Calcolo minuti al giorno in base agli orari di inizio e fine

Question

Come si estrae i minuti da un intervallo di tempo in modo che venga restituito il numero di minuti da ciascuna data?

Ho un dataframe con il caso ID, avviare & tempi di fermo, e l'intervallo di tempo totale trascorso in minuti. Ho bisogno di capire quanti minuti erano in ogni data per ogni caso.

Questo è un po 'simile a this question ma non sono riuscito a trasferire tale approccio a questa situazione.

Il set di dati originale è strutturato in questo modo, tuttavia la soluzione finale dovrà aumentare per consentire molti altri casi (vedere il set di dati alternativo di seguito).

dati originali

>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 

uscita desiderata

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 dei dati originali

> 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 dei dati alternativi più grandi impostato

> 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

Ecco un modo.

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)) 

uscita è:

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)) 

e uscita:

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

Qui una soluzione data.table. L'idea è abbastanza semplice (forse non molto efficiente): Crea un vettore di minuti per ciascun caso, trasformalo in un vettore di giorni e calcola la frequenza utilizzando la tabella.

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