r - Tried streamlining w/ SDCols - got "longer object length is not a multiple of shorter object length" -


i have tried searching stackoverflow , google answers question, couldn't find applied closely enough me able apply it. however, i'm new r, it's may need little walking through it.

if use following code, works fine. 

> dput(b) structure(list(dump_end_shift_date = structure(c(1420070400,  1420070400, 1420156800, 1420156800, 1420243200, 1420243200, 1420329600,  1420329600, 1420416000, 1420416000, 1420502400), class = c("posixct",  "posixt"), tzone = "utc"), quantity_reporting = c(235, 219, 232,  219, 219, 219, 219, 219, 219, 219, 235), wtrecv = c(32.71, 32.71,  20.19, 33.42, 21.61, 21.61, 21.61, 20.19, 21.61, 20.19, 24.2),  lc12 = c(0, 0, 0, 94, 100, 100, 100, 0, 100, 0, 100), lc34 = c(0,  100, 0, 6, 0, 0, 0, 0, 0, 0, 0), lc5 = c(0, 0, 5, 0, 0, 0,  0, 5, 0, 5, 0), = c(25, 0, 60, 0, 0, 0, 0, 60, 0, 60,  0), uc = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), ibc = c(75,  0, 35, 0, 0, 0, 0, 35, 0, 35, 0)), .names = c("dump_end_shift_date",  "quantity_reporting", "wtrecv", "lc12", "lc34", "lc5", "his",  "uc", "ibc"), class = c("data.table", "data.frame"), row.names = c(na,  -11l), .internal.selfref = <pointer: 0x0000000005860788>)  library(data.table)  b_daily <- b[,.(d_tons=sum(quantity_reporting)),by=dump_end_shift_date] b_daily[,"d_wtrecv" := b[,.(d_wtrecv=sum(quantity_reporting*wtrecv)),by=dump_end_shift_date] [,.(round(d_wtrecv/d_tons, digits=2))]] b_daily[,"d_lc12" := b[,.(d_lc12=sum(quantity_reporting*lc12)),by=dump_end_shift_date] [,.(round(d_lc12/d_tons, digits=2))]] b_daily[,"d_lc34" := b[,.(d_lc34=sum(quantity_reporting*lc34)),by=dump_end_shift_date] [,.(round(d_lc34/d_tons, digits=2))]] b_daily[,"d_lc5" := b[,.(d_lc5=sum(quantity_reporting*lc5)),by=dump_end_shift_date] [,.(round(d_lc5/d_tons, digits=2))]] b_daily[,"d_his" := b[,.(d_his=sum(quantity_reporting*his)),by=dump_end_shift_date] [,.(round(d_his/d_tons, digits=2))]] b_daily[,"d_uc" := b[,.(d_uc=sum(quantity_reporting*uc)),by=dump_end_shift_date] [,.(round(d_uc/d_tons, digits=2))]] b_daily[,"d_ibc" := b[,.(d_ibc=sum(quantity_reporting*ibc)),by=dump_end_shift_date] [,.(round(d_ibc/d_tons, digits=2))]]

however, seems inelegant - think should able using sd , sdcols. tried following, test case: 

b_daily2 <- b[,lapply(.sd, function (x) sum(x*b[,quantity_reporting])/sum(b[,quantity_reporting])), by=dump_end_shift_date, .sdcols=c("wtrecv")]  [,.(dump_end_shift_date,d_wtrecv=round(wtrecv, digits=2))]

the resulting numbers little off, , following warning:

"in x * mqd[, quantity_reporting] : longer object length not multiple of shorter object length"

i understand indicates recycling due objects being different lengths...but don't understand why or what. appreciated. apologize in advance if elementary question. thank you.

this arguably inelegant, @ least fits single operation:

b_daily <- b[,{     d_tons      = sum(quantity_reporting)     d_wtrecv    = round( sum(quantity_reporting*wtrecv)/d_tons, digits = 2 )      list(d_tons = d_tons, d_wtrecv = d_wtrecv) },by=dump_end_shift_date]

if there many columns d_wtrecv, names stored in cols = c("wtrecv",...), then...

cols    <- c("wtrecv","lc12","lc34","lc5","his","uc","ibc") b_daily2 <- b[,{     d_tons      = sum(quantity_reporting)     res         = lapply(mget(cols), function(x)                      round( sum(quantity_reporting*x)/d_tons, digits = 2 )                   )      c(list(d_tons = d_tons), setnames(res, paste0("d_",cols))) },by=dump_end_shift_date]

a similar approach using .sdcols possible when a bug related it fixed.

aside. think there feature request allow first column used in computing second, like

# non-working code: b_daily <- b[,.(     d_tons      = sum(quantity_reporting),     d_wtrecv    = round( sum(quantity_reporting*wtrecv) / d_tons, digits = 2) ),by=dump_end_shift_date]

this how mutate in dplyr package works. however, multicolumn case, dplyr more of hassle help, far can figure.

by way, may want wait on rounding. usually, it's idea printing purposes , unnecessarily worsens later calculations.


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