How to convert a column of UTC timestamps into several different timezones? - r

Question

I have a dataset with dates stored in the DB as UTC, however, the timezone is actually different.
mydat <- data.frame(
time_stamp=c("2022-08-01 05:00:00 UTC","2022-08-01 17:00:00 UTC","2022-08-02 22:30:00 UTC","2022-08-04 05:00:00 UTC","2022-08-05 02:00:00 UTC"),
timezone=c("America/Chicago","America/New_York","America/Los_Angeles","America/Denver","America/New_York")
)
I want to apply the timezone to the UTC saved timestamps, over the entire column.
I looked into the with_tz function in the lubridate package, but I don't see how to reference the "timezone" column, rather than hardcoding in a value.
Such as if I try
with_tz(mydat$time_stamp, tzone = mydat$timezone)
I get the following error
Error in as.POSIXlt.POSIXct(x, tz) : invalid 'tz' value`
However, if I try
mydat$time_stamp2 <- with_tz(mydat$time_stamp,"America/New_York")
that will render a new column without issue. How can I do this just referencing column values?

Answer 1

Welcome to StackOverflow. This is nice, common, and tricky problem! The following should do what you ask for:
Code
mydat <- data.frame(time_stamp=c("2022-08-01 05:00:00 UTC",
"2022-08-01 17:00:00 UTC",
"2022-08-02 22:30:00 UTC",
"2022-08-04 05:00:00 UTC",
"2022-08-05 02:00:00 UTC"),
timezone=c("America/Chicago", "America/New_York",
"America/Los_Angeles", "America/Denver",
"America/New_York"))
mydat$utc <- anytime::utctime(mydat$time_stamp, tz="UTC")
mydat$format <- ""
for (i in seq_len(nrow(mydat)))
mydat[i, "format"] <- strftime(mydat[i,"utc"],
"%Y-%m-%d %H:%M:%S",
tz=mydat[i,"timezone"])
Output
> mydat
time_stamp timezone utc format
1 2022-08-01 05:00:00 UTC America/Chicago 2022-08-01 05:00:00 2022-08-01 00:00:00
2 2022-08-01 17:00:00 UTC America/New_York 2022-08-01 17:00:00 2022-08-01 13:00:00
3 2022-08-02 22:30:00 UTC America/Los_Angeles 2022-08-02 22:30:00 2022-08-02 15:30:00
4 2022-08-04 05:00:00 UTC America/Denver 2022-08-04 05:00:00 2022-08-03 23:00:00
5 2022-08-05 02:00:00 UTC America/New_York 2022-08-05 02:00:00 2022-08-04 22:00:00
>
Comment
We first parse your data as UTC, I once wrote a helper function for that in my anytime package (there are alternatives but this is how I do it...). We then need to format from the given (numeric !!) UTC representation to the give timezone. We need a loop for this as the tz argument to strftime() is not vectorized.

Answer 2

Dirk gave a great answer that uses (mostly) base R tooling, if that is a requirement of yours. I wanted to also add an answer that uses the clock package that I developed because it doesn't require working rowwise over your data frame. clock has a function called sys_time_info() that retrieves low level information about a UTC time point in a specific time zone. It is one of the few functions where it makes sense to have a vectorized zone argument (which you need here) and returns an offset from UTC that will be useful here for converting to a "local" time.
As others have mentioned, you won't be able to construct a date-time vector that stores multiple time zones in it, but if you just need to see what the local time would have been in those zones, this can still be useful.
library(clock)
mydat <- data.frame(
time_stamp=c("2022-08-01 05:00:00 UTC","2022-08-01 17:00:00 UTC","2022-08-02 22:30:00 UTC","2022-08-04 05:00:00 UTC","2022-08-05 02:00:00 UTC"),
timezone=c("America/Chicago","America/New_York","America/Los_Angeles","America/Denver","America/New_York")
)
# Parse into a "sys-time" type, which can be thought of as a UTC time point
mydat$time_stamp <- sys_time_parse(mydat$time_stamp, format = "%Y-%m-%d %H:%M:%S")
mydat
#> time_stamp timezone
#> 1 2022-08-01T05:00:00 America/Chicago
#> 2 2022-08-01T17:00:00 America/New_York
#> 3 2022-08-02T22:30:00 America/Los_Angeles
#> 4 2022-08-04T05:00:00 America/Denver
#> 5 2022-08-05T02:00:00 America/New_York
# "Low level" information about DST, the time zone abbreviation,
# and offset from UTC in that zone. This is one of the few functions where
# it makes sense to have a vectorized `zone` argument.
info <- sys_time_info(mydat$time_stamp, mydat$timezone)
info
#> begin end offset dst abbreviation
#> 1 2022-03-13T08:00:00 2022-11-06T07:00:00 -18000 TRUE CDT
#> 2 2022-03-13T07:00:00 2022-11-06T06:00:00 -14400 TRUE EDT
#> 3 2022-03-13T10:00:00 2022-11-06T09:00:00 -25200 TRUE PDT
#> 4 2022-03-13T09:00:00 2022-11-06T08:00:00 -21600 TRUE MDT
#> 5 2022-03-13T07:00:00 2022-11-06T06:00:00 -14400 TRUE EDT
# Add the offset to the sys-time and then convert to a character column
# (these times don't really represent sys-time anymore since they are now localized)
mydat$localized <- as.character(mydat$time_stamp + info$offset)
mydat
#> time_stamp timezone localized
#> 1 2022-08-01T05:00:00 America/Chicago 2022-08-01T00:00:00
#> 2 2022-08-01T17:00:00 America/New_York 2022-08-01T13:00:00
#> 3 2022-08-02T22:30:00 America/Los_Angeles 2022-08-02T15:30:00
#> 4 2022-08-04T05:00:00 America/Denver 2022-08-03T23:00:00
#> 5 2022-08-05T02:00:00 America/New_York 2022-08-04T22:00:00