In my code below, i would like to find the cumsum for each year. Right now, Variable A is being summed for the entire duration. Any help would be appreciated.
library(dplyr)
library(lubridate)
set.seed(50)
DF <- data.frame(date = seq(as.Date("2001-01-01"), to= as.Date("2003-12-31"), by="day"),
A = runif(1095, 0,10))
DF1 <- DF %>%
mutate(Year = year(date), Month = month(date), JDay = yday(date)) %>%
filter(between(Month,5,10)) %>%
group_by(Year, JDay) %>%
mutate(Precipitation = cumsum(A))
It seems the issue here is with your grouping clause. Specifically, as there are as many distinct combinations of Year and JDay in your data as there are rows in DF, the subsequent cumsum operation inside mutate will simply return the same value as the input column, A. I believe the following should give you what you're after
library(dplyr)
library(lubridate)
set.seed(50)
DF <- data.frame(date = seq(as.Date("2001-01-01"), to= as.Date("2003-12-31"), by="day"),
A = runif(1095, 0,10))
DF1 <- DF %>%
mutate(Year = year(date), Month = month(date), JDay = yday(date)) %>%
filter(between(Month,5,10)) %>%
arrange(Year, JDay) %>%
group_by(Year) %>%
mutate(Precipitation = cumsum(A)) %>%
ungroup()
# illustrate that Precipitation does indeed give the cumulative value of A for
# each year by printing the first 5 observations for each year in DF1
DF1 %>%
group_by(Year) %>%
slice(1:5)
#> # A tibble: 15 x 6
#> # Groups: Year [3]
#> date A Year Month JDay Precipitation
#> <date> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 2001-05-01 6.25 2001 5 121 6.25
#> 2 2001-05-02 0.188 2001 5 122 6.43
#> 3 2001-05-03 5.37 2001 5 123 11.8
#> 4 2001-05-04 5.55 2001 5 124 17.4
#> 5 2001-05-05 5.15 2001 5 125 22.5
#> 6 2002-05-01 2.95 2002 5 121 2.95
#> 7 2002-05-02 6.75 2002 5 122 9.71
#> 8 2002-05-03 7.77 2002 5 123 17.5
#> 9 2002-05-04 8.13 2002 5 124 25.6
#> 10 2002-05-05 5.58 2002 5 125 31.2
#> 11 2003-05-01 9.98 2003 5 121 9.98
#> 12 2003-05-02 8.24 2003 5 122 18.2
#> 13 2003-05-03 6.13 2003 5 123 24.4
#> 14 2003-05-04 5.22 2003 5 124 29.6
#> 15 2003-05-05 9.81 2003 5 125 39.4