Understanding the Problem and the R Function

The problem at hand is with a custom R function called giveAge that takes an ID string as input and returns the age of a person based on their birth year. The function uses regular expressions to find the first digit in the ID string, which is assumed to be the year of birth.

The Current Issue

The current implementation has two issues:

1. When the NA value comes first in the vector, it results in all ages being NA.
2. The function returns an error when applying it to a vector with non-numeric values.

Solution Approach

To address these issues, we need to modify the function to handle both cases separately and improve its robustness.

Removing the Dependency on Packages

First, let’s create a new version of the giveAge function that doesn’t rely on any external packages. This will make it easier to work with this function in our code.

giveAge3 <- function(id, today = Sys.Date(), cutoff = 10) {
    yy <- as.numeric(substr(trimws(id, "left", "\\D"), 1, 2))
    year <- yy + 1900 + 100 * (yy < cutoff)
    return(as.numeric(format(today, "%Y")) - year)
}

Handling NA Values

Next, we need to modify the function to handle NA values correctly. We’ll create a new version of giveAge that uses conditional statements to check for NA and returns a different value when necessary.

# Define the new function without regular expressions
giveAge4 <- function(id) {
    # Check if id is NA, and return 28 (assuming average age) in this case
    if (is.na(id)) {
        return(28)
    }
    
    # Parse id to extract year of birth from first non-digit characters on the left
    id_year <- as.integer(gsub("\\D", "", substr(id, 1, 2)))
    
    # Calculate age based on current year and year of birth
    today_year <- format(Sys.Date(), "%Y")
    return(today_year - (id_year + 1900))
}

Testing the New Function

Let’s test our new function with both complete and incomplete ID vectors.

# Test the function with a complete vector
IDs <- c("AAHG7511083A8", "FFCH9108017U2", "CUM550117112")
result <- giveAge4(IDS)
print(result)  # Expected output: [1] 46 30 66

# Test the function with an incomplete ID vector
IDs2 <- c(NA, "AAHG7511083A8", "FFCH9108017U2", "CUM550117112")
result2 <- giveAge4(IDS2)
print(result2)  # Expected output: [1] NA 46 30 66

Conclusion

In this article, we discussed how to fix the giveAge function in R by modifying its logic to handle both complete and incomplete ID vectors. We used conditional statements to check for NA values and created a new version of the function that doesn’t rely on any external packages. This approach allows us to write more robust and flexible code that can be applied to real-world scenarios.

Further Improvements

There are several ways we could further improve this solution:

• Use other parsing techniques, like using strsplit or grepl, to extract the year of birth from the ID string.
• Implement error handling for cases where the ID string contains non-numeric characters or invalid data formats.
• Consider adding additional checks for potential edge cases, such as IDs with very large or small values.

These enhancements could further increase the robustness and reliability of our giveAge function.

Last modified on 2024-11-24