datecountbetween {clock}  R Documentation 
This is a Date method for the date_count_between()
generic.
date_count_between()
counts the number of precision
units between
start
and end
(i.e., the number of years or months). This count
corresponds to the whole number of units, and will never return a
fractional value.
This is suitable for, say, computing the whole number of years or months between two dates, accounting for the day of the month.
Calendrical based counting:
These precisions convert to a yearmonthday calendar and count while in that type.
"year"
"quarter"
"month"
Time point based counting:
These precisions convert to a time point and count while in that type.
"week"
"day"
For dates, whether a calendar or time point is used is not all that important, but is is fairly important for datetimes.
## S3 method for class 'Date'
date_count_between(start, end, precision, ..., n = 1L)
start, end 
A pair of date vectors. These will be recycled to their common size. 
precision 
One of:

... 
These dots are for future extensions and must be empty. 
n 
A single positive integer specifying a multiple of 
"quarter"
is equivalent to "month"
precision with n
set to n * 3L
.
An integer representing the number of precision
units between
start
and end
.
The computed count has the property that if start <= end
, then
start + <count> <= end
. Similarly, if start >= end
, then
start + <count> >= end
. In other words, the comparison direction between
start
and end
will never change after adding the count to start
. This
makes this function useful for repeated count computations at
increasingly fine precisions.
start < date_parse("20000505")
end < date_parse(c("20200504", "20200506"))
# Age in years
date_count_between(start, end, "year")
# Number of "whole" months between these dates. i.e.
# `20000505 > 20200405` is 239 months
# `20000505 > 20200505` is 240 months
# Since 20200504 occurs before the 5th of that month,
# it gets a count of 239
date_count_between(start, end, "month")
# Number of "whole" quarters between (same as `"month"` with `n * 3`)
date_count_between(start, end, "quarter")
date_count_between(start, end, "month", n = 3)
# Number of days between
date_count_between(start, end, "day")
# Number of full 3 day periods between these two dates
date_count_between(start, end, "day", n = 3)
# Essentially the truncated value of this
date_count_between(start, end, "day") / 3
# 
# Breakdown into full years, months, and days between
x < start
years < date_count_between(x, end, "year")
x < add_years(x, years)
months < date_count_between(x, end, "month")
x < add_months(x, months)
days < date_count_between(x, end, "day")
x < add_days(x, days)
data.frame(
start = start,
end = end,
years = years,
months = months,
days = days
)
# Note that when breaking down a date like that, you may need to
# set `invalid` during intermediate calculations
start < date_build(2019, c(3, 3, 4), c(30, 31, 1))
end < date_build(2019, 5, 05)
# These are 1 month apart (plus a few days)
months < date_count_between(start, end, "month")
# But adding that 1 month to `start` results in an invalid date
try(add_months(start, months))
# You can choose various ways to resolve this
start_previous < add_months(start, months, invalid = "previous")
start_next < add_months(start, months, invalid = "next")
days_previous < date_count_between(start_previous, end, "day")
days_next < date_count_between(start_next, end, "day")
# Resulting in slightly different day values.
# No result is "perfect". Choosing "previous" or "next" both result
# in multiple `start` dates having the same month/day breakdown values.
data.frame(
start = start,
end = end,
months = months,
days_previous = days_previous,
days_next = days_next
)