Grouping every n minutes with dplyr

lubridate-dplyr-esque solution.

library(lubridate)
library(dplyr)
d2 <- data.frame(interval = seq(ymd_hms('2010-05-21 00:00:00'), by = '3 min',length.out=(1440/3)))
d3 <- d1 %>% 
  mutate(interval = floor_date(date, unit="hour")+minutes(floor(minute(date)/3)*3)) %>% 
  group_by(interval) %>% 
  mutate(sumvalue=sum(value))  %>% 
  select(interval,sumvalue) 
d4 <- merge(d2,d3, all=TRUE) # better if left_join is used
tail(d4)
#               interval sumvalue
#475 2010-05-21 23:42:00       NA
#476 2010-05-21 23:45:00       NA
#477 2010-05-21 23:48:00       NA
#478 2010-05-21 23:51:00       NA
#479 2010-05-21 23:54:00       NA
#480 2010-05-21 23:57:00       NA
d4[450,]
#               interval sumvalue
#450 2010-05-21 22:27:00   643426

If you are comfortable working with Date (I am not), you can dispense with lubridate, and replace the final merge with left_join.

If you need to group data into n minute bins, the floor_date function can allow multiple units to be specified within the unit argument of the function. For example:

library(lubridate)
x <- ymd_hms("2009-08-03 12:25:59.23")
floor_date(x, unit = "3minutes")

"2009-08-03 12:24:00 UTC"

Using your example:

library(lubridate)
library(tidyverse)

# make complete time sequence
d2 <- data.frame(timePeriod = seq(as.POSIXct("2010-05-21 00:00:00"), 
                        by="3 min", length.out=(1440/3)))

d1 %>%
  mutate(timePeriod = floor_date(date, "3minutes")) %>%
  group_by(timePeriod) %>%
  summarise(sum = sum(value)) %>%
  right_join(d2)