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fix for melt with na.rm=TRUE and list column value #4737

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Merged
mattdowle merged 5 commits into from
May 9, 2021
Merged

fix for melt with na.rm=TRUE and list column value #4737

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16ef573
test failing for na.rm=TRUE and list column value
tdhock Oct 3, 2020
92bc0c9
do not ignore narm
tdhock Oct 3, 2020
821c981
use na.omit in test with na.rm=TRUE
tdhock Oct 3, 2020
eef16a9
Merge branch 'master' into fix-melt-narm-list-column
mattdowle May 9, 2021
cb510cf
test numbers
mattdowle May 9, 2021
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6 changes: 5 additions & 1 deletion inst/tests/tests.Rraw
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Original file line number Diff line number Diff line change
Expand Up @@ -3019,6 +3019,10 @@ test(1034, as.data.table(x<-as.character(sample(letters, 5))), data.table(V1=x))
test(1035.014, melt(data.table(a1=1, b1=1, b2=2), na.rm=TRUE, measure.vars=list(a="a1", b=c("b1","b2"))), data.table(variable=factor(1,c("1","2")), a=1, b=1))
test(1035.015, melt(data.table(a=1+2i, b=1), id.vars="a"), error="Unknown column type 'complex' for column 'a' in 'data'")

# na.rm=TRUE with list column value, PR#4737
test(1035.016, melt(data.table(a1=1, b1=list(1:2), b2=list(c('foo','bar'))), na.rm=TRUE, measure.vars=list(a="a1", b=c("b1","b2"))), data.table(variable=factor(1), a=1, b=list(1:2)))
test(1035.017, melt(data.table(a1=1, b1=1, b2=2), na.rm=TRUE, measure.vars=list(a="a1", b=c("b1","b2"))), data.table(variable=factor(1), a=1, b=1))#this worked even before the PR.

ans1 = cbind(DT[, c(1,2,8), with=FALSE], variable=factor("l_1"))
ans1[, value := DT$l_1]
test(1035.02, melt(DT, id.vars=c("i_1", "i_2", "l_2"), measure.vars=c("l_1")), ans1)
Expand All @@ -3041,7 +3045,7 @@ test(1034, as.data.table(x<-as.character(sample(letters, 5))), data.table(V1=x))
test(1035.051, ans1, melt(DT, id.vars="id", measure.vars=list(c(5, 6), c(7, 8))))
test(1035.052, melt(DT, id.vars="id", measure.vars=list(as.raw(0))),
error="Unknown 'measure.vars' type raw")
test(1035.06, ans1, melt(DT, id.vars="id", measure.vars=list(5:6, 7:8), na.rm=TRUE)) # should've no effect
test(1035.06, na.omit(ans1), melt(DT, id.vars="id", measure.vars=list(5:6, 7:8), na.rm=TRUE))
test(1035.07, ans1, melt(DT, id.vars="id", measure.vars=patterns("d_", "l_")))
# melt retains ordered factors!
test(1035.08, melt(DT, id.vars="id", measure.vars=c("f_1", "f_2"), value.factor=TRUE)$value, factor(c(as.character(DT$f_1), as.character(DT$f_2)), ordered=TRUE))
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4 changes: 0 additions & 4 deletions src/fmelt.c
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Expand Up @@ -448,10 +448,6 @@ SEXP getvaluecols(SEXP DT, SEXP dtnames, Rboolean valfactor, Rboolean verbose, s
SEXP thisvaluecols = VECTOR_ELT(data->valuecols, i);
if (!data->isidentical[i])
warning(_("'measure.vars' [%s] are not all of the same type. By order of hierarchy, the molten data value column will be of type '%s'. All measure variables not of type '%s' will be coerced too. Check DETAILS in ?melt.data.table for more on coercion.\n"), concat(dtnames, thisvaluecols), type2char(data->maxtype[i]), type2char(data->maxtype[i]));
if (data->maxtype[i] == VECSXP && data->narm) {
if (verbose) Rprintf(_("The molten data value type is a list at item %d. 'na.rm=TRUE' is ignored.\n"), i+1);
data->narm = FALSE;
}
}
if (data->narm) {
SEXP seqcols = PROTECT(seq_int(data->lvalues, 1));
Expand Down