Proximity to long weekends & holidays - r

Question

Data:
I have a vector of dates in a tibble.
# A tibble: 10 x 1
Date
<dttm>
1 2017-04-04
2 2017-04-05
3 2017-04-07
4 2017-04-10
5 2017-04-11
6 2017-04-12
7 2017-04-13
8 2017-04-14
9 2017-04-17
10 2017-04-18
Reproducible using:
structure(list(Date = structure(c(1491264000, 1491350400, 1491523200,
1491782400, 1491868800, 1491955200, 1492041600, 1492128000, 1492387200,
1492473600), class = c("POSIXct", "POSIXt"), tzone = "UTC")), class = c("tbl_df",
"tbl", "data.frame"), row.names = c(NA, -10L), .Names = "Date")
Need:
Two feature variables:
'Proximity to next holiday'
'Proximity to past holiday'
The intent is to determine if my response variable is dependent on if Date is close to a holiday or long weekend. For example, if 04-11 was a Holiday, I would want:
Date ProxNxtHol ProxPastHol
<dttm>
1 2017-04-04 4 32
2 2017-04-05 3 33
3 2017-04-07 2 34
4 2017-04-10 1 35
5 2017-04-11 0 36
6 2017-04-12 58 1
7 2017-04-13 57 2
8 2017-04-14 56 3
9 2017-04-17 55 4
10 2017-04-18 54 5
While I can manually define all the holidays in a vector myself and calculate the difference between the two dates, this is cumbersome because the holidays vary by location globally. (I have a variable which can indicate location.)
Is there a predefined function which can indicate if a given date is a holiday or not, for a specified region?

Answer 1

I have come up with this for loop that computes both proximity as shown in your desired output. Please see the steps below.
Converting your structure to data frame and all its elements to class Date
> qdates <- data.frame(qdates)
> qdates$Date <- as.Date(qdates$Date)
> qdates
Date
1 2017-04-04
2 2017-04-05
3 2017-04-07
4 2017-04-10
5 2017-04-11
6 2017-04-12
7 2017-04-13
8 2017-04-14
9 2017-04-17
10 2017-04-18
Using library(timeDate) to build a data frame of US holidays. You can add/modify your dates here or use other in-built functions that might contain federal holidays.
> library(timeDate)
> hdates <- data.frame(Dates = c(USNewYearsDay(2017), USInaugurationDay(2017), USMLKingsBirthday(2017),
USLincolnsBirthday(2017), USWashingtonsBirthday(2017), USCPulaskisBirthday(2017),
USGoodFriday(2017), USMemorialDay(2017), USIndependenceDay(2017), USLaborDay(2017),
USColumbusDay(2017), USElectionDay(2017), USVeteransDay(2017), USThanksgivingDay(2017),
USChristmasDay(2017)))
> colnames(hdates) <- "HolidayDate"
> hdates$HolidayDate <- as.Date(hdates$HolidayDate)
> hdates
HolidayDate
1 2017-01-01
2 2017-01-20
3 2017-01-16
4 2017-02-12
5 2017-02-22
6 2017-03-06
7 2017-04-14
8 2017-05-29
9 2017-07-04
10 2017-09-04
11 2017-10-09
12 2017-11-07
13 2017-11-11
14 2017-11-23
15 2017-12-25
for loop to compute the date difference, and populate output.
for(i in 1:nrow(qdates)) {
minDate <- max(hdates[which(hdates$HolidayDate <= qdates$Date[i]),])
maxDate <- min(hdates[which(hdates$HolidayDate >= qdates$Date[i]),])
qdates$ProxPastHol[i] <- abs(difftime(minDate, qdates$Date[i], units = "days"))
qdates$ProxNxtHol[i] <- abs(difftime(maxDate, qdates$Date[i], units = "days"))
}
> qdates
Date ProxPastHol ProxNxtHol
1 2017-04-04 29 10
2 2017-04-05 30 9
3 2017-04-07 32 7
4 2017-04-10 35 4
5 2017-04-11 36 3
6 2017-04-12 37 2
7 2017-04-13 38 1
8 2017-04-14 0 0
9 2017-04-17 3 42
10 2017-04-18 4 41
Hope this helps !!!