Chapter 11 Dates and Times

R Programming for Data Science

11.1 Dates in R

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Dates are represented by the Date class and can be coerced from a character string using the as.Date() function. This is a common way to end up with a Date object in R.

## Coerce a 'Date' object from character
x <- as.Date("1970-01-01")   
x

## [1] "1970-01-01"

You can see the internal representation of a Date object by using the unclass() function.

unclass(x)

## [1] 0

unclass(as.Date("1970-01-02"))

## [1] 1

unclass(as.Date("1969-12-31"))

## [1] -1

unclass(as.Date("1945-10-10"))

## [1] -8849

Sys.Date()

## [1] "2022-11-12"

unclass(Sys.Date())

## [1] 19308

as.Date("2004-12-31") - as.Date("2003-12-31")

## Time difference of 366 days

as.Date("1900-12-31") - as.Date("1899-12-31")

## Time difference of 365 days

as.Date("2100-12-31") - as.Date("2099-12-31")

## Time difference of 365 days

11.2 Times in R

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Times are represented by the POSIXct or the POSIXlt class.

• POSIXct is just a very large integer under the hood.
  • It use a useful class when you want to store times in something like a data frame.
• POSIXlt is a list underneath and it stores a bunch of other useful information like the day of the week, day of the year, month, day of the month.
  • This is useful when you need that kind of information.

There are a number of generic functions that work on dates and times to help you extract pieces of dates and/or times.

• weekdays: give the day of the week
• months: give the month name
• quarters: give the quarter number (“Q1”, “Q2”, “Q3”, or “Q4”)

Times can be coerced from a character string using the as.POSIXlt or as.POSIXct function.

x <- Sys.time()
x

## [1] "2022-11-12 11:07:43 +08"

Website:

• Time zones in Asia

• Time zone abbreviation

knitr::kable(OlsonNames())

x <- Sys.time()
x

## [1] "2022-11-12 11:07:43 +08"

class(x)

## [1] "POSIXct" "POSIXt"

The POSIXlt object contains some useful metadata.

p <- as.POSIXlt(x)
names(unclass(p))

##  [1] "sec"    "min"    "hour"   "mday"   "mon"    "year"   "wday"   "yday"  
##  [9] "isdst"  "zone"   "gmtoff"

## day of the week
p$wday

## [1] 6

## day of the year
p$yday

## [1] 315

You can also use the POSIXct format.

# 1 minute past midnight in GMT of January 1, 1970
x1 <- as.POSIXct("1970-01-01 00:01:00", tz = "GMT")
x1

## [1] "1970-01-01 00:01:00 GMT"

unclass(x1)

## [1] 60
## attr(,"tzone")
## [1] "GMT"

# Philippine time zone is 8 hours ahead of GMT (Greenwich Mean Time) or UTC
x2 <- as.POSIXct("1970-01-01 08:00:00", tz = "Asia/Manila")
x2

## [1] "1970-01-01 08:00:00 PST"

unclass(x2)

## [1] 0
## attr(,"tzone")
## [1] "Asia/Manila"

p2 <- as.POSIXlt(x2)
p2$hour

## [1] 8

Finally, there is the strptime() function in case your dates are written in a different format. strptime() takes a character vector that has dates and times and converts them into to a POSIXlt object.

datestring <- c("January 10, 2012 10:40", 
                "December 9, 2011 9:10", 
                "October 10, 2022 9:30")
datestring

## [1] "January 10, 2012 10:40" "December 9, 2011 9:10"  "October 10, 2022 9:30"

z <- strptime(datestring, "%B %d, %Y %H:%M", tz = "Asia/Manila")
z

## [1] "2012-01-10 10:40:00 PST" "2011-12-09 09:10:00 PST"
## [3] "2022-10-10 09:30:00 PST"

• The weird-looking symbols that start with the % symbol are the formatting strings for dates and times.

• Check ?strptime for details. It’s probably not worth memorizing this stuff.

11.3 Operations on Dates and Times

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You can use mathematical operations on dates and times. Well, really just + and -.

You can do comparisons too (i.e. ==, <=)

x <- as.POSIXlt("2022-01-01")
y <- strptime("10 Oct 2022 09:30:00", "%d %b %Y %H:%M:%S")
y - x 

## Time difference of 282.3958 days

9/24 + 30/(24*60)

## [1] 0.3958333

he nice thing about the date/time classes is that they keep track of all the annoying things about dates and times, like leap years, leap seconds, daylight savings, and time zones.

Here’s an example where a leap year gets involved.

x <- as.Date("2012-03-01") 
y <- as.Date("2012-02-28") 
x-y

## Time difference of 2 days

## 2022 is not a leap year
as.Date("2022-12-31") - as.Date("2022-01-01")

## Time difference of 364 days

## 2020 is a leap year
as.Date("2020-12-31") - as.Date("2020-01-01")

## Time difference of 365 days

## 2100 is not a leap year
as.Date("2100-12-31") - as.Date("2100-01-01")

## Time difference of 364 days

## 1900 is not a leap year
as.Date("1900-12-31") - as.Date("1900-01-01")

## Time difference of 364 days

Here’s an example where two different time zones are in play (unless you live in GMT timezone, in which case they will be the same!).

## My local time zone
x <- as.POSIXct("2022-10-10 12:30:00")    
y <- as.POSIXct("2022-10-10 12:30:00", tz = "GMT")  #knowing the time difference, different time zones
y-x

## Time difference of 8 hours