How to transpose column and group at the same time [duplicate]

Answer 1

This can be done with reshape() by synthesizing a time column:

reshape(cbind(df,time=ave(seq_len(nrow(df)),df$Pt,FUN=seq_along)),dir='w',idvar='Pt');
##     Pt EVENT.1 EVENT.2 EVENT.3
## 1  123     GGG     Nor     tre
## 4  144     GGG    <NA>    <NA>
## 5 1667     tre     Nor     tre

Data

df <- data.frame(Pt=c(123L,123L,123L,144L,1667L,1667L,1667L),EVENT=c('GGG','Nor','tre','GGG',
'tre','Nor','tre'),stringsAsFactors=F);

Answer 2

We can use data.table

 library(data.table)
 dcast(setDT(df1), Pt~rowid(Pt), value.var="EVENT")

Answer 3

Another option:

library(data.table)
l <- sapply(unique(df$Pt), function(x) data.frame(rbind(c(x,df[df$Pt==x,]$EVENT))))
rbindlist(l, fill = T)

     # X1  X2  X3  X4
# 1:  123 GGG Nor tre
# 2:  144 GGG  NA  NA
# 3: 1667 tre Nor tre

DATA

df <- structure(list(Pt = c(123L, 123L, 123L, 144L, 1667L, 1667L, 1667L
), EVENT = c("GGG", "Nor", "tre", "GGG", "tre", "Nor", "tre")), .Names = c("Pt", 
"EVENT"), row.names = c(NA, -7L), class = "data.frame")

Answer 4

Here is a dplyr and tidyr solution:

library(dplyr)
library(tidyr)

data %>%
     group_by(Pt) %>%
     mutate(rn = 1:n()) %>%
     ungroup %>%
     spread(rn, EVENT)