I have a date that I convert to a numeric value and want to convert back to a date afterwards.
Converting date to numeric:
date1 = as.POSIXct('2017-12-30 15:00:00')
date1_num = as.numeric(date1)
# 1514646000
Reconverting numeric to date:
as.Date(date1_num, origin = '1/1/1970')
# "4146960-12-12"
What am I missing with the reconversion? I'd expect the last command to return my original date1.
As the numeric vector is created from an object with time component, reconversion can also be in the same way i.e. first to POSIXct and then wrap with as.Date
as.Date(as.POSIXct(date1_num, origin = '1970-01-01'))
#[1] "2017-12-30"
You could use anytime() and anydate() from the anytime package:
R> pt <- anytime("2017-12-30 15:00:00")
R> pt
[1] "2017-12-30 15:00:00 CST"
R>
R> anydate(pt)
[1] "2017-12-30"
R>
R> as.numeric(pt)
[1] 1514667600
R>
R> anydate(as.numeric(pt))
[1] "2017-12-30"
R>
POSIXct counts the number of seconds since the Unix Epoch, while Date counts the number of days. So you can recover the date by dividing by (60*60*24) (let's ignore leap seconds), or convert back to POSIXct instead.
as.Date(as.numeric(date1)/(60*60*24), origin="1970-01-01")
[1] "2017-12-30"
as.POSIXct(as.numeric(date1),origin="1970-01-01")
[1] "2017-12-30 15:00:00 GMT"
Using lubridate :
lubridate::as_datetime(1514646000)
[1] "2017-12-30 15:00:00 UTC"
Related
I have these numbers:
-44384.520833333299 (to datetime). It should be 07/07/2021 12:30:00
-44384 (to date). It should be 07/07/2021
How can I convert these numbers and a list of them in R?
openxlsx::convertToDateTime(44384.520833333299)
# [1] "2021-07-07 12:30:00 CEST"
openxlsx::convertToDate(44384)
# [1] "2021-07-07"
Another possibility, using lubridate:
library(lubridate)
# The first argument must be in seconds
as_datetime(3600*24*44384.520833333299, origin="1899-12-30")
#> [1] "2021-07-07 12:29:59 UTC"
as_date(44384, origin="1899-12-30")
#> [1] "2021-07-07"
While converting a dataframe to xts I realized that there is something wrong with the formatter. Here's an example dataframe:
effective_date price
"1990-01-01" "100"
"1990-01-02 00:05:00" "200"
This is example output from a package that I use.
Converting this to xts is straight-forward
xts(df["price"], order_by=as.POSIXct(df["effective_date"], format="%Y-%m-%d %H:%M:%S")
However this errors out, saying NAs can't be in row names, and the result is:
<NA> 100
1990-01-02 00:05:00 200
Obviously xts can't figure out what to do with the weird date there (midnight) and it won't coerce it.
If I add tz="UTC" to as.POSIXct it doesn't work. Additionally, as.POSIXlt doesnt change anything here either.
What can I do to coerce that midnight date to the correct format?
Two issues:
1) You cannot parse a date alone as POSIXct with a given format:
R> as.POSIXct(c("2017-01-02", "2017-01-03 04:05:06"), format="%Y-%m-%d %H:%M:%S")
[1] NA "2017-01-03 04:05:06 CST"
R>
2) You can however use the anytime() function to do it:
R> anytime::anytime(c("2017-01-02", "2017-01-03 04:05:06"))
[1] "2017-01-02 00:00:00 CST" "2017-01-03 04:05:06 CST"
R>
Once you have a POSIXct, forming the xts is easy.
Also note that you have typos: you need a comma before the column indicator: df[, "price"].
Edit: Getting a little tired of #42's comment about Gabor's (fine) solution "dominating" this one, so here's minimal benchmark:
R> library(microbenchmark)
R> v <- c("2017-01-02", "2017-01-03 04:05:06")
R> library(anytime)
R> print(microbenchmark(anytime(v), do.call("c", lapply(v, as.POSIXct))), digits=3)
Unit: microseconds
expr min lq mean median uq max neval cld
anytime(v) 33.6 36.8 42.1 45.6 46.6 80.7 100 a
do.call("c", lapply(v, as.POSIXct)) 571.5 579.1 586.4 586.8 589.5 695.7 100 b
R>
so in short "not really". It is using only R Base, which is a plus, put it is a) harder read and understand, b) more limited as it deals with exactly one format (in ISO style) and c) it is about thirteen times slower.
1) To get the "POSIXct" datetime vector try converting each datetime to "POSIXct" separately and then concatenate them together:
do.call("c", lapply(df$effective_date, as.POSIXct))
2) Another base solution that is even shorter and is also substantially faster is the following which relies on the fact that as.POSIXct will ignore junk at the end.
as.POSIXct(paste(df$effective, "00:00:00"))
Most of lubridate's parsing functions have a truncated parameter that takes a number indicating the number of elements that can be missing from the end. Missing elements will be replaced by zero.
Example with the data at hand:
lubridate::ymd_hms(c("2017-01-02", "2017-01-03 04:05:06"), truncated = 3)
## [1] "2017-01-02 00:00:00 UTC" "2017-01-03 04:05:06 UTC"
Assuming you want the timestamps, preprocess with something like:
temp <- c("1990-01-01", "1990-01-02 00:05:00")
# match a date string at the end of string (indicated by $). Replace
# with the full string (indicated by \\1 and 00:00:00
temp2 <- gsub("(\\d{4}\\-\\d{2}\\-\\d{2}$)", "\\1 00:00:00", temp)
# [1] "1990-01-01 00:00:00" "1990-01-02 00:05:00"
lets say we have this date "2014-05-11 14:45:00 UTC". I would like to get the exact POSIXct object for 1 year before so "2013-05-11 14:45:00 UTC".
