Calculate daily means from 5-minute interval data
The general idea is to create a "grouping" column with repeated values for each day, and then to use aggregate to compute your combined results. The dplyr package's group_by/summarise functions can also do this, and there are also proponents of the data.table package which is high performance but tends to depend on altering data in-place unlike most other R data handling functions. Also pay attention to missing data... if you have any then you will need to consider whether you want the strictness of na.rm=FALSE or permissiveness of na.rm=TRUE for your aggregation functions.
On August 29, 2021 8:08:58 AM PDT, Rich Shepard <rshepard at 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
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