gistfile1.R

library(lubridate)
library(tibble)
library(dplyr)
library(tidyr)

t <- ymd_hms("2017/06/14 10:00:00")
tp1 <- ymd_hms("2017/06/15 15:00:00")

# 10:00 T
# 15:30 T + 1

sample_data <- 
  tibble(datetime = c(ymd_hms("2017/06/14 00:00:00", tz = "EET"),
                      ymd_hms("2017/06/14 06:00:00", tz = "EET"),
                      ymd_hms("2017/06/14 12:00:00", tz = "EET"),
                      ymd_hms("2017/06/14 18:00:00", tz = "EET"),
                      ymd_hms("2017/06/15 00:00:00", tz = "EET"),
                      ymd_hms("2017/06/15 06:00:00", tz = "EET"),
                      ymd_hms("2017/06/15 12:00:00", tz = "EET"),
                      ymd_hms("2017/06/15 18:00:00", tz = "EET"),
                      ymd_hms("2017/06/16 00:00:00", tz = "EET"),
                      ymd_hms("2017/06/16 06:00:00", tz = "EET"),
                      ymd_hms("2017/06/16 12:00:00", tz = "EET"),
                      ymd_hms("2017/06/16 18:00:00", tz = "EET")),
         sum_1 = rep(seq(0.1, 0.3, 0.1), 4),
         sum_2 = rep(seq(1, 3, 1), 4),
         sum_3 = rep(seq(10, 30, 10), 4))

result_one <- sample_data %>% 
  mutate(group = if_else(hour(datetime) >= 0 & hour(datetime) < 10, 
                         "a",
                         if_else(hour(datetime) >= 10 & hour(datetime) < 15, 
                                 "b",
                                 if_else(hour(datetime) >= 15, 
                                         "c", 
                                         "unknown")))) %>% 
  mutate(date = as.Date(datetime)) %>% 
  mutate(include = if_else(group == "a", date - days(1), date))

result_two <- result_one %>% 
  filter(group == "b") %>% 
  mutate(include = date - days(1))

result <- bind_rows(result_one, result_two)

final <- result %>% 
  group_by(include) %>% 
  summarise_at(c("sum_1", "sum_2", "sum_3"), sum)