Comparing dates inside group using same reference - r

Question

I have a data table for different patients ("Spell") and several temperature ("Temp") measures for each patient ("Episode"). I also have the date and time in which each temperature was taken.
Spell Episode Date Temp
1 3 2-1-17 21:00 40
1 2 2-1-17 20:00 36
1 1 1-1-17 10:00 37
2 3 2-1-17 15:00 36
2 2 2-1-17 10:00 37
2 1 1-1-17 8:00 36
3 1 3-1-17 10:00 40
4 3 4-1-17 15:00 36
4 2 3-1-17 12:00 40
4 1 3-1-17 10:00 39
5 7 3-1-17 17:30 36
5 6 2-1-17 17:00 36
5 5 2-1-17 16:00 37
5 1 1-1-17 9:00 36
5 4 1-1-17 14:00 39
5 3 1-1-17 13:00 40
5 2 1-1-17 11:00 39
I am interested in keeping all the measurements done 24h prior to the last one, I have grouped the observations by the spell and reverse date, but I am unsure on how to do the in-group comparison using the same reference (in this case, the first row for each group). The result should be:
Spell Episode Date Temp
1 3 2-1-17 21:00 40
1 2 2-1-17 20:00 36
2 3 2-1-17 15:00 36
2 2 2-1-17 10:00 37
3 1 3-1-17 10:00 40
4 3 4-1-17 15:00 36
5 7 3-1-17 17:30 36
Would appreciate any ideas that point me to the right direction.
Edit: Date is in d-m-yy H:M format. Here's dput from data:
structure(list(Spell = c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 4L, 4L,
4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L), Episode = c(3L, 2L, 1L, 3L,
2L, 1L, 1L, 3L, 2L, 1L, 7L, 6L, 5L, 1L, 4L, 3L, 2L), Date = c("2-1-17 21:00",
"2-1-17 20:00", "1-1-17 10:00", "2-1-17 15:00", "2-1-17 10:00",
"1-1-17 8:00", "3-1-17 10:00", "4-1-17 15:00", "3-1-17 12:00",
"3-1-17 10:00", "3-1-17 17:30", "2-1-17 17:00", "2-1-17 16:00",
"1-1-17 9:00", "1-1-17 14:00", "1-1-17 13:00", "1-1-17 11:00"
), Temp = c(40L, 36L, 37L, 36L, 37L, 36L, 40L, 36L, 40L, 39L,
36L, 36L, 37L, 36L, 39L, 40L, 39L)), .Names = c("Spell", "Episode",
"Date", "Temp"), class = c("data.table", "data.frame"), row.names = c(NA,
-17L), .internal.selfref = <pointer: 0x00000000001f0788>)

Answer 1

library(dplyr)
df %>%
mutate(Date2 = as.numeric(strptime(df$Date, "%d-%m-%Y %H:%M"))) %>%
group_by(Spell) %>%
filter(Date2 >= (max(Date2) - 60*60*24)) %>%
select(-Date2)

Answer 2

Solution using only data.table :
# convert Date column to POSIXct
DT[,Date:=as.POSIXct(Date,format='%d-%m-%y %H:%M',tz='GMT')]
# filter the data.table
filteredDT <- DT[, .SD[as.numeric(difftime(max(Date),Date,units='hours')) <= 24], by = Spell]
> filteredDT
Spell Episode Date Temp
1: 1 3 2017-01-02 21:00:00 40
2: 1 2 2017-01-02 20:00:00 36
3: 2 3 2017-01-02 15:00:00 36
4: 2 2 2017-01-02 10:00:00 37
5: 3 1 2017-01-03 10:00:00 40
6: 4 3 2017-01-04 15:00:00 36
7: 5 7 2017-01-03 17:30:00 36

Answer 3

mydata$Date <- as.POSIXct(mydata$Date, format = '%d-%m-%y %H:%M', tz='GMT')
mydata <- mydata[with(mydata, order(Spell, -as.numeric(Date))),]
index <- with(mydata, tapply(Date, Spell, function(x){x >= max(x) - as.difftime(1, unit="days")}))
mydata[unlist(index),]
Spell Episode Date Temp
1: 1 3 2017-01-02 21:00:00 40
2: 1 2 2017-01-02 20:00:00 36
4: 2 3 2017-01-02 15:00:00 36
5: 2 2 2017-01-02 10:00:00 37
7: 3 1 2017-01-03 10:00:00 40
8: 4 3 2017-01-04 15:00:00 36
11: 5 7 2017-01-03 17:30:00 36

Answer 4

The solution below uses two functions from Hadley Wickham's lubridate() package. This package is very handy when dealing with dates and times so I wonder why it hasn't been used in any of the other answers.
Furthermore, data.table is used because the OP has provided sample data of data.table class.
library(data.table) # if not already loaded
# coerce Date to POSIXct
DT[, Date := lubridate::dmy_hm(Date)][
# for each, pick measurements within last 24 hours
, .SD[Date > max(Date) - lubridate::dhours(24L)], by = Spell][
# order, just for convenience
order(Spell, -Date)]
Spell Episode Date Temp
1: 1 3 2017-01-02 21:00:00 40
2: 1 2 2017-01-02 20:00:00 36
3: 2 3 2017-01-02 15:00:00 36
4: 2 2 2017-01-02 10:00:00 37
5: 3 1 2017-01-03 10:00:00 40
6: 4 3 2017-01-04 15:00:00 36
7: 5 7 2017-01-03 17:30:00 36
Please note that the expected result given by the OP shows an additional row (Spell 5, Episode 6) which is outside of the 24 hrs window.
Data
As provided by the OP
DT <- structure(list(Spell = c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 4L, 4L,
4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L), Episode = c(3L, 2L, 1L, 3L,
2L, 1L, 1L, 3L, 2L, 1L, 7L, 6L, 5L, 1L, 4L, 3L, 2L), Date = c("2-1-17 21:00",
"2-1-17 20:00", "1-1-17 10:00", "2-1-17 15:00", "2-1-17 10:00",
"1-1-17 8:00", "3-1-17 10:00", "4-1-17 15:00", "3-1-17 12:00",
"3-1-17 10:00", "3-1-17 17:30", "2-1-17 17:00", "2-1-17 16:00",
"1-1-17 9:00", "1-1-17 14:00", "1-1-17 13:00", "1-1-17 11:00"
), Temp = c(40L, 36L, 37L, 36L, 37L, 36L, 40L, 36L, 40L, 39L,
36L, 36L, 37L, 36L, 39L, 40L, 39L)), .Names = c("Spell", "Episode",
"Date", "Temp"), class = c("data.table", "data.frame"), row.names = c(NA, -17L))