R语言中转换非常规时间格式3:34'35"为数值类型的方法问询

Got it, let's work through this problem—those apostrophes and quotes in your time string definitely throw R off when importing as a factor. Here are a few straightforward, reliable methods to convert it into either a proper time object or a numeric value (like total seconds):

Method 1: Use lubridate for Clean Time Objects #

This is my go-to for time handling because it's intuitive and requires minimal string manipulation:

1. First, convert your factor column to a character vector (since factor operations can be tricky):

   time_char <- as.character(your_data$time_column)
   

2. Clean up the weird symbols: replace the single apostrophe with a colon, and strip out the double quote:

   clean_time <- gsub("'", ":", gsub('"', "", time_char))
   # Now your strings look like "3:34:35"
   

3. Use lubridate::hms() to parse it into a time period object (this works for hours:minutes:seconds):

   library(lubridate)
   time_period <- hms(clean_time)
   

   • The time_period object is a Period type, which lets you do time arithmetic directly (e.g., adding/subtracting times).
   • If you want a numeric value (total seconds), just convert it:

     time_seconds <- as.numeric(time_period)
     

Method 2: No External Packages (Base R Only) #

If you don't want to install extra libraries, you can split the string components manually and calculate total seconds:

1. Convert to character and split the string into hours, minutes, and seconds parts:

   time_str <- as.character(your_data$time_column)
   # Split on colon and apostrophe to get separate components
   parts <- strsplit(time_str, split = "[:']")
   

2. Extract each component, clean the seconds (remove the double quote), and convert to numeric:

   hours <- sapply(parts, function(x) as.numeric(x[1]))
   minutes <- sapply(parts, function(x) as.numeric(x[2]))
   seconds <- sapply(parts, function(x) as.numeric(gsub('"', "", x[3])))
   

3. Calculate total seconds (or convert to other units if needed):

   total_seconds <- hours * 3600 + minutes * 60 + seconds
   

Method 3: Use readr for Direct Parsing #

The readr package has a flexible parse_time() function that can handle custom formats directly, no need for extra string cleanup:

library(readr)
# The format string matches your original pattern: %H (hours), %M (minutes), literal ', %S (seconds), literal "
time_obj <- parse_time(as.character(your_data$time_column), format = "%H:%M'%S\"")

• This returns a POSIXct-like time object, which integrates well with other R time functions.
• Again, convert to numeric seconds with as.numeric(time_obj) if needed.

Quick Note on Edge Cases #

If you have missing values or malformed entries (e.g., strings that don't follow the h:m's" pattern), wrap the parsing functions in tryCatch() or use na_if() to handle them gracefully. For example:

clean_time <- gsub("'", ":", gsub('"', "", time_char))
clean_time[clean_time == ""] <- NA
time_period <- hms(clean_time)

内容的提问来源于stack exchange，提问作者Denis