[R] Calculate daily means from 5-minute interval data
@kw@|mmo @end|ng |rom gm@||@com
Sun Aug 29 19:13:03 CEST 2021
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 =
On Sun, Aug 29, 2021 at 11:09 AM Rich Shepard <rshepard using appl-ecosys.com>
> 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.
> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> PLEASE do read the posting guide
> and provide commented, minimal, self-contained, reproducible code.
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