R dplyr perform different aggregation by group - r

Question

I have a dataframe dat which looks like this:
dat <- structure(list(cell.ID = c(329574L, 329574L, 329574L, 329574L,
329574L, 329574L, 329574L, 329574L, 329574L, 329574L, 329574L,
329574L), Year = c("2010", "2010", "2010", "2010", "2010", "2010",
"2010", "2010", "2010", "2010", "2010", "2010"), month_name = c("June",
"July", "June", "July", "June", "July", "June", "July", "June",
"July", "June", "July"), value = c(459.860986624053, 398.94083733151,
16, 23, 111.69, 453.333, 71.55, 30.38, 31.928, 30.13355, 17.587,
19.7938709677419), variable_name = c("ETo", "ETo", "Rday", "Rday",
"Rsum", "Rsum", "Thdd", "Thdd", "Tmax", "Tmax", "Tmin", "Tmin"
), monthID = c(6L, 7L, 6L, 7L, 6L, 7L, 6L, 7L, 6L, 7L, 6L, 7L
)), row.names = c(NA, -12L), class = "data.frame")
library(dplyr)
dat %>%
dplyr::group_by(Year, variable_name) %>%
dplyr::summarise(variable = sum(value))
If I want to average the Tmax and Tmin and sum the rest of the variables, I did this
dat %>%
dplyr::group_by(Year, variable_name) %>%
dplyr::summarise(variable = ifelse(variable_name %in% c('Tmax', 'Tmin'), mean(value), sum(value)))
Error: Column `variable` must be length 1 (a summary value), not 2
How do I correct this?

Answer 1

Another way to do this is dplyr is to use if and else instead of ifelse:
dat %>%
group_by(Year, variable_name) %>%
summarise(variable = if (variable_name[1] %in% c('Tmax', 'Tmin')) mean(value) else sum(value))
# A tibble: 6 x 3
# Groups: Year [1]
Year variable_name variable
<chr> <chr> <dbl>
1 2010 ETo 859.
2 2010 Rday 39
3 2010 Rsum 565.
4 2010 Thdd 102.
5 2010 Tmax 31.0
6 2010 Tmin 18.7

Answer 2

I think the problem is that ifelse in this context is operating row-wise, not at the level of the group. If that's right, then you could work around the problem by getting both summary statistics and then conditionally selecting the one you want by variable name, like this:
dat %>%
dplyr::group_by(Year, variable_name) %>%
dplyr::summarise(var_mean = mean(value), var_sum = sum(value)) %>%
dplyr::mutate(variable = ifelse(variable_name %in% c('Tmax', 'Tmin'), var_mean, var_sum)) %>%
dplyr::select(-var_mean, -var_sum)
Result:
# A tibble: 6 x 3
# Groups: Year [1]
Year variable_name variable
<chr> <chr> <dbl>
1 2010 ETo 859.
2 2010 Rday 39
3 2010 Rsum 565.
4 2010 Thdd 102.
5 2010 Tmax 31.0
6 2010 Tmin 18.7