6/1/2023 0 Comments Minus minutes from as.posixct![]() The following approach is approximately 1,000x faster than the cut approach (tested with 400k records. The cut approach is handy but slow with large data frames. If you don't know the break interval, for example, because you chose the number of breaks and let R pick the interval, you could find the number of seconds to add by doing max(unique(diff(as.POSIXct(as.character(dat$by15))))) - 1. This matches the default format that datetimeparsecomplete () parses. If format is NULL, a default format of 'Y-m-dTH:M:SEz Z' is used. dateformat () formats a date-time (POSIXct) using a format string. retains the same hour, minute, and second information If FALSE, the new date will be. If you want the end point to the nearest minute before the next interval (instead of the nearest second), you could to as.POSIXct(as.character(dat$by15)) + 60*14. This is a POSIXct method for the dateformat () generic. A period or a date-time object of class POSIXlt, POSIXct or Date. The as.POSIXct(as.character(.)) is because cut returns a factor and this just converts it back to date-time so that we can do math on it. We add 60*15 - 1 because POSIXct is denominated in seconds. ![]() In other words, the endpoint of the grouping interval is 15 minutes minus one second from the start of the interval. A string type date object can be converted to POSIXct object, using the as.POSIXct (date) method in R. Another way (as mentioned by nicola and is present in the same documentation) is to take advantage of the fact that - has a. Table of contents: 1) Example 1: Apply as.POSIXlt () Function with Default Specifications 2) Example 2: Apply as. UPDATE: To answer the comment, for this case the end point of each grouping interval is as.POSIXct(as.character(dat$by15)) + 60*15 - 1. In this R tutorial you’ll learn how to manipulate date and time objects using the as.POSIXlt function. Now aggregate by the new grouping column, using sum as the aggregation function: dat.summary = aggregate(count ~ by15, FUN=sum, data=dat)ĭat.summary = dat %>% group_by(by15=cut(time, "15 min")) %>%ĭat.summary = setDT(dat) The code below shows how to do this in base R and with the dplyr and data.table packages.įirst, create some fake data: set.seed(4984)ĭat = ame(time=seq(as.POSIXct(""), as.POSIXct("") + 60*99, by=60),Ĭut the data into 15 minute groups: dat$by15 = cut(dat$time, breaks="15 min") For data that's in POSIXct format, you can use the cut function to create 15-minute groupings, and then aggregate by those groups. Since POSIXct objects are, internally, a number of seconds, it is possible to add or subtract seconds from them.
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