[R] Changing time intervals in data set

Rich Shepard r@hep@rd @end|ng |rom @pp|-eco@y@@com
Thu Dec 16 14:57:31 CET 2021

On Thu, 16 Dec 2021, Chris Evans wrote:

> What you said earlier was:

> For me the next step, in tidyverse pseudocode, might be something like:
> tibData %>%
>   arrange(nbr, datetime) %>% # just in case things are not ordered nicely
>   group_by(site_nbr) %>% # as you want to get changes within site I think
>   mutate(gapTime = datetime - lag(datetime)) %>% # get the simple gaps
>   summarise(nGaps = n_distinct(gapTime)) # get the number of gaps per site


Thank you. Each tibble has the data for the same site_nbr. Your pseudocode
should put me on the path to doing what I want.

If the rows were grouped by the minute (the measurement variable period) ...
I'll need to think deeply how only the time interval, not the individual
values, could be extracted.

> From what you are saying that will get you numbers of time gap changes per
> site. That will help you work out how many are simple failures of sensors
> etc. (would they come up as multiples of that site's then usual interval,
> or might they be more complex?) In the light of that you can start the
> somewhat more challenging issue of disentangling those from more long
> lasting switches in a site's gapTime value. I am sure I can offer some
> thoughts on that in the light of what you find but the best solutions will
> depend on the number of sites and on what those distributions of changes
> within site look like.

There are only four sites, and I've identified the dates and times of
measurement frequencies for one of them. My interest is on when that
measurement frequency changes. Because I've not before seen such frequency
changes in data sets I've used for projects I've no idea whether these
changes affect analytic results.

> Disclaimer: I am not a professional statistician nor a professional R
> coder though I do spend much of each week hacking up R code that works and
> supports publications. Others here are professional statisticians _and_
> professional R coders.

Neither am I a professional statistician nor do I use R every day or with
every project.



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