Hello,
I would suggest something like: date <- seq(as.Date("2020-01-01"), as.Date("2020-12-31"), 1) time <- sprintf("%02d:%02d", rep(0:23, each = 12), seq.int(0, 55, 5)) x <- data.frame( date = rep(date, each = length(time)), time = time ) x$cfs <- stats::rnorm(nrow(x)) cols2aggregate <- "cfs" # add more as necessary S <- split(x[cols2aggregate], x$date) means <- do.call("rbind", lapply(S, colMeans, na.rm = TRUE)) sds <- do.call("rbind", lapply(S, function(xx) sapply(xx, sd, na.rm = TRUE))) On Sun, Aug 29, 2021 at 11:09 AM Rich Shepard <rshep...@appl-ecosys.com> wrote: > I have a year's hydraulic data (discharge, stage height, velocity, etc.) > from a USGS monitoring gauge recording values every 5 minutes. The data > files contain 90K-93K lines and plotting all these data would produce a > solid block of color. > > What I want are the daily means and standard deviation from these data. > > As an occasional R user (depending on project needs) I've no idea what > packages could be applied to these data frames. There likely are multiple > paths to extracting these daily values so summary statistics can be > calculated and plotted. I'd appreciate suggestions on where to start to > learn how I can do this. > > TIA, > > 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. > [[alternative HTML version deleted]] ______________________________________________ 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.