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data.tableのidateとitimeを1時間増やす方法はありますか？data.table：時間ごとにIDateTimeを時間単位で遅らせる
私はデータを遅らせるために、here Christoph_Jと記述したいと思います。
は私のデータは次のように私は上記のSO-答えからコードとそれに遅れることを試みた。この
> dt
idate itime windgeschwindigkeit
1: 1958-02-01 00:00:00 -0.9049475
2: 1958-02-01 01:00:00 -0.9049475
3: 1958-02-01 02:00:00 -0.9049475
4: 1958-02-01 03:00:00 -1.0049475
5: 1958-02-01 04:00:00 -2.0049475
---
498020: 2014-11-24 19:00:00 -1.0852256
498021: 2014-11-24 20:00:00 -0.7852256
498022: 2014-11-24 21:00:00 -0.8852256
498023: 2014-11-24 22:00:00 -1.0852256
498024: 2014-11-24 23:00:00 -1.3852256
次のようになります。
期待出力になりsetkeyv(dt, c("idate","itime"))
m_col = "windgeschwindigkeit"
pm_col = parse(text="windgeschwindigkeit")
lagg = 1
dt[, paste0(m_col,"_",lagg) :=
dt[list(idate,itime+lagg*3600), eval(pm_col), roll=-1]]
：
新しい列が1時間遅れています。 BUT（下記参照）
> dt
idate itime windgeschwindigkeit windgeschwindigkeit_1
1: 1958-02-01 00:00:00 -0.9049475 -0.9049475
2: 1958-02-01 01:00:00 -0.9049475 -0.9049475
3: 1958-02-01 02:00:00 -0.9049475 -1.0049475
4: 1958-02-01 03:00:00 -1.0049475 -2.0049475
5: 1958-02-01 04:00:00 -2.0049475 -2.0049475
---
498020: 2014-11-24 19:00:00 -1.0852256 -0.7852256
498021: 2014-11-24 20:00:00 -0.7852256 -0.8852256
498022: 2014-11-24 21:00:00 -0.8852256 -1.0852256
498023: 2014-11-24 22:00:00 -1.0852256 -1.3852256
498024: 2014-11-24 23:00:00 -1.3852256 NA
しかし、24の倍数であるすべての行が1時24分とDATA-に午前0時23分からlist(idate,itime+lagg*3600)増加 ITIMEの時間として今NAありますテーブルの傾き一致itimeの時間すべての結果に一致します。
> dt[c(24,48)]
idate itime windgeschwindigkeit windgeschwindigkeit_1
1: 1958-02-01 23:00:00 0.5950525 NA
2: 1958-02-02 23:00:00 4.0939842 NA
1時間で、この例の増加IDATEとITIMEを修正するためにどのように任意のアイデア？ ご迷惑をおかけして申し訳ございません。
私はas.POSIXctで、「回避策」次でそれを行うために管理が、それは非常に効率的ではありません。私のデータの頭の
setkeyv(dt, c("idate","itime"))
m_col = "windgeschwindigkeit"
pm_col = parse(text="windgeschwindigkeit")
lagg = 1
new_time <- dt[,IDateTime(as.POSIXct(idate)+itime+lagg*3600)]
dt[, paste0(m_col,"_",lagg) :=
dt[new_time, eval(pm_col), roll=-1]]
はdput：
structure(list(idate = structure(c(-4352L, -4352L, -4352L, -4352L,
-4352L, -4352L, -4352L, -4352L, -4352L, -4352L, -4352L, -4352L,
-4352L, -4352L, -4352L, -4352L, -4352L, -4352L, -4352L, -4352L,
-4352L, -4352L, -4352L, -4352L, -4351L, -4351L, -4351L, -4351L,
-4351L, -4351L, -4351L, -4351L, -4351L, -4351L, -4351L, -4351L,
-4351L, -4351L, -4351L, -4351L, -4351L, -4351L, -4351L, -4351L,
-4351L, -4351L, -4351L, -4351L), class = c("IDate", "Date")),
itime = structure(c(0L, 3600L, 7200L, 10800L, 14400L, 18000L,
21600L, 25200L, 28800L, 32400L, 36000L, 39600L, 43200L, 46800L,
50400L, 54000L, 57600L, 61200L, 64800L, 68400L, 72000L, 75600L,
79200L, 82800L, 0L, 3600L, 7200L, 10800L, 14400L, 18000L,
21600L, 25200L, 28800L, 32400L, 36000L, 39600L, 43200L, 46800L,
50400L, 54000L, 57600L, 61200L, 64800L, 68400L, 72000L, 75600L,
79200L, 82800L), class = "ITime"), windgeschwindigkeit = c(-0.904947510665982,
-0.904947510665982, -0.904947510665982, -1.00494751066598,
-2.00494751066598, -2.00494751066598, -2.90494751066598,
-2.50494751066598, -2.50494751066598, -1.40494751066598,
-1.50494751066598, -1.30494751066598, -1.00494751066598,
-0.704947510665983, -0.504947510665983, -0.504947510665983,
-0.204947510665982, -0.104947510665983, 0.0950524893340177,
1.09505248933402, 0.195052489334017, -0.204947510665982,
0.0950524893340177, 0.595052489334018, 1.79398421777773,
2.99398421777773, 3.39398421777773, 3.29398421777773, 2.99398421777773,
2.89398421777773, 1.89398421777773, 0.593984217777727, 0.293984217777727,
-0.706015782222273, -0.706015782222273, -0.806015782222273,
-0.406015782222273, 0.893984217777727, -0.206015782222273,
-0.606015782222273, -0.00601578222227328, 0.693984217777727,
1.29398421777773, 2.49398421777773, 3.79398421777773, 4.29398421777773,
3.99398421777773, 4.09398421777773)), .Names = c("idate",
"itime", "windgeschwindigkeit"), row.names = c(NA, -48L), class = c("data.table",
"data.frame"), sorted = c("idate", "itime"))