```
set.seed(123)
DT = data.table(x1 = rep(letters[1:2], 6),
x2 = rep(letters[3:5], 4),
x3 = rep(letters[5:8], 3),
y = rnorm(12))
DT = DT[sample(.N)]
DF = as.data.frame(DT)
# split consistency with data.frame: `x, f, drop`
all.equal(
split(DT, list(DT$x1, DT$x2)),
lapply(split(DF, list(DF$x1, DF$x2)), setDT)
)
# nested list using `flatten` arguments
split(DT, by=c("x1", "x2"))
split(DT, by=c("x1", "x2"), flatten=FALSE)
# dealing with factors
fdt = DT[, c(lapply(.SD, as.factor), list(y=y)), .SDcols=x1:x3]
fdf = as.data.frame(fdt)
sdf = split(fdf, list(fdf$x1, fdf$x2))
all.equal(
split(fdt, by=c("x1", "x2"), sorted=TRUE),
lapply(sdf[sort(names(sdf))], setDT)
)
# factors having unused levels, drop FALSE, TRUE
fdt = DT[, .(x1 = as.factor(c(as.character(x1), "c"))[-13L],
x2 = as.factor(c("a", as.character(x2)))[-1L],
x3 = as.factor(c("a", as.character(x3), "z"))[c(-1L,-14L)],
y = y)]
fdf = as.data.frame(fdt)
sdf = split(fdf, list(fdf$x1, fdf$x2))
all.equal(
split(fdt, by=c("x1", "x2"), sorted=TRUE),
lapply(sdf[sort(names(sdf))], setDT)
)
sdf = split(fdf, list(fdf$x1, fdf$x2), drop=TRUE)
all.equal(
split(fdt, by=c("x1", "x2"), sorted=TRUE, drop=TRUE),
lapply(sdf[sort(names(sdf))], setDT)
)
```

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