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feat(7614): added redirection of data.frame at dcast and melt to dcast.data.table and melt.data.table #7634

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feat(7614): added redirection of data.frame at dcast and melt to dcast.data.table and melt.data.table #7634

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b0a9b0f
feat(7614): added s3 method at dcast and melt for data.frame
manmita Jan 27, 2026
00fa021
feat(7614): added to news
manmita Jan 27, 2026
c50d1dc
feat(7614): code styling
manmita Jan 27, 2026
fa909a6
feat(7614): bug fix on dcast
manmita Jan 27, 2026
9cc619b
feat(7614): added s3method to namespace
manmita Jan 27, 2026
6502e86
feat(7614): fix test 2365.1 as its calling undefined columns
manmita Jan 27, 2026
b4cd9ed
feat(7614): removed s3method and used redirection incase of data.fram…
manmita Jan 27, 2026
a05b069
feat(7614): code linting
manmita Jan 27, 2026
a3e5465
feat(7614): use call to capture args and redirect to dcast.data.table…
manmita Jan 28, 2026
3cfe6a0
feat(7614): updated tests and dcast, melt
manmita Jan 29, 2026
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2 changes: 2 additions & 0 deletions NEWS.md
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Original file line number Diff line number Diff line change
Expand Up @@ -26,6 +26,8 @@
- Type conversion support in GForce expressions (e.g., `sum(as.numeric(x))` will use GForce, saving the need to coerce `x` in a setup step) [#2934](https://github.com/Rdatatable/data.table/issues/2934)
- Arithmetic operation support in GForce (e.g., `max(x) - min(x)` will use GForce on both `max(x)` and `min(x)`, saving the need to do the subtraction in a follow-up step) [#3815](https://github.com/Rdatatable/data.table/issues/3815)

4. Added support for dcast/melt of data.frames, Thanks @MichaelChirico for the suggestion and @manmita for the PR. [#7614](https://github.com/Rdatatable/data.table/issues/7614)

### BUG FIXES

1. `fread()` with `skip=0` and `(header=TRUE|FALSE)` no longer skips the first row when it has fewer fields than subsequent rows, [#7463](https://github.com/Rdatatable/data.table/issues/7463). Thanks @emayerhofer for the report and @ben-schwen for the fix.
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6 changes: 5 additions & 1 deletion R/fcast.R
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Expand Up @@ -12,6 +12,11 @@ dcast = function(
data, formula, fun.aggregate = NULL, ..., margins = NULL,
subset = NULL, fill = NULL, value.var = guess(data)
) {
if (!is.data.table(data) && is.data.frame(data)){
mc <- match.call()
mc[[1L]] <- as.name("dcast.data.table")
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@MichaelChirico MichaelChirico Jan 29, 2026 •
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Can you confirm this works outside the test suite?

R CMD INSTALL data.table
Rscript -e "library(data.table); dcast(mtcars, cyl ~ gear, value.var='wt', fun.aggregate=mean)"

I am not sure without running it myself whether the frame in which mc is evaluated will be able to see dcast.data.table given that it's not exported.

In the test suite, we define dcast.data.table = data.table:::dcast.data.table, so the test passing is not enough to resolve my apprehension.

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@manmita manmita Jan 29, 2026

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> dcast(mtcars, cyl ~ gear, value.var='wt', fun.aggregate=mean)
Key: <cyl>
     cyl        3        4      5
   <num>    <num>    <num>  <num>
1:     4 2.465000 2.378125 1.8265
2:     6 3.337500 3.093750 2.7700
3:     8 4.104083      NaN 3.3700

This is the output for dcast of mtcars
gives the same output on converting it to data.table

> a = as.data.table(mtcars)
> dcast(a, cyl ~ gear, value.var='wt', fun.aggregate=mean)
Key: <cyl>
     cyl        3        4      5
   <num>    <num>    <num>  <num>
1:     4 2.465000 2.378125 1.8265
2:     6 3.337500 3.093750 2.7700
3:     8 4.104083      NaN 3.3700

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I had also printed the m values while debugging (line 170 of fcast)
and the results for data.table and data.frame were same after these changes and were as expected
eg: m["data"] was giving dt_dcast which was the user arg passed.

