[datatable-help] subset between data.table list and single data.table object

[iembry]

Hi Matthew, partly based on your suggestion I  have the following R code:

big = rbindlist(lapply(sitefiles,freadDataRatingDepotFiles)) 
big <- setnames(big,c("y", "shift", "x", "stor")) 
big <- big[, y:=as.numeric(y)]
big <- big[, x:=as.numeric(x)]
big <- big[, shift:=as.numeric(shift)]
big <- big[, c("stor"):=NULL]
big <- na.omit(big)
big <- big[,y:=y+shift] 
big <- big[,shift:=NULL] 

Thus instead of a list of 59 data.table objects I have one list of over
100,000 rows. 

How do I know which row range belongs to a certain data.table object (59 of
them) for the other calculations?

As before I want to subset big (or the list of 59 data.tables) based on
their connection to aimall (see below). aimall contains each of the 59
station numbers & the order of aimall matches the order of the 59
data.tables.

Does this help clarify what I had previously asked?

Thank you.

Irucka



str(big)
Classes ‘data.table’ and 'data.frame':	112253 obs. of  2 variables:
 $ y: num  14.8 14.8 14.8 14.8 14.8 ...
 $ x: num  7900 7920 7930 7950 7970 7980 8000 8010 8030 8050 ...
 - attr(*, ".internal.selfref")=<externalptr> 

dput(aimall)
structure(list(site_no = c("02437100", "02446500", "02467000", 
"03217500", "03219500", "03227500", "03230700", "03231500", "03439000", 
"03441000", "03455000", "03479000", "04185000", "04186500", "04189000", 
"04191500", "04192500", "04193500", "06191500", "06214500", "06218500", 
"06225500", "06228000", "06235500", "06276500", "06279500", "06287000", 
"06289000", "06311000", "06313500", "06317000", "06320000", "06320500", 
"06323000", "06324000", "06324500", "06326500", "06329500", "06342500", 
"06426500", "06428500", "06436000", "06437000", "06438000", "06818000", 
"06821500", "06856600", "06860000", "06864000", "06864500", "06865500", 
"06877600", "06887500", "06889000", "06891000", "06893000", "06934500", 
"07010000", "07289000"), mean = c(3882.65, 819.82, 23742.37, 
224.72, 496.79, 1491.39, 3170.14, 3682.46, 237.02, 127.9, 2955.14, 
176.1, 345.72, 296.23, 275.35, 1870.93, 4544.74, 5157.63, 3106.7, 
6940.54, 167.04, 1172.53, 771.23, 559.23, 407.46, 2144.53, 3384.37, 
148.67, 14.99, 195.91, 267.9, 47.49, 63.49, 96.74, 184.16, 446.52, 
565.5, 12419.4, 22372.86, 23.34, 92.56, 100.45, 296.65, 391.31, 
43534.12, 16.65, 915.93, 20.16, 197.09, 227.78, 274.43, 1517.04, 
5042.7, 5632.7, 7018.45, 52604.19, 81758.03, 186504.25, 755685.3
), p50 = c(1830, 382, 10400, 50, 140, 500, 1520, 1600, 188, 99, 
2260, 115, 130, 75, 62, 460, 1470, 1700, 1390, 3670, 80, 559, 
380, 257, 223, 1550, 2730, 82, 3.8, 120, 130, 23, 46, 34, 86, 
216, 231, 7900, 20400, 2.9, 36, 7.5, 120, 114, 38200, 6.3, 430, 
1, 37, 58, 73, 541, 2320, 2620, 3300, 43200, 61200, 147000, 687000
)), .Names = c("site_no", "mean", "p50"), row.names = c(4463L, 
4495L, 4586L, 5353L, 5357L, 5378L, 5393L, 5397L, 6165L, 6169L, 
6203L, 6253L, 7304L, 7308L, 7317L, 7326L, 7328L, 7330L, 9633L, 
9698L, 9710L, 9725L, 9733L, 9756L, 9832L, 9840L, 9877L, 9889L, 
9988L, 9997L, 10010L, 10019L, 10022L, 10029L, 10031L, 10032L, 
10041L, 10052L, 10118L, 10284L, 10288L, 10306L, 10317L, 10322L, 
11165L, 11185L, 11261L, 11268L, 11281L, 11283L, 11284L, 11325L, 
11363L, 11370L, 11401L, 11421L, 11606L, 11626L, 12714L), class =
"data.frame")



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