Mutation count

19.05.2024

Let’s use the SMMT package and the municipality inventory data to analyse the number of mutations.

By now, we know that municipalities change frequently in Switzerland. To get a better grasp, how often mutations occur, we can analyse the yearly frequency of these changes.


start_date <- seq.Date(as.Date("1960-01-01"), to = as.Date("2022-01-01"), by = "1 year")

res <- mutation_count(mutations = mutations_object$mutations, 
                      start_date, start_date + lubridate::years(1), 
                      territorial_changes_only = FALSE)


p <- ggplot(data = res, aes(start_date, number_of_mutations_in_period)) + geom_bar(stat = "identity")
print(p)

This calculation also includes the administrative changes as well. Mutations that had a territorial effect can be calculated as follows:


res <- territorial_mutation_count(mutations = mutations_object$mutations, 
                      start_date, start_date + lubridate::years(1))

p <- ggplot(data = res, aes(start_date, number_of_mutations_in_period)) + geom_bar(stat = "identity")
print(p)