[Rd] Help useRs to use R's own Time/Date objects more efficiently

[J C Nash]

As with many areas of R usage, my view is that the concern is one
of making it easier to find appropriate information quickly. The
difficulty is that different users have different needs. So if
one wants to know (most of) what is available, the Time Series
Task View is helpful. If one is a novice, it may now be rather
daunting, while I've found, as a long time user of different software,
that I have to dig to find what I need.

In optimization I have tried -- and have had several false starts --
to unify several packages. That could be helpful for time and date
functions.

Another possibility could be to put the "see" and "see also" information
at the TOP of the documentation rather than lower down, and also to
refer to Task Views and possibly other -- eventually R-project --
documentation objects. I happen to favour wiki-like approaches, but
there has not been much movement towards that yet. We R people are
quite strong individualists, but perhaps more team minded thinking
would help. Some of us are getting beyond our best-before date.

However, I support Martin's intent, and hope there will be attempts
in these directions.

Best,

John Nash


On 2020-04-04 5:49 a.m., Martin Maechler wrote:
> This is mostly a RFC  [but *not* about the many extra packages, please..]:
> 
> Noticing to my chagrin  how my students work in a project,
> googling for R code and cut'n'pasting stuff together, accumulating
> this and that package on the way  all just for simple daily time series
> (though with partly missing parts),
> using chron, zoo, lubridate, ...  all for things that are very
> easy in base R *IF* you read help pages and start thinking on
> your own (...), I've noted once more that the above "if" is a
> very strong one, and seems to happen rarely nowadays by typical R users...
> (yes, I stop whining for now).
> 
> In this case, I propose to slightly improve the situation ...
> by adding a few more lines to one help page [[how could that
> help in the age where "google"+"cut'n'paste" has replaced thinking ? .. ]] :
> 
> On R's own ?Dates  help page (and also on ?DateTimeClasses )
> we have pointers, notably
> 
> See Also:
> 
>      ...............
>      ...............
>      
>      'weekdays' for convenience extraction functions.
> 
> So people must find that and follow the pointer
> (instead of installing one of the dozen helper packages).
> 
> Then on that page, one sees  weekdays(), months() .. julian()
> in the usage ... which don't seem directly helpful for a person
> who needs more.  If that person is diligent and patient (as good useRs are ;-),
> she finds
> 
>    Note:
> 
> 	Other components such as the day of the month or the year are very
> 	easy to compute: just use 'as.POSIXlt' and extract the relevant
> 	component.  Alternatively (especially if the components are
> 	desired as character strings), use 'strftime'.
> 
> 
> But then, nowadays, the POSIXlt class is not so transparent to the
> non-expert anymore (as it behaves very much like POSIXct, and
> not like a list for good reasons) .. and so 97%  of R users will
> not find this "very easy".
> 
> For this reason, I propose to at add the following to the
> 'Examples:' section of the help file ...
> and I hope that also readers of  R-devel  who have not been
> aware of how to do this nicely,  will now remember (or remember
> where to look?).
> 
> I at least will tell my students in the future to use these or
> write versions of these simple utility functions.
> 
> 
> ------------------------------------------------
> 
> ## Show how easily you get month, day, year, day (of {month, week, yr}), ... :
> ## (remember to count from 0 (!): mon = 0..11, wday = 0..6,  etc !!)
> 
> ##' Transform (Time-)Date vector  to  convenient data frame :
> dt2df <- function(dt, dName = deparse(substitute(dt)), stringsAsFactors = FALSE) {
>     DF <- as.data.frame(unclass(as.POSIXlt( dt )), stringsAsFactors=stringsAsFactors)
>     `names<-`(cbind(dt, DF, deparse.level=0L), c(dName, names(DF)))
> }
> dt2df(.leap.seconds)    # date+time
> dt2df(Sys.Date() + 0:9) # date
> 
> ##' Even simpler:  Date -> Matrix:
> d2mat <- function(x) simplify2array(unclass(as.POSIXlt(x)))
> d2mat(seq(as.Date("2000-02-02"), by=1, length.out=30)) # has R 1.0.0's release date
> 
> ------------------------------------------------------------
> 
> In the distant past / one of the last times I touched on people
> using (base) R's  Date / Time-Date  objects, I had started
> thinking if we should not provide some simple utilities to "base R"
> (not in the 'base' pkg, but rather 'utils') for "extracting" from
> {POSIX(ct), Date} objects ... and we may have discussed that
> within R Core 20 years ago,  and had always thought that this
> shouldn't be hard for useRs themselves to see how to do...
> 
> But then I see that "everybody" uses extension packages instead,
> even in the many situations where there's no gain doing so, 
> but rather increases the dependency-complexity of the data analysis
> unnecessarily.
> 
> Martin Maechler
> ETH Zurich  and   R Core Team.
> 
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