I have seen many questions in SO on converting daily data to weekly using xts, zoo or lubridate packages. None of the answers was found appropriate for my problem. I have tried the following code
library(zoo)
library(lubridate)
library(xts)
library(tidyverse)
#Calculation for multistation
set.seed(123)
df <- data.frame("date"= seq(from = as.Date("1970-1-1"), to = as.Date("2000-12-31"), by = "day"),
"Station1" = runif(length(seq.Date(as.Date("1970-1-1"), as.Date("2000-12-31"), "days")), 10, 30),
"Station2" = runif(length(seq.Date(as.Date("1970-1-1"), as.Date("2000-12-31"), "days")), 11, 29),
"Station3" = runif(length(seq.Date(as.Date("1970-1-1"), as.Date("2000-12-31"), "days")), 9, 28))
head(df)
# Aggregate over week
df %>%
mutate(Week = week(ymd(date)),
Year = year(ymd(date))) %>%
pivot_longer(-c(Week, date, Year), values_to = "value", names_to = "Station") %>%
group_by(Year, Week, Station) %>%
summarise(Weekly = mean(value)) %>%
arrange(Station) %>%
print(n = 55)
From the output you can see that 1970 cotains 53 weeks which I don't want. I want to start the week from the first date of every year and the 52nd week should have 8 days in a nonleap year and in case of leap years 9th and 52nd week should have 8 days so that every year contains 52 weeks only. How to do that in R?
Why not just write a function that gives the meteorological week from the definition you gave? Package lubridate will give you the day of the year with yday, which can act as the index for a vector of the correct week labels. These are straightforward to construct with simple modular math and concatenation.
You then only need to figure out if you are in a leap year, which again is possible using lubridate::leap_year. Combine these in an ifelse and you have an easy-to-use function:
met_week <- function(dates)
{
normal_year <- c((0:363 %/% 7 + 1), 52)
leap_year <- c(normal_year[1:59], 9, normal_year[60:365])
year_day <- lubridate::yday(dates)
return(ifelse(lubridate::leap_year(dates), leap_year[year_day], normal_year[year_day]))
}
and you can do
df %>% mutate(week = met_week(date))