the quickest way to replace a nested ifelse() statements chain-CodePudding

I have this series of nested statements

data$Country == 1,"Brazil",
  ifelse(data$Country == 2, "Canada",ifelse(
    data$Country == 3, "China",ifelse(
      data$Country == 4, "Ecuador",ifelse(
        data$Country == 5, "France",ifelse(
          data$Country == 6, "Germany",ifelse(
            data$Country == 7, "India",ifelse(
              data$Country == 8, "Italy",ifelse(
                data$Country == 9, "Mexico",ifelse(
                  data$Country == 10, "Nigeria",ifelse(
                    data$Country == 11, "Poland",ifelse(
                      data$Country == 12, "Russia",ifelse(
                        data$Country == 13, "South Africa",
                        ifelse(
                          data$Country == 14, "South Korea",ifelse(
                            data$Country == 15, "Singapore",
                            ifelse(
                              data$Country == 16, "Spain",
                              ifelse(
                                data$Country == 17, "Sweden",ifelse(
                                  data$Country == 18, "United Kingdom",ifelse(
                                    data$Country == 19, "United States","l"
))))))))))))))))))))

I was looking for the quickest way to convert any encoded variable into the respective Country name. Do you think is there a way to cope with this operation?

Thank you so much

CodePudding user response：

There are 2 options:

1: case_when from dplyr

library(dplyr)
data.frame(info = letters[1:5],
           country_id = 1:5) %>% 
  mutate(country_name = case_when(country_id == 1 ~ "Brazil",
                                  country_id == 2 ~ "Canada",
                                  country_id == 3 ~ "China",
                                  country_id == 4 ~ "Ecuador",
                                  country_id == 5 ~ "France",
                                  TRUE ~ "Unknown"))

  info country_id country_name
1    a          1       Brazil
2    b          2       Canada
3    c          3        China
4    d          4      Ecuador
5    e          5       France

2: merge or join the info from a country table:

# country table
countries <- data.frame(country_id = 1:5, 
                        country_name = c("Brazil", "Canada", "China", "Ecuador", "France"))

data.frame(info = letters[1:5],
           country_id = 1:5) %>% 
  left_join(countries, by = "country_id")

  info country_id country_name
1    a          1       Brazil
2    b          2       Canada
3    c          3        China
4    d          4      Ecuador
5    e          5       France

My preference would be 2, less coding and less chance of a mistake. You can keep the country table in your database or in a file somewhere and maintain that without needing to change the code.

CodePudding user response：

I am not sure of the desired use. But maybe you can try to use a named vector. This is not the most elegant solution, though it solves the ifelse mess ;)

An example of 4 countries. China = "4"

countrys <- c("Brazil", "Canada",
              "China",
              "Ecuador")
names(countrys) <- c(2:5)

# Test data.frame
data <- data.frame(country = 4)

# Now we can get the country directly from the data$country:
# Careful! 4 is not '4'
unname(countrys[as.character(data$country)])