R - split data to hydrological quarters

Question

I wish to split my data sets into year quarters according to definition of hydrological year. According to Wikipedia, "Due to meteorological and geographical factors, the definition of the water years varies". In USA, hydrological year is a period between October 1st of one year and September 30th of the next. I use definition of hydrological year for Poland (starts at November 1st and ends at October 31st).

Sample data set looks as folllows:

sampleData <- structure(list(date = structure(c(15946, 15947, 15875, 15910, 15869, 15888, 15823, 16059, 16068, 16067), class = "Date"),`example value` = c(-0.325806595888448, 0.116001346459147, 1.68884381116696, -0.480527505762716, -0.50307381813168,-1.12032214801472, -0.659699514672226, -0.547101497279717, 0.729148872679021,-0.769760735764215)), .Names = c("date", "example value"), row.names = c(NA, -10L), class = "data.frame")

For some reason, function "cut" in my code complains that "breaks" and "labels" differs in length (but they don't). If I omit "labels" options in cut (as below) function works perfectly. What is wrong with labels?

ToHydroQuarters <-function(df)
{
  result <- df
  yearStart <- as.numeric(format(min(df$date),'%Y'))-1
  #Hydrological year in Poland starts at November 1st
  DateStart <- as.Date(paste(yearStart,"-11-01",sep=""))

  breaks <- seq(from=DateStart, to=max(df$date)+90, by="quarter")
  breakYear <- format(breaks,'%Y')

  #Please, do not create labels in such way.
  #Please note that for November and December we have next hydrological year - since it started at 1st November. So, we need to check month to decide which year we have (?) or use cut function again as mentioned here: http://stackoverflow.com/questions/22073881/hydrological-year-time-series
  labels <- c(paste("Winter",breakYear[1]),
           paste("Spring",breakYear[2]),
           paste("Summer",breakYear[3]),
           paste("Autumn",breakYear[4]),
           paste("Autumn",breakYear[5]))

  ######Here is problem - once I add labels parameter, function complains about different lengths
  result$hydroYear <- cut(df$date, breaks)

  result
}

Answer 1

Firstly I think it is unwise to have labels as a "hardcoded" variable in a function since it is impossible to check without some kind of reproducible example, however I can see what you're trying to achieve.

You claim that your break and labels should be the correct length, however the function itself doesn't always work (this is without the labels, even if the labels did exist the cut function did not process the last portion of the dates).

For example:

library(lubridate)
x <- ymd(c("09-01-01", "09-01-02", "11-09-03"))
df <- data.frame(date=as.Date(seq(from=min(x), to=max(x), by="day")))
a <- ToHydroQuarters(df)

tail(a)

returns:

          date hydroYear
971 2011-08-29      <NA>
972 2011-08-30      <NA>
973 2011-08-31      <NA>
974 2011-09-01      <NA>
975 2011-09-02      <NA>
976 2011-09-03      <NA>

Doing something like breaks <- seq(from=DateStart, to=max(df$date)+90, by="quarter"), does resolve that issue, as it forces a break to actually exist. This might solve your labelling issue that you've had in your function, but it does not make the function "generic".

---

Personally on the coding side I think it would be better to convert the month, and year parts separately, because it would be easier to understand. For example, you could use library(lubridate) to easily extract the month and specify the breaks and the labels as you normally would. I was thinking the function could look something like this:

thq <- function(date) {
  mnth <- cut(month(date), breaks=c(1,4,7, 10, 12), 
              right=FALSE, include.lowest=TRUE, 
              labels=c("Spring", "Summer", "Autumn", "Winter"))
  return(paste(mnth, ifelse(mnth == "Winter", year(date)+1, year(date))))
}

So then using some dummy data ...

library(lubridate)
x <- ymd(c("09-01-01", "09-01-02", "11-09-03"))
df <- data.frame(date=as.Date(seq(from=min(x), to=max(x), by="month")))

thq <- function(date) {
  mnth <- cut(month(date), breaks=c(1,4,7, 10, 12), 
              right=FALSE, include.lowest=TRUE, 
              labels=c("Spring", "Summer", "Autumn", "Winter"))
  return(paste(mnth, ifelse(mnth == "Winter", year(date)+1, year(date))))
}

df$newdate <- thq(df$date)

Which has the following output:

         date     newdate
1  2009-01-01 Spring 2009
2  2009-02-01 Spring 2009
3  2009-03-01 Spring 2009
4  2009-04-01 Summer 2009
5  2009-05-01 Summer 2009
6  2009-06-01 Summer 2009
7  2009-07-01 Autumn 2009
8  2009-08-01 Autumn 2009
9  2009-09-01 Autumn 2009
10 2009-10-01 Winter 2010
11 2009-11-01 Winter 2010
12 2009-12-01 Winter 2010
13 2010-01-01 Spring 2010
14 2010-02-01 Spring 2010
15 2010-03-01 Spring 2010
16 2010-04-01 Summer 2010
17 2010-05-01 Summer 2010
18 2010-06-01 Summer 2010
19 2010-07-01 Autumn 2010
20 2010-08-01 Autumn 2010
21 2010-09-01 Autumn 2010
22 2010-10-01 Winter 2011
23 2010-11-01 Winter 2011
24 2010-12-01 Winter 2011
25 2011-01-01 Spring 2011
26 2011-02-01 Spring 2011
27 2011-03-01 Spring 2011
28 2011-04-01 Summer 2011
29 2011-05-01 Summer 2011
30 2011-06-01 Summer 2011
31 2011-07-01 Autumn 2011
32 2011-08-01 Autumn 2011
33 2011-09-01 Autumn 2011

---

You can shift the months using the modulo operator if it is in a weird order...

thq <- function(date) {
mnth <- cut(((month(df$date)+1) %% 12), breaks=c(0, 3, 6, 9, 12), 
            right=FALSE, include.lowest=TRUE, 
            labels=c("Nov_Jan", "Feb_Apr", "May_Jul", "Aug_Oct")
            )
# you will need to alter the return statement yourself, because
# I feel there is enough information for you to do it, rather than
# me changing it every time you change the question.
return(paste(mnth, ifelse(mnth == "Winter", year(date)+1, year(date))))
}

library(lubridate)
x <- ymd(c("09-01-01", "09-01-02", "11-09-03"))
df <- data.frame(date=as.Date(seq(from=min(x), to=max(x), by="day")))

df$new <- thq(df$date)

head(df)

output:

> head(df)
        date          new
1 2009-01-01 Nov_Jan 2009
2 2009-01-02 Nov_Jan 2009
3 2009-01-03 Nov_Jan 2009
4 2009-01-04 Nov_Jan 2009
5 2009-01-05 Nov_Jan 2009
6 2009-01-06 Nov_Jan 2009