The goal of grates is to make it easy to group dates across a range of different time intervals. It defines a collection of classes and associated methods that, together, formalise the concept of grouped dates and are intuitive to use. To assist in formatting plots of grates objects we also provides x-axis scales that can be used in conjunction with ggplot2 output. Currently implemented classes are:
grates_year; and
The underlying implementation for these objects build upon ideas of Davis Vaughan and the unreleased datea package as well as Zhian Kamvar and the aweek package.
Note that for brevity in the rest of the vignette, we will drop the grates_
prefix when discussing the underlying class.
yearweek objects are stored as the number of weeks (starting at 0L) from
the date of the firstday
nearest the Unix Epoch (1970-01-01). Put more simply,
the number of seven day periods from:
firstday
equal to 1 (Monday)firstday
equal to 2 (Tuesday)firstday
equal to 3 (Wednesday)firstday
equal to 4 (Thursday)firstday
equal to 5 (Friday)firstday
equal to 6 (Saturday)firstday
equal to 7 (Sunday)They can be constructed directly from integers via the new_yearweek()
function
but it is generally easier to use the either the as_yearweek()
coercion
function or the yearweek()
constructor. as_yearweek()
takes two arguments; x
, the vector (normally a Date or POSIXt) you wish to group,
and firstday
, the day of the week you wish your weeks to start on. yearweek()
takes three arguments; year
and week
integer vectors and, again, a
firstday
value.
The epiweek class is similar to the yearweek class but, by definition, will
always begin on a Sunday. They are stored as the integer number of weeks (again
starting at 0L) since 1970-01-04 so internally are akin to
grates_yearweek_sunday
objects but with the benefit of slightly more
efficient implementations for many of the associated methods.
Likewise, the isoweek class is similar to epiweek class but uses the ISO 8601 definition of a week that will always start on a Monday. Internally they are stored as the integer number of weeks since 1969-12-29.
library(grates)
# Choose some consecutive dates that begin on a Friday
first <- as.Date("2021-01-01")
weekdays(first)
#> [1] "Friday"
dates <- first + 0:9
# Below we use a Friday-week grouping
weeks <- as_yearweek(dates, firstday = 5L)
(dat <- data.frame(dates, weeks))
#> dates weeks
#> 1 2021-01-01 2021-W01
#> 2 2021-01-02 2021-W01
#> 3 2021-01-03 2021-W01
#> 4 2021-01-04 2021-W01
#> 5 2021-01-05 2021-W01
#> 6 2021-01-06 2021-W01
#> 7 2021-01-07 2021-W01
#> 8 2021-01-08 2021-W02
#> 9 2021-01-09 2021-W02
#> 10 2021-01-10 2021-W02
# we can also use the constructor function if we already have weeks and years
yearweek(year = c(2020L, 2021L), week = c(1L, 10L), firstday = 5L)
#> <grates_yearweek_friday[2]>
#> [1] "2020-W01" "2021-W10"
# epiweeks always start on a Sunday
(epiwk <- as_epiweek(Sys.Date()))
#> <grates_epiweek[1]>
#> [1] "2024-W35"
weekdays(as.Date(epiwk))
#> [1] "Sunday"
# isoweeks always start on a Sunday
(isowk <- as_isoweek(Sys.Date()))
#> <grates_isoweek[1]>
#> [1] "2024-W35"
weekdays(as.Date(isowk))
#> [1] "Monday"
By default plots (using ggplot2) will centre yearweek (epiweek / isoweek) labels:
library(ggplot2)
# use simulated linelist data from the outbreaks package
dat <- outbreaks::ebola_sim_clean
dat <- dat$linelist$date_of_infection
# calculate the total number for across each week
week_dat <- aggregate(
list(cases = dat),
by = list(week = as_epiweek(dat)),
FUN = length
)
head(week_dat)
#> week cases
#> 1 2014-W12 1
#> 2 2014-W15 1
#> 3 2014-W16 1
#> 4 2014-W17 3
#> 5 2014-W18 6
#> 6 2014-W19 16
# plot the output
(week_plot <-
ggplot(week_dat, aes(week, cases)) +
geom_col(width = 1, colour = "white") +
theme_bw())
We can have non-centred date labels on the x_axis by utilising the associated scale_x_grates functions and explicitly specifying a format for the date labels:
week_plot + scale_x_grates_epiweek(format = "%Y-%m-%d")
period objects are stored as the integer number, starting at 0L, of periods
since the Unix Epoch (1970-01-01) and a specified offset. Here periods are taken
to mean groupings of n
consecutive days.
Like yearweek objects, a period object can be constructed directly via a
call to new_period()
but more easily via the as_period()
coercion function.
as_period()
takes 3 arguments; x
, the vector (normally a Date or POSIXt) you
wish to group, n
, the integer number of days you wish to group, and offset
,
the value you wish to start counting groups from relative to the Unix Epoch.
