I have some numbers that represent dates in milliseconds since epoch, 00:00:00 Coordinated Universal Time (UTC), Thursday, 1 January 1970
1365368400000,
1365973200000,
1366578000000
I'm converting them to date format:
as.Date(as.POSIXct(my_dates/1000, origin="1970-01-01", tz="GMT"))
answer:
[1] "2013-04-07" "2013-04-14" "2013-04-21"
How to convert these strings back to milliseconds since epoch?
Here are your javascript dates
x <- c(1365368400000, 1365973200000, 1366578000000)
You can convert them to R dates more easily by dividing by the number of milliseconds in one day.
y <- as.Date(x / 86400000, origin = "1970-01-01")
To convert back, just convert to numeric and multiply by this number.
z <- as.numeric(y) * 86400000
Finally, check that the answer is what you started with.
stopifnot(identical(x, z))
As per the comment, you may sometimes get numerical rounding errors leading to x and z not being identical. For numerical comparisons like this, use:
library(testthat)
expect_equal(x, z)
I will provide a simple framework to handle various kinds of dates encoding and how to go back an forth. Using the R package ‘lubridate’ this is made very easy using the period and interval classes.
When dealing with days, it can be easy as one can use the as.numeric(Date) to get the number of dates since the epoch. To get any unit of time smaller than a day one can convert using the various factors (24 for hours, 24 * 60 for minutes, etc.) However, for months, the math can get a bit more tricky and thus I prefer in many instances to use this method.
library(lubridate)
as.period(interval(start = epoch, end = Date), unit = 'month')#month
This can be used for year, month, day, hour, minute, and smaller units through apply the factors.
Going the other way such as being given months since epoch:
library(lubridate)
epoch %m+% as.period(Date, unit = 'months')
I presented this approach with months as it might be the more complicated one. An advantage to using period and intervals is that it can be adjusted to any epoch and unit very easily.
Related
I have some timedelta strings which were exported from Python. I'm trying to import them for use in R, but I'm getting some weird results.
When the timedeltas are small, I get results that are off by 2 days, e.g.:
> as.difftime('26 days 04:53:36.000000000',format='%d days %H:%M:%S.000000000')
Time difference of 24.20389 days
When they are larger, it doesn't work at all:
> as.difftime('36 days 04:53:36.000000000',format='%d days %H:%M:%S.000000000')
Time difference of NA secs
I also read into 'R' some time delta objects I had processed with 'Python' and had a similar issue with the 26 days 04:53:36.000000000 format. As Gregor said, %d in strptime is the day of the month as a zero padded decimal number so won't work with numbers >31 and there doesn't seem to be an option for cumulative days (probably because strptime is for date time objects and not time delta objects).
My solution was to convert the objects to strings and extract the numerical data as Gregor suggested and I did this using the gsub function.
# convert to strings
data$tdelta <- as.character(data$tdelta)
# extract numerical data
days <- as.numeric(gsub('^.*([0-9]+) days.*$','\\1',data$tdelta))
hours <- as.numeric(gsub('^.*ys ([0-9]+):.*$','\\1',data$tdelta))
minutes <- as.numeric(gsub('^.*:([0-9]+):.*$','\\1',data$tdelta))
seconds <- as.numeric(gsub('^.*:([0-9]+)..*$','\\1',data$tdelta))
# add up numerical components to whatever units you want
time_diff_seconds <- seconds + minutes*60 + hours*60*60 + days*24*60*60
# add column to data frame
data$tdelta <- time_diff_seconds
That should allow you to do computations with the time differences. Hope that helps.
Lots of people ask how to strip the time and keep the date, but what about the other way around? Given:
myDateTime <- "11/02/2014 14:22:45"
I would like to see:
myTime
[1] "14:22:45"
Time zone not necessary.
I've already tried (from other answers)
as.POSIXct(substr(myDateTime, 12,19),format="%H:%M:%S")
[1] "2013-04-13 14:22:45 NZST"
The purpose is to analyse events recorded over several days by time of day only.
Thanks
Edit:
It turns out there's no pure "time" object, so every time must also have a date.
