Transpose / reshape dataframe without "timevar" from long to wide format

With the data.table package, this could easily be solved with the new rowid function:

library(data.table)
dcast(setDT(d1), 
      Name ~ rowid(Name, prefix = "medication"), 
      value.var = "MedName")

which gives:

   Name    medication1     medication2       medication3
1 Name1  atenolol 25mg    aspirin 81mg  sildenafil 100mg
2 Name2  atenolol 50mg  enalapril 20mg              <NA>

Another method (commonly used before version 1.9.7):

dcast(setDT(d1)[, rn := 1:.N, by = Name], 
      Name ~ paste0("medication",rn), 
      value.var = "MedName")

giving the same result.

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A similar approach, but now using the dplyr and tidyr packages:

library(dplyr)
library(tidyr)
d1 %>%
  group_by(Name) %>%
  mutate(rn = paste0("medication",row_number())) %>%
  spread(rn, MedName)

which gives:

Source: local data frame [2 x 4]
Groups: Name [2]

    Name   medication1    medication2      medication3
  (fctr)         (chr)          (chr)            (chr)
1  Name1 atenolol 25mg   aspirin 81mg sildenafil 100mg
2  Name2 atenolol 50mg enalapril 20mg               NA

Assuming your data is in the object dataset:

library(plyr)
## Add a medication index
data_with_index <- ddply(dataset, .(Name), mutate, 
                         index = paste0('medication', 1:length(Name)))    
dcast(data_with_index, Name ~ index, value.var = 'MedName')

##    Name   medication1    medication2      medication3
## 1 Name1 atenolol 25mg   aspirin 81mg sildenafil 100mg
## 2 Name2 atenolol 50mg enalapril 20mg             <NA>