dcast.data.table {data.table} | R Documentation

## Fast dcast for data.table

### Description

`dcast.data.table` is a much faster version of `reshape2::dcast`, but for `data.table`s. More importantly, it's capable of handling very large data quite efficiently in terms of memory usage in comparison to `reshape2::dcast`.

From 1.9.6, `dcast` is implemented as an S3 generic in `data.table`. To melt or cast `data.table`s, it is not necessary to load `reshape2` anymore. If you have load `reshape2`, do so before loading `data.table` to prevent unwanted masking.

NEW: `dcast.data.table` can now cast multiple `value.var` columns and also accepts multiple functions to `fun.aggregate`. See Examples for more.

### Usage

    ## S3 method for class 'data.table'
    dcast(data, formula, fun.aggregate = NULL, sep = "_",
        ..., margins = NULL, subset = NULL, fill = NULL,
        drop = TRUE, value.var = guess(data),
        verbose = getOption("datatable.verbose"))

### Arguments

`data` | A `data.table`.
`formula` | A formula of the form LHS ~ RHS to cast, see Details.
`fun.aggregate` | Should the data be aggregated before casting? If the formula doesn't identify a single observation for each cell, then aggregation defaults to `length` with a message. NEW: it is possible to provide a list of functions to `fun.aggregate`. See Examples.
`sep` | Character vector of length 1, indicating the separating character in variable names generated during casting. Default is `_` for backwards compatibility.
`...` | Any other arguments that may be passed to the aggregating function.
`margins` | Not implemented yet. Should take variable names to compute margins on. A value of `TRUE` would compute all margins.
`subset` | Specified if casting should be done on a subset of the data. Ex: `subset = .(col1 <= 5)` or `subset = .(variable != "January")`.
`fill` | Value with which to fill missing cells. If `fun.aggregate` is present, takes the value by applying the function on a 0-length vector.
`drop` | `FALSE` will cast by including all missing combinations. NEW: Following #1512, `c(FALSE, TRUE)` will only include all missing combinations of formula `LHS`. And `c(TRUE, FALSE)` will only include all missing combinations of formula RHS. See Examples.
`value.var` | Name of the column whose values will be filled to cast. Function 'guess()' tries to, well, guess this column automatically, if none is provided. NEW: it is now possible to cast multiple `value.var` columns simultaneously. See Examples.
`verbose` | Not used yet. May be dropped in the future or used to provide informative messages through the console.

### Details

The cast formula takes the form `LHS ~ RHS`, ex: `var1 + var2 ~ var3`. The order of entries in the formula is essential. There are two special variables: `.` and `...`. `.` represents no variable; `...` represents all variables not otherwise mentioned in `formula`; see Examples.

`dcast` also allows `value.var` columns of type `list`.

When variable combinations in `formula` doesn't identify a unique value in a cell, `fun.aggregate` will have to be specified, which defaults to `length` if unspecified. The aggregating function should take a vector as input and return a single value (or a list of length one) as output. In cases where `value.var` is a list, the function should be able to handle a list input and provide a single value or list of length one as output.

If the formula's LHS contains the same column more than once, ex: `dcast(DT, x+x~ y)`, then the answer will have duplicate names. In those cases, the duplicate names are renamed using `make.unique` so that key can be set without issues.

Names for columns that are being cast are generated in the same order (separated by an underscore, `_`) from the (unique) values in each column mentioned in the formula RHS.

From `v1.9.4`, `dcast` tries to preserve attributes whereever possible.

NEW: From `v1.9.6`, it is possible to cast multiple `value.var` columns and also cast by providing multiple `fun.aggregate` functions. Multiple `fun.aggregate` functions should be provided as a `list`, for e.g., `list(mean, sum, function(x) paste(x, collapse="")`. `value.var` can be either a character vector or list of length=1, or a list of length equal to `length(fun.aggregate)`. When `value.var` is a character vector or a list of length 1, each function mentioned under `fun.aggregate` is applied to every column specified under `value.var` column. When `value.var` is a list of length equal to `length(fun.aggregate)` each element of `fun.aggregate` is appled to each element of `value.var` column.