In the end I used
as.POSIXct(as.numeric(as.POSIXct(myDateTime)) %% 86400, origin = "2000-01-01")
rather than the character solution, because I need to do arithmetic on the results. This solution is similar to my original one, except that the date can be controlled consistently - "2000-01-01" in this case, whereas my attempt just used the current date at runtime.
I think you're looking for the format function.
(x <- strptime(myDateTime, format="%d/%m/%Y %H:%M:%S"))
#[1] "2014-02-11 14:22:45"
format(x, "%H:%M:%S")
#[1] "14:22:45"
That's character, not "time", but would work with something like aggregate if that's what you mean by "analyse events recorded over several days by time of day only."
If the time within a GMT day is useful for your problem, you can get this with %%, the remainder operator, taking the remainder modulo 86400 (the number of seconds in a day).
stamps <- c("2013-04-12 19:00:00", "2010-04-01 19:00:01", "2018-06-18 19:00:02")
as.numeric(as.POSIXct(stamps)) %% 86400
## [1] 0 1 2
I want to create a single column with a sequence of date/time increasing every hour for one year or one month (for example). I was using a code like this to generate this sequence:
start.date<-"2012-01-15"
start.time<-"00:00:00"
interval<-60 # 60 minutes
increment.mins<-interval*60
x<-paste(start.date,start.time)
for(i in 1:365){
print(strptime(x, "%Y-%m-%d %H:%M:%S")+i*increment.mins)
}
However, I am not sure how to specify the range of the sequence of dates and hours. Also, I have been having problems dealing with the first hour "00:00:00"? Not sure what is the best way to specify the length of the date/time sequence for a month, year, etc? Any suggestion will be appreciated.
I would strongly recommend you to use the POSIXct datatype. This way you can use seq without any problems and use those data however you want.
start <- as.POSIXct("2012-01-15")
interval <- 60
end <- start + as.difftime(1, units="days")
seq(from=start, by=interval*60, to=end)
Now you can do whatever you want with your vector of timestamps.
Try this. mondate is very clever about advancing by a month. For example, it will advance the last day of Jan to last day of Feb whereas other date/time classes tend to overshoot into Mar. chron does not use time zones so you can't get the time zone bugs that code as you can using POSIXct. Here x is from the question.
library(chron)
library(mondate)
start.time.num <- as.numeric(as.chron(x))
# +1 means one month. Use +12 if you want one year.
end.time.num <- as.numeric(as.chron(paste(mondate(x)+1, start.time)))
# 1/24 means one hour. Change as needed.
hours <- as.chron(seq(start.time.num, end.time.num, 1/24))
How can I accurately convert the products (units is in days) of the difftime below to years, months and days?
difftime(Sys.time(),"1931-04-10")
difftime(Sys.time(),"2012-04-10")
This does years and days but how could I include months?
yd.conv<-function(days, print=TRUE){
x<-days*0.00273790700698851
x2<-floor(x)
x3<-x-x2
x4<-floor(x3*365.25)
if (print) cat(x2,"years &",x4,"days\n")
invisible(c(x2, x4))
}
yd.conv(difftime(Sys.time(),"1931-04-10"))
yd.conv(difftime(Sys.time(),"2012-04-10"))
I'm not sure how to even define months either. Would 4 weeks be considered a month or the passing of the same month day. So for the later definition of a month if the initial date was 2012-01-10 and the current 2012-05-31 then we'd have 0 years, 5 months and 21 days. This works well but what if the original date was on the 31st of the month and the end date was on feb 28 would this be considered a month?
As I wrote this question the question itself evolved so I'd better clarify:
What would be the best (most logical approach) to defining months and then how to find diff time in years, months and days?
If you're doing something like
difftime(Sys.time(), someDate)
It comes as implied that you must know what someDate is. In that case, you can convert this to a POSIXct class object that gives you the ability to extract temporal information directly (package chron offers more methods, too). For instance
as.POSIXct(c(difftime(Sys.time(), someDate, units = "sec")), origin = someDate)
This will return your desired date object. If you have a timezone tz to feed into difftime, you can also pass that directly to the tz parameter in as.POSIXct.
Now that you have your date object, you can run things like months(.) and if you have chron you can do years(.) and days(.) (returns ordered factor).
