Obliczanie minut dziennie z uwzględnieniem czasu rozpoczęcia i zakończenia

Question

W jaki sposób można wyodrębnić minuty z przedziału czasowego, tak aby liczba minut z każdej daty została zwrócona?

Posiadam ramkę danych z identyfikatorem przypadku, rozpoczynając od & czasów zakończenia i całkowity czas, jaki upłynął w minutach. Muszę dowiedzieć się, ile minut przypada na każdą datę dla każdego przypadku.

To jest trochę podobne do this question, ale nie mogłem przenieść tego podejścia do tej sytuacji.

Oryginalny zestaw danych jest skonstruowany w ten sposób, jednak ostateczne rozwiązanie będzie musiało zostać skalowane, aby umożliwić wiele innych przypadków (patrz alternatywny zestaw danych poniżej).

oryginalne dane

>so 
    Case    Start    Stop Minutes 
1 A 2013-01-10 18:00:00 2013-01-10 20:30:00 150 mins 
2 B 2013-01-15 22:45:00 2013-01-16 00:15:00 90 mins 
3 C 2013-01-20 22:00:00 2013-01-22 02:00:00 1680 mins 
4 D 2013-01-27 12:00:00 2013-01-28 06:00:00 1080 mins 
5 E 2013-01-01 00:00:00 2013-01-01 02:00:00 120 mins 
6 F 2013-01-02 08:00:00 2013-01-03 07:00:00 1380 mins 

sygnał wyjściowy

Case  Date Minutes 
1 A 2013-01-10  150 
2 B 2013-01-15  75 
3 B 2013-01-16  15 
4 C 2013-01-20  120 
5 C 2013-01-21 1440 
6 C 2013-01-22  120 
7 D 2013-01-27  720 
8 D 2013-01-28  360 
9 E 2013-01-01  120 
10 F 2013-01-02  960 
11 F 2013-01-03  420 

dput danych pierwotnych

> dput(so) 
structure(list( 
Case = structure(1:5, .Label = c("A", "B", "C", "D", "E"), class = "factor"), 
Start = structure(c(2L, 3L, 4L, 5L, 1L), .Label = c("2013-01-01 00:00:00", "2013-01-10 18:00:00", "2013-01-15 22:45:00", "2013-01-20 22:00:00", "2013-01-27 12:00:00"), class = "factor"), 
Stop = structure(c(2L, 3L, 4L, 5L, 1L), .Label = c("2013-01-01 02:00:00", "2013-01-10 20:30:00", "2013-01-16 00:15:00", "2013-01-22 02:00:00", "2013-01-28 06:00:00"), class = "factor"), 
Minutes = structure(c(150, 90, 1680, 1080, 120), tzone = "", units = "mins", class = "difftime") 
), 
.Names = c("Case","Start", "Stop", "Minutes"), 
row.names = c(NA, -5L), 
class = "data.frame") 

dput alternatywnych większych zestawu danych

> dput(so_alt) 
structure(list(Case = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 1L, 2L), .Label = c("A", "B", "C", "D", "E", "F", "G", "H"), class = "factor"),  Start = structure(c(12L, 13L, 4L, 5L, 19L, 20L, 21L, 30L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 9L, 6L, 7L, 8L, 3L, 10L, 11L, 14L, 15L, 16L), .Label = c("2012-10-25 18:10:00", "2012-11-01 20:18:00", "2012-11-16 17:45:00", "2012-12-06 01:00:00", "2012-12-06 08:00:00", "2012-12-26 13:15:00", "2012-12-29 19:50:00", "2012-12-30 00:00:00", "2013-01-01 01:46:00", "2013-01-10 20:15:00", "2013-01-11 09:00:00", "2013-01-29 17:00:00", "2013-02-05 21:30:00", "2013-02-21 01:50:00", "2013-02-21 09:25:00", "2013-02-21 12:20:00", "2013-02-22 21:45:00", "2013-02-24 15:30:00", "2013-03-01 10:10:00", "2013-03-06 16:15:00", "2013-03-07 20:00:00", "2013-03-12 21:00:00", "2013-03-13 05:15:00", "2013-03-14 00:45:00", "2013-03-14 11:30:00", "2013-03-15 21:00:00", "2013-03-16 08:15:00", "2013-03-17 06:45:00", "2013-03-18 18:04:00", "2013-03-21 21:40:00"), class = "factor"), Stop = structure(c(12L, 13L, 4L, 5L, 19L, 20L, 21L, 30L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 9L, 6L, 7L, 8L, 3L, 10L, 11L, 14L, 15L, 16L), .Label = c("2012-10-25 21:30:00", "2012-11-03 08:00:00", "2012-11-17 08:45:00", "2012-12-06 05:00:00", "2012-12-06 09:30:00", "2012-12-29 19:50:00", "2012-12-30 00:00:00", "2012-12-31 20:00:00", "2013-01-02 06:00:00", "2013-01-10 22:13:00", "2013-01-12 03:30:00", "2013-01-30 07:45:00", "2013-02-06 07:30:00", "2013-02-21 09:25:00", "2013-02-21 12:20:00", "2013-02-22 11:30:00", "2013-02-24 10:15:00", "2013-02-24 16:45:00", "2013-03-06 07:45:00", "2013-03-07 07:30:00", "2013-03-08 08:00:00", "2013-03-13 05:00:00", "2013-03-14 00:45:00", "2013-03-14 10:15:00", "2013-03-14 19:00:00", "2013-03-15 22:36:00", "2013-03-16 19:00:00", "2013-03-18 15:15:00", "2013-03-18 22:00:00", "2013-03-22 08:30:00"), class = "factor"), Minutes = structure(c(885, 600, 240, 90, 7055, 915, 720, 650, 480, 1170, 570, 450, 96, 645, 1950, 236, 1694, 4715, 250, 2640, 900, 118, 1110, 455, 175, 1390), class = "difftime", units = "mins")), .Names = c("Case", "Start", "Stop", "Minutes"), row.names = c(NA, 26L), class = "data.frame") 
> 

