使用不具有聚合功能的Reshape2在R中将DF从长到宽重塑

Question

a common task in the data I work with is reshaping client data from long to wide. I have a process to do this with Reshape outlined below that basically creates new (but unmodified) columns with a numeric index appended. In my case I do not want to perform any modifications on the data. My question, because I often use reshape2 for other operations, is how this can be accomplished with dcast? It does not seem that the example data need to be melted by id, for example, but I'm not sure how I would go about making it wide. Would anyone be able to provide code in reshape2 to produce a frame comparable to "wide" in the example below?

Thanks.

Example

date_up   <- as.numeric(as.Date("1990/01/01"))
date_down <- as.numeric(as.Date("1960/01/01"))
ids <- data.frame(id=rep(1:1000, 3),site=rep(c("NMA", "NMB","NMC"), 1000))
ids <- ids[order(ids$id), ]
dates <-  data.frame(datelast=runif(3000, date_down, date_up),
          datestart=runif(3000, date_down, date_up),
          dateend=runif(3000, date_down, date_up),
          datemiddle=runif(3000, date_down, date_up))
dates[] <- lapply(dates[ , c("datestart", "dateend", "datemiddle")], 
             as.Date.numeric, origin = "1970-01-01")
df <- cbind(ids, dates)

# Make a within group index and reshape df
df$gid <- with(df, ave(rep(1, nrow(df)), df[,"id"], FUN = seq_along))
wide <- reshape(df, idvar = "id", timevar = "gid", direction = "wide")

Answer 1

We can use dcast from data.table , which can take multiple value.var columns. Convert the 'data.frame' to 'data.table' ( setDT(df) ), use the dcast with formula and value.var specified.

library(data.table)
dcast(setDT(df), id~gid, value.var=names(df)[2:6])

NOTE: The data.table method would be faster compared to the reshape2