The request for a date column results in a bit of redundancy beyond
what tapply would have produced, but here it is as specified:
> data.frame(dnames=names(tapply(X$PL_Pos, X$MyDate, sum)), dsums =
tapply(X$PL_Pos, X$MyDate, sum) )
dnames dsums
2009-08-03 2009-08-03 174
2009-08-04 2009-08-04 -26
2009-08-05 2009-08-05 614
2009-08-06 2009-08-06 318
2009-08-10 2009-08-10 414
2009-08-11 2009-08-11 -626
2009-08-12 2009-08-12 544
2009-08-13 2009-08-13 -106
2009-08-17 2009-08-17 -146
2009-08-19 2009-08-19 1004
2009-08-20 2009-08-20 568
2009-08-24 2009-08-24 -716
2009-08-25 2009-08-25 -132
2009-08-26 2009-08-26 8
2009-08-27 2009-08-27 622
On Aug 28, 2009, at 12:37 PM, Mark Knecht wrote:
Hi,
I wonder if someone can suggest how to create a new data.frame Y
from X where X$PL_Pos is summed by each unique X$MyDate. Y should end
up with two (or more) columns Y$MyDate and Y$PL_Sum with its value
being the cumsum of all the values in X for that date. - a 'daily
cumsum'.
Thanks,
Mark
TStoDate = function (TSDate) {
X = strptime(TSDate + 19e6L, "%Y%m%d")
return(as.Date(X))
}
X = structure(list(EnDate = c(1090803,
1090804, 1090805, 1090806, 1090806, 1090810, 1090811, 1090812,
1090813, 1090817, 1090819, 1090820, 1090820, 1090824, 1090825,
1090825, 1090826, 1090826, 1090827, 1090827, 1090827), PL_Pos = c(174,
-26, 614, 344, -26, 414, -626, 544, -106, -146, 1004, 344, 224,
-716, -176, 44, 354, -346, -296, 564, 354)), .Names = c("EnDate",
"PL_Pos"),
class = "data.frame", row.names = c("733",
"734", "3631", "3641", "736", "2403", "2413", "3651", "3661",
"3671", "3681", "3691", "1303", "3701", "1304", "1305", "2432",
"1306", "3712", "1307", "4214"))
X$MyDate = TStoDate(X$EnDate)
X
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