Running a function in dplyr gives wrong output - r

Question

My sample data consists of daily rainfall and temperature from day 1 to 365 for year 1981 and 1982
set.seed(0)
df <- data.frame(year = rep(1981:1982, each = 365),
doy = rep(1:365, times = 2),
rainfall = sample(0:30, 730, replace = T),
tmax = sample(25:35, 730, replace = T))
Each year I have two days of the year called ref.doy and for each ref.doy, I have corresponding doy.first, doy.second.
my.df <- data.frame(year = c(1981, 1981, 1982, 1982),
ref.doy = c(250, 260, 230, 240),
doy.first = c(280, 300, 290, 310),
doy.second = c(310, 330, 340, 350))
What I want to do is for each year, take the first ref.doy and the corresponding
doy.first, doy.second and calculate total rainfall and mean temperature from
ref.doy:doy.first and doy.first:doy.second`. I wrote a function to do this:
my.func <- function(x) {
dat <- x %>%
dplyr::summarise(tot.rain.val1 = sum(rainfall[doy >= ref.doy & doy <= doy.first]),
tot.rain.val2 = sum(rainfall[doy >= doy.first & doy <= doy.second]),
mean.tmax.val1 = mean(tmax[doy >= ref.doy & doy <= doy.first]),
mean.tmax.val2 = sum(tmax[doy >= doy.first & doy <= doy.second]))
return(dat)
}
The approach I took is to first join the two data and then run my function
df <- df %>% left_join(my.df)
results <- df %>% dplyr::group_by(year, ref.doy) %>%
dplyr::summarise(results = paste(my.func(.), collapse = ","))
However, the results look a bit funny and the format is not correct. I need the results
in the following format
year ref.doy tot.rain.val1 tot.rain.val2 mean.tmax.val1 mean.tmax.val2
1981 250
1981 260
1982 230
1982 240

Answer 1

Your function returns a dataframe in the format you want, so you don't need to use paste, but save those outputs in a list and then unnest.
library(tidyverse)
df <- df %>% left_join(my.df)
df %>%
group_by(year, ref.doy) %>%
summarise(results = list(my.func(.))) %>%
unnest() %>%
ungroup() %>%
select(-year, -ref.doy)
# # A tibble: 16 x 6
# year1 ref.doy1 tot.rain.val1 tot.rain.val2 mean.tmax.val1 mean.tmax.val2
# <dbl> <dbl> <int> <int> <dbl> <int>
# 1 1981 250 396 365 29.6 939
# 2 1981 260 429 489 29.8 926
# 3 1982 230 994 805 29.3 1515
# 4 1982 240 1140 653 29.7 1224
# 5 1981 250 396 365 29.6 939
# 6 1981 260 429 489 29.8 926
# 7 1982 230 994 805 29.3 1515
# 8 1982 240 1140 653 29.7 1224
# 9 1981 250 396 365 29.6 939
#10 1981 260 429 489 29.8 926
#11 1982 230 994 805 29.3 1515
#12 1982 240 1140 653 29.7 1224
#13 1981 250 396 365 29.6 939
#14 1981 260 429 489 29.8 926
#15 1982 230 994 805 29.3 1515
#16 1982 240 1140 653 29.7 1224

Answer 2

What about something like this, if you want it in a function:
library(dplyr)
fun <- function(x,y) {
df1 <- x %>% left_join(y) %>% group_by(year,ref.doy) %>%
summarise(tot.rain.val1 = sum(rainfall[doy >= ref.doy & doy <= doy.first]),
tot.rain.val2 = sum(rainfall[doy >= doy.first & doy <= doy.second]),
mean.tmax.val1 = mean(tmax[doy >= ref.doy & doy <= doy.first]),
mean.tmax.val2 = sum(tmax[doy >= doy.first & doy <= doy.second]))
print(df1)
}
fun(df,my.df)
Joining, by = "year"
# A tibble: 4 x 6
# Groups: year [?]
year ref.doy tot.rain.val1 tot.rain.val2 mean.tmax.val1 mean.tmax.val2
<dbl> <dbl> <int> <int> <dbl> <int>
1 1981 250 396 365 29.6 939
2 1981 260 429 489 29.8 926
3 1982 230 994 805 29.3 1515
4 1982 240 1140 653 29.7 1224