teilen, transponieren und sammeln Datenrahmen

Question

Ich muss die Daten im Datenrahmen sammeln und transponieren, stündliche Werte sollten in einer Spalte sein. Die erste Spalte sollte Datum mit Stunde und Sekunde transponierten Stundenwerten sein.

Beispieldaten:

structure(list(Year = c(2016L, 2016L), JDay = 1:2, Hour_1 = c(2.59, 
5.95), Hour_2 = c(2.19, 5.84), Hour_3 = c(1.84, 5.75), Hour_4 = c(1.51, 
5.66), Hour_5 = c(1.21, 5.58), Hour_6 = c(0.94, 5.5), Hour_7 = c(0.69, 
5.43), Hour_8 = c(0.45, 5.37), Hour_9 = c(0.23, 5.31), Hour_10 = c(2.18, 
6.19), Hour_11 = c(4.39, 7.16), Hour_12 = c(6.29, 8), Hour_13 = c(7.76, 
8.65), Hour_14 = c(8.68, 9.06), Hour_15 = c(9, 9.2), Hour_16 = c(8.68, 
9.06), Hour_17 = c(7.76, 8.65), Hour_18 = c(7.8, 8.52), Hour_19 = c(7.21, 
7.57), Hour_20 = c(6.85, 6.99), Hour_21 = c(6.59, 6.57), Hour_22 = c(6.39, 
6.25), Hour_23 = c(6.22, 5.98), Hour_24 = c(6.08, 5.75)), .Names = c("Year", 
"JDay", "Hour_1", "Hour_2", "Hour_3", "Hour_4", "Hour_5", "Hour_6", 
"Hour_7", "Hour_8", "Hour_9", "Hour_10", "Hour_11", "Hour_12", 
"Hour_13", "Hour_14", "Hour_15", "Hour_16", "Hour_17", "Hour_18", 
"Hour_19", "Hour_20", "Hour_21", "Hour_22", "Hour_23", "Hour_24" 
), row.names = c(NA, -2L), class = c("tbl_df", "tbl", "data.frame" 

Die Nutzung sammeln nur wird mir alle Hour_1 Werte in, um zu geben ...

gather(OP_daily[, c(5:28)], time,temp, Hour_1:Hour_24) 

Beispiel Ausgabe:

date   temp  
2016-1-1 1:00 2.59 
2016-1-1 2:00 2.19 

Answer 1

Dieser Sound wie die gather suchen Sie:

df %>% 
    gather(-c(Year,JDay), key = "Hour", value = "temp") %>% 
    unite(date,Year,JDay,Hour) %>% 
    mutate(date=as.POSIXct(date,format='%Y_%j_Hour_%H')) %>% 
    arrange(date) 

        date  temp 
       <time> <dbl> 
1 2016-01-01 01:00:00 2.592221 
2 2016-01-01 02:00:00 2.193009 
3 2016-01-01 03:00:00 1.835225 
4 2016-01-01 04:00:00 1.511071 
5 2016-01-01 05:00:00 1.214767 
6 2016-01-01 06:00:00 0.941902 

EDIT

Um zu sehen, wie viele Beobachtungen pro Tag:

res <- df %>% 
    gather(-c(Year,JDay), key = "Hour", value = "temp") %>% 
    unite(date,Year,JDay,Hour) %>% 
    mutate(date=as.POSIXct(date,format='%Y_%j_Hour_%H',tz = "GMT")) %>% 
    arrange(date) 
res%>% 
mutate(date_only=as.Date(date))%>% 
group_by(date_only)%>% 
summarise(count=n()) 

    date_only count 
     <date> <int> 
1 2016-01-01 23 
2 2016-01-02 24 
3 2016-01-03  1