For convenience, offset
can be given as a date you want periods to be relative
to (internally this date is converted to integer).
Note that storage and calculation purposes, offset
is scaled relative to n
.
I.e. offset <- offset %% n
and values of x
stored relative to this scaled
offset.
# calculate the total number for across 14 day periods with no offset.
# note - 0L is the default value for the offset but we specify it explicitly
# here for added clarity
period_dat <- aggregate(
list(cases = dat),
by = list(period = as_period(dat, n = 14L, offset = 0L)),
FUN = length
)
head(period_dat)
#> period cases
#> 1 2014-03-13 to 2014-03-26 1
#> 2 2014-03-27 to 2014-04-09 1
#> 3 2014-04-10 to 2014-04-23 3
#> 4 2014-04-24 to 2014-05-07 19
#> 5 2014-05-08 to 2014-05-21 19
#> 6 2014-05-22 to 2014-06-04 30
ggplot(period_dat, aes(period, cases)) +
geom_col(width = 1, colour = "white") +
theme_bw() +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
xlab("")
We can also use a date as an offset
dates <- as.Date("2020-01-03") + 0:9
offset <- as.Date("2020-01-01")
data.frame(dates, period = as_period(dates, n = 7L, offset = offset))
#> dates period
#> 1 2020-01-03 2020-01-01 to 2020-01-07
#> 2 2020-01-04 2020-01-01 to 2020-01-07
#> 3 2020-01-05 2020-01-01 to 2020-01-07
#> 4 2020-01-06 2020-01-01 to 2020-01-07
#> 5 2020-01-07 2020-01-01 to 2020-01-07
#> 6 2020-01-08 2020-01-08 to 2020-01-14
#> 7 2020-01-09 2020-01-08 to 2020-01-14
#> 8 2020-01-10 2020-01-08 to 2020-01-14
#> 9 2020-01-11 2020-01-08 to 2020-01-14
#> 10 2020-01-12 2020-01-08 to 2020-01-14
yearmonth, yearquarter and year objects are stored as the integer number of months/quarters/years (starting at 0L) since the Unix Epoch (1970-01-01).
Similar to other grates objects we provide both coercion and construction functions.
(month_dat <- aggregate(
list(cases = dat),
by = list(month = as_yearmonth(dat)),
FUN = length
))
#> month cases
#> 1 2014-Mar 1
#> 2 2014-Apr 6
#> 3 2014-May 57
#> 4 2014-Jun 80
#> 5 2014-Jul 183
#> 6 2014-Aug 453
#> 7 2014-Sep 813
#> 8 2014-Oct 719
#> 9 2014-Nov 448
#> 10 2014-Dec 307
#> 11 2015-Jan 251
#> 12 2015-Feb 199
#> 13 2015-Mar 152
#> 14 2015-Apr 73
(month_plot <-
ggplot(month_dat, aes(month, cases)) +
geom_col(width = 1, colour = "white") +
theme_bw() +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
xlab(""))
Again we can have non-centred date labels by applying the associated scale
month_plot + scale_x_grates_yearmonth(format = "%Y-%m-%d")
yearquarter works similarly
(quarter_dat <- aggregate(
list(cases = dat),
by = list(quarter = as_yearquarter(dat)),
FUN = length
))
#> quarter cases
#> 1 2014-Q1 1
#> 2 2014-Q2 143
#> 3 2014-Q3 1449
#> 4 2014-Q4 1474
#> 5 2015-Q1 602
#> 6 2015-Q2 73
ggplot(quarter_dat, aes(quarter, cases)) +
geom_col(width = 1, colour = "white") +
theme_bw() +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
xlab("")
As does year
(year_dat <- aggregate(
list(cases = dat),
by = list(year = as_year(dat)),
length
))
#> year cases
#> 1 2014 3067
#> 2 2015 675
ggplot(year_dat, aes(year, cases)) +
geom_col(width = 1, colour = "white") +
theme_bw() +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
xlab("")
# Construction functions can also be used
yearmonth(2022L, 11L)
#> <grates_yearmonth[1]>
#> [1] "2022-Nov"
yearquarter(2022L, 4L)
#> <grates_yearquarter[1]>
#> [1] "2022-Q4"
year(2022L)
#> <grates_year[1]>
#> [1] 2022
month objects are stored as the integer number of n-month groups (starting at 0L) since the Unix Epoch (1970-01-01). Here n-months is taken to mean a ‘grouping of n consecutive months’.
month objects can be constructed directly from integers via the new_month()
function and through coercion via the as_month()
function. as_period()
takes
two arguments; x
, the vector (normally a Date or POSIXt) you wish to group and
n
, the integer number of months you wish to group.
