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2017 Dec 30
0
10 Minute Time Window Aggregate By Multiple Grouping Variables
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variables of interest (distance and fuel for example) by the 10.min start
and end time intervals across all ids as long as there is the 10min
start/end time overlap derived from the raw data 4. Repeat the same with
some grouping criteria from DateTime or suitable index, example day of week
or by truckid. From index 1 (00:00:00 to 00:10:00 ) to index 6(00:00:50 to
01:00:00), 60 miles and 6 gallons are equally distributed.
So far, I have created the 10 min HH:MM ids and exploring the foverlaps in
data.table, period.apply from xts, converting the time indices into
numerics and explore ddply %>%...