Creating a data frame in R from list data that is missing some values

I have a CSV with a long list of data that looks like this:

Date    user_id    value
4/1       1           5
4/1       2           3
4/1       3           10
4/2       1           1
4/2       3           7

and I want to move it into a data frame开发者_JAVA百科 that just has one column of user id's and a column for each date. I'm assuming there is a way to do with with sapply or lapply but I'm not sure how to handle that the user id's don't always exist for every date.

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Maybe something using reshape like the following, which assumes your data are stored in dat:

reshape(dat,v.names = "value",idvar = "user_id",
        direction = "wide",timevar = "Date")

  user_id value.4/1 value.4/2
1       1         5         1
2       2         3        NA
3       3        10         7

Or perhaps more simply, use dcast from reshape2:

dcast(dat,user_id~Date)

  user_id 4/1 4/2
1       1   5   1
2       2   3  NA
3       3  10   7

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This is also something that tidyr::spread does quite conveniently

require(tidyr)
require(dplyr)

df <- data.frame("Date" = rep(c("Nov", "Dec"), each = 3), 
             "user.id" = rep(1:3, 2),
             "value" = rnorm(6))

df.2 <- df %>% 
spread(Date, value)

df.2
  user.id        Dec       Nov
     1      -1.9094765   -1.101037
     2       0.2358694   -1.418151
     3      -0.4297790   -1.426573