Welcome!
I tried to take your descriptionof the data and created a sample input dataset. Note the below is just a screenshot. The code to generate that is below and is assigned to the "dataset" variable.
To do this I used datapasta to paste from Sheets to R. I recommend this fabulous post on how to generate a reprex https://maraaverick.rbind.io/2018/10/reprex-with-datapasta/.
#read in sample data from Sheets using datapasta
library(tidyverse)
dataset <- data.frame(stringsAsFactors=FALSE,
CouncilCode = c("x", "x", "x", "x", "x", "y", "y", "y", "y", "z", "z", "z",
"z", "z", "z"),
Response = c(1L, 1L, NA, NA , 3L, 4L, 4L, 3L, 1L, 1L, 3L, 3L, 2L, 2L, NA)
)

On to the actual computation. What I ended up doing here is grouping by CouncilCode and summing across Response where Response is not NA.
What I end up with is a column TotalEligibleResponses that is equal to the sum of responses that are not NA.
#computation
dataset %>% group_by(CouncilCode) %>%
mutate(TotalEligibleResponses = sum(!is.na(Response)))
Check out the TotalEligibleResponses column.