# calculate the bimonthly number of cases
(bimonth_dat <- aggregate(
list(cases = dat),
by = list(group = as_month(dat, n = 2L)),
FUN = length
))
#> group cases
#> 1 2014-Mar to 2014-Apr 7
#> 2 2014-May to 2014-Jun 137
#> 3 2014-Jul to 2014-Aug 636
#> 4 2014-Sep to 2014-Oct 1532
#> 5 2014-Nov to 2014-Dec 755
#> 6 2015-Jan to 2015-Feb 450
#> 7 2015-Mar to 2015-Apr 225
# by default lower date bounds are used for the x axis
(bimonth_plot <-
ggplot(bimonth_dat, aes(group, cases)) +
geom_col(width = 1, colour = "white") +
theme_bw() +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
xlab(""))
Note that the default plotting behaviour of non-centred date labels is different to that of the yearweek, yearmonth, yearquarter and year scales where labels are centred by default. To obtain centred labels you must explicitly set the format to NULL in the scale:
bimonth_plot + scale_x_grates_month(format = NULL, n = 2L)
For all grates objects we have added many methods and operations to ensure logical and consistent behaviour. The following sections utilise the unique epiweeks from the earlier example:
weeks <- week_dat$week
Some times it is useful to access both the starting dates covered by grates
objects as well as the end dates. To this end we provide functions
date_start()
and date_end()
.
To find out whether a grate
object spans a particular date we provide a
%during%
function.
dat <- weeks[1:5]
data.frame(
week = dat,
start = date_start(dat),
end = date_end(dat),
contains.2014.04.14 = as.Date("2014-04-14") %during% dat
)
#> week start end contains.2014.04.14
#> 1 2014-W12 2014-03-16 2014-03-22 FALSE
#> 2 2014-W15 2014-04-06 2014-04-12 FALSE
#> 3 2014-W16 2014-04-13 2014-04-19 TRUE
#> 4 2014-W17 2014-04-20 2014-04-26 FALSE
#> 5 2014-W18 2014-04-27 2014-05-03 FALSE
Conversion of grate objects back to dates is analogous to date_start()
.
identical(as.Date(weeks), date_start(weeks))
#> [1] TRUE
# min, max and range
(minw <- min(weeks))
#> <grates_epiweek[1]>
#> [1] "2014-W12"
(maxw <- max(weeks))
#> <grates_epiweek[1]>
#> [1] "2015-W17"
(rangew <- range(weeks))
#> <grates_epiweek[2]>
#> [1] "2014-W12" "2015-W17"
# seq method works if both `from` and `to` are epiweeks
seq(from = minw, to = maxw, by = 6L)
#> <grates_epiweek[10]>
#> [1] "2014-W12" "2014-W18" "2014-W24" "2014-W30" "2014-W36" "2014-W42"
#> [7] "2014-W48" "2015-W01" "2015-W07" "2015-W13"
# but will error informatively if `to` is a different class
try(seq(from = minw, to = 999, by = 6L))
#> Error in seq.grates_epiweek(from = minw, to = 999, by = 6L) :
#> `to` must be a <grates_epiweek> object of length 1.
Addition (subtraction) of whole numbers will add (subtract) the corresponding number of weeks to (from) the object
dat <- head(week_dat)
(dat <- transform(dat, plus4 = week + 4L, minus4 = week - 4L))
#> week cases plus4 minus4
#> 1 2014-W12 1 2014-W16 2014-W08
#> 2 2014-W15 1 2014-W19 2014-W11
#> 3 2014-W16 1 2014-W20 2014-W12
#> 4 2014-W17 3 2014-W21 2014-W13
#> 5 2014-W18 6 2014-W22 2014-W14
#> 6 2014-W19 16 2014-W23 2014-W15
Addition of two yearweek objects will error as the intention is unclear.
try(transform(dat, willerror = week + week))
#> Error in Ops.grates_epiweek(week, week) :
#> Cannot add <grates_epiweek> objects to each other.
Subtraction of two yearweek objects gives the difference in weeks between them
transform(dat, difference = plus4 - minus4)
#> week cases plus4 minus4 difference
#> 1 2014-W12 1 2014-W16 2014-W08 8 weeks
#> 2 2014-W15 1 2014-W19 2014-W11 8 weeks
#> 3 2014-W16 1 2014-W20 2014-W12 8 weeks
#> 4 2014-W17 3 2014-W21 2014-W13 8 weeks
#> 5 2014-W18 6 2014-W22 2014-W14 8 weeks
#> 6 2014-W19 16 2014-W23 2014-W15 8 weeks
epiweek objects can be combined with themselves but not other classes (assuming an epiweek object is the first entry).
c(minw, maxw)
#> <grates_epiweek[2]>
#> [1] "2014-W12" "2015-W17"
identical(c(minw, maxw), rangew)
#> [1] TRUE
try(c(minw, 1L))
#> Error in c.grates_epiweek(minw, 1L) :
#> Unable to combine <grates_epiweek> objects with other classes.