Creating Labels for Dates - r

Question

I am working in R. I have a data frame that consists of Sampling Date and water temperature. I have provided a sample dataframe below:
Date Temperature
2015-06-01 11
2015-08-11 13
2016-01-12 2
2016-07-01 12
2017-01-08 4
2017-08-13 14
2018-03-04 7
2018-09-19 10
2019-8-24 8
Due to the erratic nature of sampling dates (due to samplers ability to site) I am unable to classify years normally January 1 to December 31st and instead am using the beginning of the sampling period as the start of 1 year. In this case a year would start June 1st and End may 31st, that way I can accruately compare the years to one another. Thus I want 4 years to have the following labels
Year_One = "2015-06-01" - "2016-05-31"
Year_Two = "2016-06-01" - "2017-05-31"
Year_Three = "2017-06-01" - "2018-05-31"
Year_Four = "2018-06-01" - "2019-08-24"
My goal is to create an additional column with these labels but have thus far been unable to do so.

Answer 1

I create two columns year1 and year2 with two different approaches. The year2 approach needs that all the periods start june 1st and end may 31st (in your code the year_four ends 2019-08-24) so it may not be exactly what you need:
library(tidyverse)
library(lubridate)
dt$Date <- as.Date(dt$Date)
dt %>%
mutate(year1= case_when(between(Date, as.Date("2015-06-01") , as.Date("2016-05-31")) ~ "Year_One",
between(Date, as.Date("2016-06-01") , as.Date("2017-05-31")) ~ "Year_Two",
between(Date, as.Date("2017-06-01") , as.Date("2018-05-31")) ~ "Year_Three",
between(Date, as.Date("2018-06-01") , as.Date("2019-08-24")) ~ "Year_Four",
TRUE ~ "0")) %>%
mutate(year2 = paste0(year(Date-months(5)),"/", year(Date-months(5))+1))
The output:
# A tibble: 9 x 4
Date Temperature year1 year2
<date> <dbl> <chr> <chr>
1 2015-06-01 11 Year_One 2015/2016
2 2015-08-11 13 Year_One 2015/2016
3 2016-01-12 2 Year_One 2015/2016
4 2016-07-01 12 Year_Two 2016/2017
5 2017-01-08 4 Year_Two 2016/2017
6 2017-08-13 14 Year_Three 2017/2018
7 2018-03-04 7 Year_Three 2017/2018
8 2018-09-19 10 Year_Four 2018/2019
9 2019-08-24 8 Year_Four 2019/2020

Answer 2

Using strftime to get the years, then make a factor with levels on the unique values. I'd recommend numbers instead of words, because they can be coded automatically. Else, use labels=c("one", "two", ...).
d <- within(d, {
year <- strftime(Date, "%Y")
year <- paste("Year", factor(year, labels=seq(unique(year))), sep="_")
})
# Date temperature year
# 1 2017-06-01 1 Year_1
# 2 2017-09-01 2 Year_1
# 3 2017-12-01 3 Year_1
# 4 2018-03-01 4 Year_2
# 5 2018-06-01 5 Year_2
# 6 2018-09-01 6 Year_2
# 7 2018-12-01 7 Year_2
# 8 2019-03-01 8 Year_3
# 9 2019-06-01 9 Year_3
# 10 2019-09-01 10 Year_3
# 11 2019-12-01 11 Year_3
# 12 2020-03-01 12 Year_4
# 13 2020-06-01 13 Year_4
Data:
d <- structure(list(Date = structure(c(17318, 17410, 17501, 17591,
17683, 17775, 17866, 17956, 18048, 18140, 18231, 18322, 18414
), class = "Date"), temperature = 1:13), class = "data.frame", row.names = c(NA,
-13L))