     Cherry

2  Mary Sims  25 Asparagus Apricot                      Celery  Cranberry

3  John Kent  40           Avocado          Blueberry          Clementine

library(reshape2)

# decast can only handle one value variable at a time, so we need to # melt the mixed format to long format first, and then cast it by

# ‘Group’ and ‘Type’ to get the wide format

# From mixed_left to wide

temp <- melt(data = mixed_left,

             id.vars = c('First','Last','Age','Group'),

             measure.vars = c('Veggie','Fruit'),

             variable.name = 'Type',

             value.name = 'Plant')

temp

   First Last Age Group   Type      Plant

1   John Sims  30     A Veggie  Artichoke

2   Mary Sims  25     A Veggie  Asparagus

3   John Kent  40     A Veggie          

4   John Sims  30     B Veggie   Broccoli

5   Mary Sims  25     B Veggie          

6   John Kent  40     B Veggie          

7   John Sims  30     C Veggie     Carrot

8   Mary Sims  25     C Veggie     Celery

9   John Kent  40     C Veggie          

10  John Sims  30     A  Fruit      Apple

11  Mary Sims  25     A  Fruit    Apricot

12  John Kent  40     A  Fruit    Avocado

13  John Sims  30     B  Fruit     Banana

14  Mary Sims  25     B  Fruit          

15  John Kent  40     B  Fruit  Blueberry

16  John Sims  30     C  Fruit     Cherry

17  Mary Sims  25     C  Fruit  Cranberry

18  John Kent  40     C  Fruit Clementine

wide <- dcast(data = temp,

              formula = First+Last+Age~Group+Type,

              value.var = 'Plant')

wide

  First Last Age  A_Veggie A_Fruit B_Veggie   B_Fruit C_Veggie    C_Fruit

1  John Kent  40           Avocado          Blueberry          Clementine

2  John Sims  30 Artichoke   Apple Broccoli    Banana   Carrot     Cherry

3  Mary Sims  25 Asparagus Apricot                      Celery  Cranberry

library(tidyr)

# From mixed_left to wide

wide <- mixed_left %>%

  gather(key = 'Type',value = 'Plant', Veggie:Fruit) %>%

  unite(col = 'key', Type, Group, sep='-') %>%

  spread(key = 'key', value = 'Plant')

wide

  First Last Age Fruit-A   Fruit-B    Fruit-C  Veggie-A Veggie-B Veggie-C

1  John Kent  40 Avocado Blueberry Clementine                            

2  John Sims  30   Apple    Banana     Cherry Artichoke Broccoli   Carrot

3  Mary Sims  25 Apricot            Cranberry Asparagus            Celery