In my data I have a column of temperature measurements together with a column showing the time passed until the temp was measured by the data logger. The dataframe contains 500000+ observations.
eggtemp <- read.csv("temp_time.csv", header=FALSE)
colnames(eggtemp) <- c("time passed", "temp")
time passed temp
1 0.00043823 16.876
2 0.00087645 17.903
3 0.00131470 18.923
4 0.00175290 19.933
The data logger started recording at 7/30/2014, 13:05:00.
Is there a way to make a new column in the data set, based on the start recording time, showing the exact time at which the measurements were taken? Like this one (I typed the rough time in by hand for the first 4 rows):
time passed temp time
1 0.00043823 16.876 13:05:00:00
2 0.00087645 17.903 13:05:00:04
3 0.00131470 18.923 13:05:00:09
4 0.00175290 19.933 13:05:00:13
Can someone tell me if there is a function that takes the starting time and adds the "time passed" values, to get the exact time (and date) of every observation? I just can't figure it out..
Thanks!
You don't mention the unit of eggtemp[,'time passed'], but I'm guessing hours from your typed in values. I use the lubridate package, it makes these calculations easy. Although it's definitely possible with base R.
start <- mdy_hms("7/30/2014 13:05:00")
time_passed <- c(0.00043823, 0.00087645, 0.00131470, 0.00175290)
time_passed <- dhours(time_passed)
time <- start + time_passed
Make sure to set the tz argument to mdy_hms if you're concerned about getting it into a correct local time.