Answer 1

Oto sposób.

library(plyr) 

ddply(ddply(so, 1, function(x) { 
    d1 <- as.Date(x$Start) 
    d2 <- as.Date(x$Stop) 
    if (d1 == d2) data.frame(date = d1, min = x$Minutes) 
    else { 
     ret <- rbind(data.frame(date=d1, min = difftime(as.POSIXct(paste(d1+1, "00:00:00")), as.POSIXct(x$Start), units = "mins")), 
     data.frame(date=d2, min=difftime(as.POSIXct(x$Stop), as.POSIXct(paste(d2, "00:00:00")), units = "mins"))) 
     if (d2-d1>1) { 
      ret <- rbind(ret, data.frame(date = seq(d1+1, d2-1, by = "day"), min = 60*24)) 
     } 
     ret 
    } 
}), .(Case, date), summarise, min = sum(min)) 

wyjściowa wynosi:

Case  date  min 
1 A 2013-01-10 150 mins 
2 B 2013-01-15 75 mins 
3 B 2013-01-16 15 mins 
4 C 2013-01-20 120 mins 
5 C 2013-01-21 1440 mins 
6 C 2013-01-22 120 mins 

---

The final version here: 

ddply(ddply(data.frame(.id = 1:nrow(so_alt), so_alt), .(.id, Case), function(x) { 
    d1 <- as.Date(x$Start) 
    d2 <- as.Date(x$Stop) 
    if (d1 == d2) data.frame(date = d1, min = x$Minutes) 
    else { 
     ret <- rbind(data.frame(date=d1, min = difftime(as.POSIXct(paste(d1+1, "00:00:00")), as.POSIXct(x$Start), units = "mins")), 
     data.frame(date=d2, min=difftime(as.POSIXct(x$Stop), as.POSIXct(paste(d2, "00:00:00")), units = "mins"))) 
     if (d2-d1>1) { 
      ret <- rbind(ret, data.frame(date = seq(d1+1, d2-1, by = "day"), min = 60*24)) 
     } 
     ret 
    } 
}), .(Case, date), summarise, min = sum(min)) 

i wyjście:

Case  date  min 
1  A 2013-01-01 1334 mins 
2  A 2013-01-02 360 mins 
3  A 2013-01-29 420 mins 
4  A 2013-01-30 465 mins 
5  A 2013-02-21 175 mins 
6  A 2013-03-12 180 mins 
7  A 2013-03-13 300 mins 
8  B 2012-12-26 645 mins 
9  B 2012-12-27 1440 mins 
10 B 2012-12-28 1440 mins 
11 B 2012-12-29 1190 mins 
12 B 2013-02-05 150 mins 
13 B 2013-02-06 450 mins 
14 B 2013-02-21 700 mins 
15 B 2013-02-22 690 mins 
16 B 2013-03-13 1125 mins 
17 B 2013-03-14 45 mins 
18 C 2012-12-06 240 mins 
19 C 2012-12-29 250 mins 
20 C 2012-12-30 0 mins 
21 C 2013-03-14 570 mins 
22 D 2012-12-06 90 mins 
23 D 2012-12-30 1440 mins 
24 D 2012-12-31 1200 mins 
25 D 2013-03-14 450 mins 
26 E 2012-11-16 375 mins 
27 E 2012-11-17 525 mins 
28 E 2013-03-01 830 mins 
29 E 2013-03-02 1440 mins 
30 E 2013-03-03 1440 mins 
31 E 2013-03-04 1440 mins 
32 E 2013-03-05 1440 mins 
33 E 2013-03-06 465 mins 
34 E 2013-03-15 96 mins 
35 F 2013-01-10 118 mins 
36 F 2013-03-06 465 mins 
37 F 2013-03-07 450 mins 
38 F 2013-03-16 645 mins 
39 G 2013-01-11 900 mins 
40 G 2013-01-12 210 mins 
41 G 2013-03-07 240 mins 
42 G 2013-03-08 480 mins 
43 G 2013-03-17 1035 mins 
44 G 2013-03-18 915 mins 
45 H 2013-02-21 455 mins 
46 H 2013-03-18 236 mins 
47 H 2013-03-21 140 mins 
48 H 2013-03-22 510 mins 

Answer 2

Oto rozwiązanie data.table. Pomysł jest dość prosty (może niezbyt wydajny): Utwórz wektor minut dla każdego przypadku, przekształć go na wektor dni i oblicz częstotliwość za pomocą tabeli.

DT <- as.data.table(dat) 
DT[,list(seqD= seq(as.Date(Start),as.Date(Stop),'day'), 
     duration= { 
      seq.minus <- seq(as.POSIXct(Start), 
            as.POSIXct(Stop),'min')[-1] 
      as.data.frame(table(format(seq.minus,'%Y-%m-%d')))$Freq 
      }), 
    by = list(Case)] 

    Case  seqD duration 
1: A 2013-01-10  150 
2: B 2013-01-15  74 
3: B 2013-01-16  16 
4: C 2013-01-20  119 
5: C 2013-01-21  1440 
6: C 2013-01-22  121