#cleaning environment
rm(list = ls())

#packages required
library(tidyverse)
library(bizdays)

#enter one or more holidays
holiday <- as.Date(c( '2023-01-02','2023-05-29','2023-07-04'))


#create a sequence of days
date_range <- seq.Date(as.Date('2023-05-24'), as.Date('2023-05-30'), 1)

#print range of dates
print(date_range)

## [1] "2023-05-24" "2023-05-25" "2023-05-26" "2023-05-27" "2023-05-28"
## [6] "2023-05-29" "2023-05-30"

#count the days from first to last date, remove saturday, remove holiday
n_distinct(date_range[!weekdays(date_range) %in% (c("Saturday", "Sunday")) & !date_range %in% holiday])

## [1] 4

business_calendar <- create.calendar('my_calendar', weekdays = c('saturday','sunday'), holidays =  holiday) #creating the calendar here

bizdays('2023-05-24', '2023-05-30', cal = business_calendar)

## [1] 3

bizdays("2023-05-24", "2023-05-30", cal = business_calendar) +1

## [1] 4

## lets do the same thing with data frames
#create example data set
df <- data.frame(
  "name"=c('a', 'b', 'c', 'd', 'e'),
  "start"=c('2023-05-24', '2023-05-24', '2023-05-23', '2023-05-22', '2023-05-22'),
  "stop"=c('2023-05-27', '2023-06-05', '2023-06-05', '2023-06-06', '2023-06-05'),
  "days_count"=''
)
df$start<- as.Date(df$start)
df$stop<- as.Date(df$stop)


#Calculate Ready for DPSS Screening to Ready for Batch, exclude weekends and federal holidays (RS to RB)
for(i in 1:nrow(df)) {
  date_range <- seq.Date(df$start[i], df$stop[i], 1)
  df$days_count[i] <- n_distinct(date_range[!weekdays(date_range) %in% (c("Saturday", "Sunday")) & !date_range %in% holiday])
  df$days_count [i] <- as.numeric(df$days_count[i])
}


#remove days count for second function
df2 <- df %>% mutate(days_count = '')
print(df2)

##   name      start       stop days_count
## 1    a 2023-05-24 2023-05-27           
## 2    b 2023-05-24 2023-06-05           
## 3    c 2023-05-23 2023-06-05           
## 4    d 2023-05-22 2023-06-06           
## 5    e 2023-05-22 2023-06-05

#use the mutate function to calculate days count
df2 <- df2 %>%
  mutate("days_count" = bizdays(from = start, to= stop, cal = business_calendar)+1)

df$days_count <- as.numeric(df$days_count)
summary(df$days_count)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##     3.0     8.0     9.0     8.2    10.0    11.0

summary(df2$days_count)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##     3.0     8.0     9.0     8.2    10.0    11.0

identical(df2$days_count, df$days_count)

## [1] TRUE