### Value

A keyed `data.table` that has been cast. The key columns are equal to the variables in the `formula` LHS in the same order.

### See Also

`melt.data.table`, `rowid`, https://cran.r-project.org/package=reshape

### Examples

    require(data.table)
    names(ChickWeight) <- tolower(names(ChickWeight))
    DT <- melt(as.data.table(ChickWeight), id=2:4) # calls melt.data.table

    # dcast is a S3 method in data.table from v1.9.6
    dcast(DT, time ~ variable, fun=mean)
    dcast(DT, diet ~ variable, fun=mean)
    dcast(DT, diet+chick ~ time, drop=FALSE)
    dcast(DT, diet+chick ~ time, drop=FALSE, fill=0)

    # using subset
    dcast(DT, chick ~ time, fun=mean, subset=.(time < 10 & chick < 20))

    # drop argument, #1512
    DT <- data.table(v1 = c(1.1, 1.1, 1.1, 2.2, 2.2, 2.2),
                     v2 = factor(c(1L, 1L, 1L, 3L, 3L, 3L), levels=1:3),
                     v3 = factor(c(2L, 3L, 5L, 1L, 2L, 6L), levels=1:6),
                     v4 = c(3L, 2L, 2L, 5L, 4L, 3L))
    # drop=TRUE
    dcast(DT, v1 + v2 ~ v3)                      # default is drop=TRUE
    dcast(DT, v1 + v2 ~ v3, drop=FALSE)          # all missing combinations of both LHS and RHS
    dcast(DT, v1 + v2 ~ v3, drop=c(FALSE, TRUE)) # all missing combinations of only LHS
    dcast(DT, v1 + v2 ~ v3, drop=c(TRUE, FALSE)) # all missing combinations of only RHS

    # using . and ...
    DT <- data.table(v1 = rep(1:2, each = 6),
                     v2 = rep(rep(1:3, 2), each = 2),
                     v3 = rep(1:2, 6),
                     v4 = rnorm(6))
    dcast(DT, ... ~ v3, value.var = "v4") #same as v1 + v2 ~ v3, value.var = "v4"
    dcast(DT, v1 + v2 + v3 ~ ., value.var = "v4")

    ## for each combination of (v1, v2), add up all values of v4
    dcast(DT, v1 + v2 ~ ., value.var = "v4", fun.aggregate = sum)

    ## Not run:
    # benchmark against reshape2's dcast, minimum of 3 runs
    set.seed(45)
    DT <- data.table(aa=sample(1e4, 1e6, TRUE),
          bb=sample(1e3, 1e6, TRUE),
          cc = sample(letters, 1e6, TRUE), dd=runif(1e6))
    system.time(dcast(DT, aa ~ cc, fun=sum)) # 0.12 seconds
    system.time(dcast(DT, bb ~ cc, fun=mean)) # 0.04 seconds
    # reshape2::dcast takes 31 seconds
    system.time(dcast(DT, aa + bb ~ cc, fun=sum)) # 1.2 seconds

    ## End(Not run)

    # NEW FEATURE - multiple value.var and multiple fun.aggregate
    dt = data.table(x=sample(5,20,TRUE), y=sample(2,20,TRUE),
                    z=sample(letters[1:2], 20,TRUE), d1 = runif(20), d2=1L)
    # multiple value.var
    dcast(dt, x + y ~ z, fun=sum, value.var=c("d1","d2"))
    # multiple fun.aggregate
    dcast(dt, x + y ~ z, fun=list(sum, mean), value.var="d1")
    # multiple fun.agg and value.var (all combinations)
    dcast(dt, x + y ~ z, fun=list(sum, mean), value.var=c("d1", "d2"))
    # multiple fun.agg and value.var (one-to-one)
    dcast(dt, x + y ~ z, fun=list(sum, mean), value.var=list("d1", "d2"))

[Package data.table version 1.10.4-1 Index]