On Thu, 2 Sep 2021, Jeff Newmiller wrote:
Regardless of whether you use the lower-level split function, or the higher-level aggregate function, or the tidyverse group_by function, the key is learning how to create the column that is the same for all records corresponding to the time interval of interest.
Jeff, I definitely agree with the above
If you convert the sampdate to POSIXct, the tz IS important, because most of us use local timezones that respect daylight savings time, and a naive conversion of standard time will run into trouble if R is assuming daylight savings time applies. The lubridate package gets around this by always assuming UTC and giving you a function to "fix" the timezone after the conversion. I prefer to always be specific about timezones, at least by using so something like Sys.setenv( TZ = "Etc/GMT+8" ) which does not respect daylight savings.
I'm not following you here. All my projects have always been in a single time zone and the data might be recorded at June 19th or November 4th but do not depend on whether the time is PDT or PST. My hosts all set the hardware clock to local time, not UTC. As the location(s) at which data are collected remain fixed geographically I don't understand why daylight savings time, or non-daylight savings time is important.
Regarding using character data for identifying the month, in order to have clean plots of the data I prefer to use the trunc function but it returns a POSIXlt so I convert it to POSIXct:
I don't use character data for months, as far as I know. If a sample data is, for example, 2021-09-03 then monthly summaries are based on '09', not 'September.' I've always valued your inputs to help me understand what I don't. In this case I'm really lost in understanding your position. Have a good Labor Day weekend, Rich ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
