Hi, I have a large datasets of countries with data for savings and investment for 50+ years. Some values are missing (NA) and I would like to drop the countries that have at least a missing value (or create a subset with only those with available data in all years).
I have tried both: df <- df[!is.na(df)] and df <-df[!(is.na(df$Country))] but in both cases my dataset collapses to values. Anyone so kind to give me any suggestions?
thanks in advance!