From here, you could do more simple math on the difference of years, months, and days separately (converting to appropriate numeric representations). Of course, convert someDate to POSIXct will be required.
EDIT: On second thought, months(.) returns a character representation of the month, so that may not be efficient. At least, it'll require a little processing (not too difficult) to give a numeric representation.
R has not implemented these features out of ignorance. difftime objects are transitive. A 700 day difference on any arbitrary start-date can yield a differing number of years depending on whether there was a leap year or not. Similarly for months, they take between 28-31 days.
For research purposes, we use these units a lot (months and years) and pragmatically, we define a year as 365.25 days and a month as 365.25/12 = 30.4375 days.
To do arithmetic on a given difftime, you must convert this value to numeric using as.numeric(difftime.obj) which is, in default, days so R stops spouting off the units.
You can not simply convert a difftime to month, since the definition of months depends on the absolute time at which the difftime has started.
You'll need to know the start date or the end date to accurately tell the number of months.
You could then, e.g., calculate the number of months in the first year of your timespan, the number of month in the last your of the timespan, and add the number of years between times 12.
Hmm. I think the most sensible would be to look at the various units themselves. So compare the day of the month first, then compare the month of the year, then compare the year. At each point, you can introduce a carry to avoid negative values.
In other words, don't work with the product of difftime, but recode your own difftime.
The diff command returns the differences between dates in a vector of dates in the R date format. I'd like to control the units that are returned, but it seems like they are automatically determined, with no way to control it w/ an argument. Here's an example:
> t = Sys.time()
> diff(c(t, t + 1))
Time difference of 1 secs
And yet:
> diff(c(t, t+10000))
Time difference of 1.157407 days
The "time delta" object has a units attribute, but it seems silly to write a bunch of conditionals to coerce everything into days, seconds etc.
I'm not sure what you mean by "a bunch of conditionals," just change the units manually.
> t = Sys.time()
> a <- diff(c(t,t+1))
> b <- diff(c(t, t+10000))
> units(a) <- "mins"
> units(b) <- "mins"
> a
Time difference of 0.01666667 mins
> b
Time difference of 166.6667 mins
See ?difftime. If you only need to use diff to get the difference between two times (rather than a longer vector), then, as Dirk suggests, use the difftime function with the units parameter.
A POSIXct type (which you created by calling Sys.time()) always use fractional seconds since the epoch.
The difftime() functions merely formats this differently for your reading pleasure. If you actually specify the format, you get what you specified:
R> difftime(t+ 10000,t,unit="secs")
Time difference of 10000 secs
R> difftime(t+ 10000,t,unit="days")
Time difference of 0.115741 days
R>
I think you need difftime in which you can specify the desired units. See:
> difftime(Sys.time(), Sys.time()+10000)
Time difference of -2.777778 hours
> difftime(Sys.time(), Sys.time()+10000, units="secs")
Time difference of -10000 secs
Not sure how precise you care to be, but you can get very specific about date-times with the lubridate package. A wonky thing about time units is that their length depends on when they occur because of leap seconds, leap days, and other conventions.
After you load lubridate, subtracting date times automatically creates a time interval object.
library(lubridate)
int <- Sys.time() - (Sys.time() + 10000)
You can then change it to a duration, which measures the exact length of time. Durations display in seconds because seconds are the only unit that has a consistent length. If you want your answer in a specific unit, just divide by a duration object that has the length of one of those units.
as.duration(int)
int / dseconds(1)
int / ddays(1)
int / dminutes(5) #to use "5 minutes" as a unit
Or you could just change the int to a period. Unlike durations, periods don't have an exact and consistent length. But they faithfully map clock times. You can do math by adding and subtracting both periods and durations to date-times.
as.period(int)
Sys.time() + dseconds(5) + dhours(2) - ddays(1)
Sys.time() + hours(2) + months(5) - weeks(1) #these are periods
If yon need to use the diff() function (e.g. as I do in within a ddply function), you can also turn the input data into numeric format to always receive differences in seconds like this:
> t = Sys.time()
> diff(as.numeric(c(t, t+1)))
[1] 1
> diff(as.numeric(c(t, t+10000)))
[1] 10000
From that point on you can use the diff seconds to calculate differences in other units.