Hello,
You have date and hour in two separate columns, so to compute daily
stats part of the work is already done. (Were they in the same column
you would have to extract the date only.)
# convert to class "Date"
df1$date <- as.Date(df1$date)
# function to compute the stats required
# it's important to note that all the stats
# are returned in a vector, see below
fun <- function(x, na.rm = FALSE){
c(mean_cfs = mean(x, na.rm = na.rm),
sd_cfs = sd(x, na.rm = na.rm))
}
# now this will put a *matrix* under cfs
# each row has the statistics computed
# by the function
agg <- aggregate(cfs ~ date, df1, fun)
str(agg)
#'data.frame': 1 obs. of 2 variables:
# $ date: Date, format: "2020-08-26"
# $ cfs : num [1, 1:2] 110400 16143
# ..- attr(*, "dimnames")=List of 2
# .. ..$ : NULL
# .. ..$ : chr [1:2] "mean_cfs" "sd_cfs"
# so now put everything in separate columns
agg <- cbind(agg[-ncol(agg)], agg[[ncol(agg)]])
str(agg)
#'data.frame': 1 obs. of 3 variables:
# $ date : Date, format: "2020-08-26"
# $ mean_cfs: num 110400
# $ sd_cfs : num 16143
Hope this helps,
Rui Barradas
Às 17:49 de 29/08/21, Rich Shepard escreveu:
On Sun, 29 Aug 2021, Eric Berger wrote:
Provide dummy data (e.g. 5-10 lines), say like the contents of a csv
file,
and calculate by hand what you'd like to see in the plot. (And describe
what the plot would look like.)
Eric,
Mea culpa! I extracted a set of sample data and forgot to include it in the
message. Here it is:
date,time,cfs
2020-08-26,09:30,136000
2020-08-26,09:35,126000
2020-08-26,09:40,130000
2020-08-26,09:45,128000
2020-08-26,09:50,126000
2020-08-26,09:55,125000
2020-08-26,10:00,121000
2020-08-26,10:05,117000
2020-08-26,10:10,120000
...
2020-08-26,23:10,108000
2020-08-26,23:15,96200
2020-08-26,23:20,86700
2020-08-26,23:25,103000
2020-08-26,23:30,103000
2020-08-26,23:35,99500
2020-08-26,23:40,85200
2020-08-26,23:45,103000
2020-08-26,23:50,95800
2020-08-26,23:55,88200
Rich
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______________________________________________
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
