ifelse 语句在 R 中计算

Question

I'm trying to write code to convert different currencies to EUR.

The current dataset(df) looks like this.

Currency	Price
CHF	1000
DKK	20000

My goal is mutate a column to show how much they are in EUR.

Currency	Price	EUR
CHF	1000	980
DKK	20000	2600

It seems easy but I can't really figure it out... Can anyone help me with this?

I tried a code with ifelse.

df <- df %>%
mutate(converted = ifelse(Currency == "CHF", Price*0.98, 
                      ifelse(Currency == "EUR", Price*1,         
                      ifelse(Currency == "DKK", Price*0.13))))

It returns this error message.

Error: Problem with mutate() column converted . [34mℹ[39m converted = ifelse(...) . [31m✖[39m non-numeric argument to...

I've also tried this.

df <- df %>%
mutate(converted = if(Currency == "CHF"){
    Price*0.98
} else if (Currency == "DKK"){
    Price*0.13
} else {
    Price*1
}

It returns another error message.

Error in parse(text = x, srcfile = src): <text>:9:0: unexpected end of input 7: Price*1 8: } ^

Answer 1

case_when vs nested ifelse

As mentioned in the replies, case_when() will make your code easier to read and write:

library(dplyr)

df <- tibble::tribble(
  ~Currency, ~Price,
  "CHF", 1000,
  "DKK", 20000
)

euro_prices <- df %>%
  mutate(
    converted = case_when(
      Currency == "CHF" ~ Price * 0.98, 
      Currency == "EUR" ~ Price * 1,         
      Currency == "DKK" ~ Price * 0.13,
      TRUE ~ NA_real_
    )
  )

output:

an alternative that will scale

If you have more currencies though or if you will want to track changes in the rates then it will be more effective to keep your prices and rates each in their own data.table and join the rates as needed in order to convert your prices. Something like this:

rates <- tibble::tribble(
  ~Currency, ~rate,
  "CHF", 0.98, 
  "EUR", 1,         
  "DKK", 0.13
)

df %>% 
  left_join(rates, by = "Currency") %>% 
  mutate(converted = Price * rate) %>% 
  select(-rate)

output: