Dates and times with lubridate

beginner

Published

May 17, 2024

Previous attendees have said…

4 previous attendees have left feedback
75% would recommend this session to a colleague
100% said that this session was pitched correctly

Three random comments from previous attendees

All the content was very relevant. Found the run through a bit quick but I think I picked up most of it. A useful summary of the lubridate functions, thank-you.
Nice introduction, examples and practice for using lubridate.
Useful intro to lubridate. Sorry forgot to say in the session but would be interested to learn how to calculate time between dates. Ie age or time passed.

Slides

Session content

Word of warning

dates and times are hard everywhere
R is no exception
this session is a beginner’s guide to lubridate
- not the only way of dealing with dates
- not always the best
- on balance the most consistent, and least quirky tools for dates

This session

beginner-friendly
focus on core parsing, get/set, and rounding functions
lots on dates, a bit of date-times, no times

Resources

library(lubridate)

R dates

days since 1970-01-01

as_date(0)

[1] “1970-01-01”

R dates

as_date(19860)

[1] “2024-05-17”

as_date(1:5)

[1] “1970-01-02” “1970-01-03” “1970-01-04” “1970-01-05” “1970-01-06”

class(as_date(0))

[1] “Date”

R date-times

seconds since 1970-01-01 00:00:00 UTC

as_datetime(0)

[1] “1970-01-01 UTC”

as_datetime(1715935369)

[1] “2024-05-17 08:42:49 UTC”

as_datetime(0:5)

[1] “1970-01-01 00:00:00 UTC” “1970-01-01 00:00:01 UTC” [3] “1970-01-01 00:00:02 UTC” “1970-01-01 00:00:03 UTC” [5] “1970-01-01 00:00:04 UTC” “1970-01-01 00:00:05 UTC”

class(as_datetime(0))

[1] “POSIXct” “POSIXt”

Famously…

as_datetime(2 ^ 31-1) # 32 bit signed int

[1] “2038-01-19 03:14:07 UTC”

Parsing dates is important

most functions that accept dates (like ggplot) will mis-behave if you feed them date-shaped-words
- e.g. alphabetically-ordered dates
we also want to be able to calculate with dates

Couple of fun intro functions

today()

[1] “2026-05-18”

date_decimal(2024.37534)

[1] “2024-05-17 08:59:11 UTC”

now()

[1] “2026-05-18 10:54:31 BST”

now("Japan")

[1] “2026-05-18 18:54:31 JST”

random_zone <- sample(OlsonNames(), 1)
cat(paste("The date-time in", random_zone, "is", now(sample(OlsonNames(), 1))))

The date-time in America/Argentina/Ushuaia is 2026-05-18 06:54:31.56886

Parsing

as_date() is fine assuming you have your date as a number of days
but usually, we’ll need to parse our dates

as_date(45429) # excel-format 1900 date

[1] “2094-05-19”

as_date(45429 - 25569) # dirty but effective

[1] “2024-05-17”

as_date(45429, origin = "1899-12-30") # better

[1] “2024-05-17”

Parsing

more often, we’ll be taking human-readable dates and parsing them
that’s a pain, because there are loads of inconsistent ways of representing dates
worse, lots of dates are ambiguous (5/6/24 and 6/5/24 might refer to the same day)

date_input <- c("17/5/24", "2024-05-17", "Friday 17th May 2024", "17*May*24", "5/17/2024" )

as_date(date_input) # as_date expects ISO-8601ish dates

[1] “2017-05-24” “2024-05-17” NA “2017-05-24” NA

# one correct, two silently incorrent, two NAs

parse_date_time

parse_date_time(date_input, orders = "ymd")

[1] “2017-05-24 UTC” “2024-05-17 UTC” NA “2017-05-24 UTC” [5] NA

parse_date_time(date_input, orders = c("dmy", "ymd", "dmy", "dmy", "mdy"))

[1] “2024-05-17 UTC” “2024-05-17 UTC” “2024-05-17 UTC” “2024-05-17 UTC” [5] “2024-05-17 UTC”

dmy and co

you can also use the orders (like dmy) as standalone parsing functions:

dmy(date_input[c(1,3,4)])

[1] “2024-05-17” “2024-05-17” “2024-05-17”

ymd_hms("2024-05/17 9-05-01")

[1] “2024-05-17 09:05:01 UTC”

So you can make dates/date-times. So what?

date(now())

[1] “2026-05-18”

year(today())

[1] 2026

leap_year(today())

[1] FALSE

quarter(today())

[1] 2

semester(today())

[1] 1

semester(today(), with_year = T)

[1] 2026.1

Months and weeks

month(today())

[1] 5

month(today(), label = T)

[1] May 12 Levels: Jan < Feb < Mar < Apr < May < Jun < Jul < Aug < Sep < … < Dec

week(today())

[1] 20

epiweek(today()) # special ways of counting weeks. See  https://en.wikipedia.org/wiki/ISO_week_date and https://www.cmmcp.org/mosquito-surveillance-data/pages/epi-week-calendars-2008-2024

[1] 20

Days

day(today())

[1] 18

wday(today())

[1] 2

qday(today())

[1] 48

Hour and minute

hour(now())

[1] 10

minute(now())

[1] 54

am(now())

[1] TRUE

dst(now())

[1] TRUE

Set

update(now(), hour = 11, minute = 0, second = 0) # nominal finish time today

[1] “2026-05-18 11:00:00 BST”

or, more generally:

test_date <- dmy("05/06/23")
day(test_date)

[1] 5

day(test_date) <- 11
test_date

[1] “2023-06-11”

Round

floor_date(today(), unit = "week")

[1] “2026-05-17”

round_date(today(), unit = "week")

[1] “2026-05-17”

ceiling_date(today(), unit = "month")

[1] “2026-06-01”

rollback(today()) # last day of previous month

[1] “2026-04-30”