segregation datetime on hourly basis in R - r

Question

I'm using below-mentioned dataframe in R:
ID Datetime Value
T-1 2020-01-01 15:12:14 10
T-2 2020-01-01 00:12:10 20
T-3 2020-01-01 03:11:11 25
T-4 2020-01-01 14:01:01 20
T-5 2020-01-01 18:07:11 10
T-6 2020-01-01 20:10:09 15
T-7 2020-01-01 15:45:23 15
Using the above mentioned dataframe, I want to segregate datetime on hourly basis. For which, I'm using following code.
library(tidyverse)
DF$bins <- cut(lubridate::hour(DF$Datetime), c(-1, 0:24 - 0.01))
levels(DF$bins) <- c("00:00 to 00:59", "00:01 to 01:59", "00:02 to 02:59", "00:03 to 03:59", "00:04 to 04:59", "00:05 to 05:59",
"00:06 to 06:59", "00:07 to 07:59", "00:08 to 08:59", "00:09 to 09:59", "00:10 to 10:59", "00:11 to 11:59",
"00:12 to 12:59", "00:13 to 13:59", "00:14 to 14:59", "00:15 to 15:59", "00:16 to 16:59", "00:17 to 17:59",
"00:18 to 18:59", "00:19 to 19:59", "00:20 to 20:59", "00:21 to 21:59", "00:22 to 22:59", "00:23 to 23:59")
newDF <- DF %>%
dplyr::group_by(bins, .drop = FALSE) %>%
dplyr::summarise(Count = length(Value), Total = sum(Value))
Final<-newDF %>%
dplyr::summarise(bins = "January", Count = sum(Count), Total = sum(Total)) %>% bind_rows(newDF)
Final[,c(2,3)]<-sapply(Final[,c(2,3)], function(x) scales::comma(x))
at levels(DF$bins)<- I'm getting error Error inlevels<-.factor(tmp, value = c("00:00 to 00:59", "00:01 to 01:59", :
number of levels differs
How to keep below mentioned segregation static and aggregate the numbers accordingly.
"00:00 to 00:59", "00:01 to 01:59", "00:02 to 02:59", "00:03 to 03:59", "00:04 to 04:59", "00:05 to 05:59", "00:06 to 06:59", "00:07 to 07:59", "00:08 to 08:59", "00:09 to 09:59", "00:10 to 10:59", "00:11 to 11:59","00:12 to 12:59", "00:13 to 13:59", "00:14 to 14:59", "00:15 to 15:59", "00:16 to 16:59", "00:17 to 17:59","00:18 to 18:59", "00:19 to 19:59", "00:20 to 20:59", "00:21 to 21:59", "00:22 to 22:59", "00:23 to 23:59"
Expected Output:
Month Count Sum
Jan-20 7 115
12:00 AM to 05:00 AM 2 45
06:00 AM to 12:00 PM 0 0
12:00 PM to 03:00 PM 1 20
03:00 PM to 08:00 PM 3 35
08:00 PM to 12:00 AM 1 15

Answer 1

We can use floor_date/ceiling_date from lubridate to create hourly breaks, create a grouping column (bins) based on our requirement using sprintf and then use this column to calculate whatever we want for each group.
library(dplyr)
library(lubridate)
df %>%
mutate(bins = floor_date(Datetime, "hour"),
hour = hour(bins),
bins = paste0(sprintf("%02d:00 :", hour), sprintf(" %02d:59", hour))) %>%
group_by(bins) %>%
summarise(sum = sum(Value))
# A tibble: 6 x 2
# bins sum
# <chr> <int>
#1 00:00 : 00:59 20
#2 03:00 : 03:59 25
#3 14:00 : 14:59 20
#4 15:00 : 15:59 25
#5 18:00 : 18:59 10
#6 20:00 : 20:59 15
For the updated condition, we can do
df %>%
mutate(hour = hour(Datetime),
gr = case_when(hour >= 0 & hour < 6 ~ "12:00 AM to 06:00 AM",
hour >= 6 & hour < 12 ~ "06:00 AM to 12:00 PM",
hour >= 12 & hour < 15 ~ "12:00 PM to 03:00 PM",
hour >= 15 & hour < 20 ~ "03:00 PM to 08:00 PM",
TRUE ~ "08:00 PM to 12:00 AM"),
month_year = format(Datetime, "%Y-%m"),
bins = factor(gr, levels = c("12:00 AM to 06:00 AM", "06:00 AM to 12:00 PM",
"12:00 PM to 03:00 PM", "03:00 PM to 08:00 PM",
"08:00 PM to 12:00 AM"))) %>%
group_by(month_year, bins, .drop = FALSE) %>%
summarise(sum = n())
# month_year bins sum
# <chr> <fct> <int>
#1 2020-01 12:00 AM to 06:00 AM 2
#2 2020-01 06:00 AM to 12:00 PM 0
#3 2020-01 12:00 PM to 03:00 PM 1
#4 2020-01 03:00 PM to 08:00 PM 3
#5 2020-01 08:00 PM to 12:00 AM 1
data
df <- structure(list(ID = structure(1:7, .Label = c("T-1", "T-2", "T-3",
"T-4", "T-5", "T-6", "T-7"), class = "factor"), Datetime = structure(c(1577891534,
1577837530, 1577848271, 1577887261, 1577902031, 1577909409, 1577893523
), class = c("POSIXct", "POSIXt"), tzone = "UTC"), Value = c(10L,
20L, 25L, 20L, 10L, 15L, 15L)), row.names = c(NA, -7L), class = "data.frame")