R语言嵌套ifelse处理字符、时间日期变量时出错求助

Let's break down what's going wrong with your code and fix it step by step, plus I'll show a cleaner alternative that avoids messy nested ifelse calls.

First, the root causes of your error #

• Incorrect ifelse syntax: ifelse() only takes 3 arguments: condition, yes, no. You tried passing a 4th argument to the first ifelse, which is why you got the "unused argument" error. Your nested structure was misaligned.
• Incomplete difftime calls: For Frankfurt and Hamburg, you forgot to compare the closing time to the HMS value—you only passed one time to difftime, which is invalid.
• Variable name mismatch: Your data frame has StockExchange (singular), but your code uses StockExchanges (plural) — that would cause unexpected FALSE values.
• Mixing df and df1: You start modifying df$TimeStampNew but then reference df1 later; keep your data frame names consistent.
• NA handling can be integrated: No need for a separate line to handle NA HMS values—we can include that in our logic.

Fixed nested ifelse code #

First, let's correct the syntax and fix all the issues:

# Ensure variable names match your data frame (StockExchange, not StockExchanges)
df$TimeStampNew <- with(df, 
  ifelse(is.na(HMS),  # Handle NA HMS values first
         as.character(TimeStamp),
         ifelse(StockExchange == "Vienna" & difftime(as.POSIXct(HMS, format = "%H:%M:%S"), 
                                                     as.POSIXct("17:35:00", format = "%H:%M:%S")) > 0,
                as.character(TimeStamp + 1),
                ifelse(StockExchange == "Frankfurt" & difftime(as.POSIXct(HMS, format = "%H:%M:%S"), 
                                                               as.POSIXct("22:00:00", format = "%H:%M:%S")) > 0,
                       as.character(TimeStamp + 1),
                       ifelse(StockExchange == "Hamburg" & difftime(as.POSIXct(HMS, format = "%H:%M:%S"), 
                                                                     as.POSIXct("20:00:00", format = "%H:%M:%S")) > 0,
                              as.character(TimeStamp + 1),
                              as.character(TimeStamp))
                       )
                )
         )
)

A cleaner alternative using dplyr::case_when #

Nested ifelse gets hard to read quickly. Using case_when from the dplyr package makes this logic much more explicit and maintainable:

library(dplyr)

df <- df %>%
  mutate(
    TimeStampNew = case_when(
      # Keep original timestamp if HMS is NA
      is.na(HMS) ~ as.character(TimeStamp),
      # Vienna: add 1 day if HMS is later than 17:35
      StockExchange == "Vienna" & difftime(as.POSIXct(HMS, format = "%H:%M:%S"), 
                                           as.POSIXct("17:35:00", format = "%H:%M:%S")) > 0 ~ as.character(TimeStamp + 1),
      # Frankfurt: add 1 day if HMS is later than 22:00
      StockExchange == "Frankfurt" & difftime(as.POSIXct(HMS, format = "%H:%M:%S"), 
                                              as.POSIXct("22:00:00", format = "%H:%M:%S")) > 0 ~ as.character(TimeStamp + 1),
      # Hamburg: add 1 day if HMS is later than 20:00
      StockExchange == "Hamburg" & difftime(as.POSIXct(HMS, format = "%H:%M:%S"), 
                                            as.POSIXct("20:00:00", format = "%H:%M:%S")) > 0 ~ as.character(TimeStamp + 1),
      # Default: keep original timestamp for all other cases
      TRUE ~ as.character(TimeStamp)
    )
  )

Both solutions handle all your requirements: NA values, exchange-specific closing time checks, and date incrementing when needed. The case_when version is far easier to edit if you add more exchanges or adjust closing times later.

内容的提问来源于stack exchange，提问作者Chellarioo