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@manmita manmita Jan 29, 2026

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> dcast(mtcars, cyl ~ gear, value.var='wt', fun.aggregate=mean)
$data
mtcars

$formula
cyl ~ gear

$fun.aggregate
mean

$value.var
[1] "wt"

Key: <cyl>
     cyl        3        4      5
   <num>    <num>    <num>  <num>
1:     4 2.465000 2.378125 1.8265
2:     6 3.337500 3.093750 2.7700
3:     8 4.104083      NaN 3.3700
>

when printing m values

return(eval(mc, parent.frame()))
}
UseMethod("dcast", data)
}

Expand Down Expand Up @@ -119,7 +124,6 @@ aggregate_funs = function(funs, vals, sep="_", ...) {
}

dcast.data.table = function(data, formula, fun.aggregate = NULL, sep = "_", ..., margins = NULL, subset = NULL, fill = NULL, drop = TRUE, value.var = guess(data), verbose = getOption("datatable.verbose"), value.var.in.dots = FALSE, value.var.in.LHSdots = value.var.in.dots, value.var.in.RHSdots = value.var.in.dots) {
if (!is.data.table(data)) stopf("'%s' must be a data.table", "data")
drop = as.logical(rep_len(drop, 2L))
if (anyNA(drop)) stopf("'drop' must be logical vector with no missing entries")
if (!isTRUEorFALSE(value.var.in.dots))
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6 changes: 5 additions & 1 deletion R/fmelt.R
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Expand Up @@ -4,6 +4,11 @@
# redirection as well

melt = function(data, ..., na.rm = FALSE, value.name = "value") {
if (!is.data.table(data) && is.data.frame(data)){
mc <- match.call()
mc[[1L]] <- as.name("melt.data.table")
return(eval(mc, parent.frame()))
}
UseMethod("melt", data)
}

Expand Down Expand Up @@ -176,7 +181,6 @@ measurev = function(fun.list, sep="_", pattern, cols, multiple.keyword="value.na
melt.data.table = function(data, id.vars, measure.vars, variable.name = "variable",
value.name = "value", ..., na.rm = FALSE, variable.factor = TRUE, value.factor = FALSE,
verbose = getOption("datatable.verbose")) {
if (!is.data.table(data)) stopf("'%s' must be a data.table", "data")
for(type.vars in c("id.vars","measure.vars")){
sub.lang <- substitute({
if (missing(VAR)) VAR=NULL
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17 changes: 13 additions & 4 deletions inst/tests/tests.Rraw
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Expand Up @@ -13043,8 +13043,8 @@ test(1953.2, melt(DT, id.vars = 'id', measure.vars = patterns(a = 'a', b = 'b',
test(1953.3, melt(DT, id.vars = 'id', measure.vars = patterns(1L)),
error = 'Input patterns must be of type character')
setDF(DT)
test(1953.4, melt.data.table(DT, id.vars = 'id', measure.vars = 'a'),
error = "must be a data.table")
expected = data.table(id = rep(DT$id, 2), variable = factor(rep(c("a1", "a2"), each = 3)), value = c(DT$a1, DT$a2))
test(1953.4, melt(DT, id.vars = "id", measure.vars = c("a1", "a2")), expected)

# appearance order of two low-cardinality columns that were squashed in pr#3124
DT = data.table(A=INT(1,3,2,3,2), B=1:5) # respect groups in 1st column (3's and 2's)
Expand Down Expand Up @@ -13389,8 +13389,7 @@ test(1962.083, guess(DT), '(all)')
setnames(DT, 'V')
test(1962.084, guess(DT), 'V',
message = 'Using.*value column.*override')
setDF(DT)
test(1962.085, dcast.data.table(DT), error = 'must be a data.table')
## removed test of error case 1962.085 for dcast() passed a data.frame for #7614
setDT(DT)
test(1962.086, dcast(DT, a ~ a, drop = NA),
error = "'drop' must be logical vector with no missing entries")
Expand Down Expand Up @@ -21509,3 +21508,13 @@ setdroplevels(x)
setdroplevels(y)
test(2364.2, levels(x$a), levels(y$a))
rm(x, y)

# test for data.frame reshape for melt
df_melt = data.frame(a = 1:2, b = 3:4)
dt_melt = data.table(a = 1:2, b = 3:4)
test(2365.1, melt(df_melt, id.vars=1:2), melt(dt_melt, id.vars=1:2))

# test for data.frame reshape for dcast
df_dcast = data.frame(a = c("x", "y"), b = 1:2, v = 3:4)
dt_dcast = data.table(a = c("x", "y"), b = 1:2, v = 3:4)
test(2365.2, dcast(df_dcast, a ~ b, value.var = "v"), dcast(dt_dcast, a ~ b, value.var = "v"))
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