Create a function named
KPI_per_country that takes two arguments:
country. The first argument,
df, represents the data frame we're using (in our case, either
bank_branches_2018). The second argument represent the name of the
country in question (for which we are doing a total count).
The function should return a data frame that has three columns:
country (the country for which we are calculating totals),
accounts. Those last two columns should be totals for the given country. Those totals are calculated using the
opened_accounts columns from the given data frame, summed across all branches for the given country.
Here's an example: If we call our function with
df = bank_branches_2018 and
country = "Austria", one row should be returned:
df[df$country == country, "number_of_clients"] will give you the number of clients for a specific country.
df[df$country == country, "opened_accounts"] will give you the number of opened accounts for those clients.
Hint 2: use the
data.frame() function. In case you don't remember how to use it, here's an example:
country = country,
clients = sum(df[df$country == country, "number_of_clients"]),
accounts = sum(df[df$country == country, "opened_accounts"])