My first thought is to create a whole new POSIXct object by subtracting one from the year bit and pasting it together with the remainder of the string and then creating a new POSIXct object with that string like so:
time <- as.POSIXct("2014-05-11 14:45:00 UTC",tz="UTC",origin="1970-01-01")
newTime <- as.POSIXct(paste(as.character(as.numeric(substr(time,1,4)) - 1),substr(time,5,19),sep=""),tz="UTC",origin="1970-01-01")
this works fine (except in case of leap years!) but the thing is I need to do this in a large data.table for each row and preferably put the results right back in data.table.
Is there any other way of subtracting a year off an object like this?
Some extra I need to apply this to a data.table like this one:
Time
1: 1349206200
2: 1349207100
3: 1349208000
4: 1349208900
5: 1349209800
6: 1349210700
7: 1349211600
8: 1349212500
9: 1349213400
10: 1349214300
11: 1349215200
but this happens when I do:
SOdata[,Time:=as.numeric(as.POSIXct(paste(as.character(as.numeric(substr(Time,1,4)) - 1),substr(Time,5,19),sep=""),tz="UTC",origin="1970-01-01"))]
Error in as.POSIXlt.character(x, tz, ...) :
character string is not in a standard unambiguous format
I am guessing I need to use something like lapply, but I always mess up syntax when using that function. So does anyone know how?
lubridate is your friend.
library(lubridate)
time <- as.POSIXct("2014-05-11 14:45:00 UTC",tz="UTC",origin="1970-01-01")
time-dyears(1)
#[1] "2013-05-11 14:45:00 UTC"
time+dyears(1)
#[1] "2015-05-11 14:45:00 UTC"
For leap years
> x <- as.POSIXct(c("2012-02-28", "2012-02-29"), tz="UTC",origin="1970-01-01")
> x - dyears(1)
[1] "2011-02-28 UTC" "2011-03-01 UTC"
I haven't tested the other answers, but the following should work as required regardless of leap years:
time <- as.POSIXct("2014-05-11 14:45:00 UTC",tz="UTC",origin="1970-01-01")
time <- as.POSIXlt(time)
time$year <- time$year - 1
time <- as.POSIXct(time)
#[1] "2013-05-11 14:45:00 UTC"
With Gabor's leap year example:
time <- as.POSIXct("2012-02-29 14:45:00 UTC",tz="UTC",origin="1970-01-01")
time <- as.POSIXlt(time)
time$year <- time$year - 1
time <- as.POSIXct(time)
#[1] "2011-03-01 14:45:00 UTC"
seq in base can be used:
LastYr <- function(x) seq(x, length = 2, by = "-1 year")[2]
toPOSIXct <- function(x) as.POSIXct(x, origin = "1970-01-01")
# example 1
LastYr(as.POSIXct("2012-02-28"))
## [1] "2011-02-28 EST"
# example 2 - leap year
LastYr(as.POSIXct("2012-02-29"))
## [1] "2011-03-01 EST"
# example 3 - vector case
x <- as.POSIXct(c("2012-02-28", "2012-02-29")) # test data
toPOSIXct(sapply(x, LastYr))
## [1] "2011-02-28 EST" "2011-03-01 EST"
# example 4 - data.table shown in question
DT[, Time := sapply(toPOSIXct(Time), LastYr)]
Revised simplified using functions LastYr and toPOSIXct.
or you can try, in base R :
> time + as.difftime(52*7+1,units="days")
[1] "2015-05-11 14:45:00 UTC"
> time - as.difftime(52*7+1,units="days")
[1] "2013-05-11 14:45:00 UTC"
of course, it would be easier if units could be years...
Why does the Date below change to "2014-07-07" when converted to POSIXct?
Sys.setenv(TZ='America/Sao_Paulo')
d <- as.Date("2014-07-08", format="%Y-%m-%d")
d
[1] "2014-07-08"
as.POSIXct(d)
[1] "2014-07-07 21:00:00 BRT"
Because as.POSIXct.Date doesn't look for a timezone (and won't pass it to .POSIXct if you specify it in ...) and Date objects are "UTC", so your POSIXct is offset from the UTC of the Date object.
It would be better to call as.POSIXct on the character string directly, if you can:
> as.POSIXct("2014-07-08", format="%Y-%m-%d")
[1] "2014-07-08 BRT"
I'm probably doing something stupid and not seeing it, but:
> strptime("201101","%Y%m")
[1] NA
From help strptime:
%Y Year with century
%m Month as decimal number (01–12)
Just paste a day field (say, "01") that you ignore:
R> shortdate <- "201101"
R> as.Date(paste(shortdate, "01", sep=""), "%Y%m%d")
[1] "2011-01-01"
R>
I prefer as.Date() for dates and strptime() for POSIXct objects, i.e. dates and times.
You can then convert the parsed Date object into a POSIXlt object to retrieve year and month:
R> mydt <- as.Date(paste(shortdate, "01", sep=""), "%Y%m%d")
R> myp <- as.POSIXlt(mydt)
R> c(myp$year, myp$mon)
[1] 111 0
R>
This is standard POSIX behaviour with years as "year - 1900" and months as zero-indexed.
Edit seven years later: For completeness, and as someone just upvoted this, the functions in my anytime package can help:
R> anytime::anydate("201101") ## returns a Date
[1] "2011-01-01"
R> anytime::anytime("201101") ## returns a Datetime
[1] "2011-01-01 CST"
R>
The use a different parser (from Boost Date_time which is more generous and imputes the missing day (or day/hour/minute/second in the second case).