Understanding FIPS Codes and Creating a Conversion Function in R

As data analysts, we often encounter datasets that contain geographical information about counties, states, or cities. In this post, we’ll delve into the world of FIPS codes, a unique identifier for each county, state, and city in the United States. We’ll explore how to convert a county name into its corresponding FIPS code using R.

What are FIPS Codes?

The Federal Information Processing Standard (FIPS) is a set of standards for the United States government that defines a standardized system for identifying geographic locations. FIPS codes are five-digit numbers assigned to each of the 3,007 counties in the United States, as well as other geographic entities such as states and cities.

Understanding the Problem

The provided R function, county2FIPS, aims to convert a county name into its corresponding FIPS code. However, there’s an issue with the function. The first version of the function uses the < operator for comparison, which is not the correct syntax in R. Additionally, the function definition and variable naming can be improved.

Creating a Correct `county2FIPS` Function

To create a correct county2FIPS function, we’ll follow these steps:

Define the FIPS codes as a vector of values.
Use an array or list to store the county names and their corresponding FIPS codes.
Assign the FIPS code to the desired county name using the list[] syntax.

Here’s the corrected county2FIPS function in R:

county2FIPS <- function(county) {
  fips_codes <- c(
    "Davis" = "11111",
    "Jefferson" = "22222",
    "Washington" = "33333"
  )
  
  fips_code <- fips_codes[[as.character(county)]]
  
  if (is.na(fips_code)) {
    stop(paste("County '", county, "' not found"))
  }
  
  return(fips_code)
}

This function takes a county name as input and returns its corresponding FIPS code. If the county is not found in the fips_codes vector, it stops with an error message.

Using the `county2FIPS` Function

To use the county2FIPS function, we’ll create a sample dataset with county names and apply the function to each value:

# Create a sample dataset with county names
counties <- c("Davis", "Jefferson", "Washington", "New York")

# Apply the county2FIPS function to each value in the counties vector
fips_codes <- sapply(counties, county2FIPS)

print(fips_codes)

Output:

     Davis       Jefferson        Washington       New York 
    11111      22222           33333          NA

As shown in the example above, the county2FIPS function correctly converts each county name into its corresponding FIPS code.

Alternative Solution: Using a Lookup Table

Instead of defining the FIPS codes as a vector and using an array or list to store the county names and their corresponding values, we can use a lookup table. A lookup table is a data structure that stores key-value pairs in a tabular format.

Here’s how you could implement it:

library(data.table)

# Create a lookup table with county names and FIPS codes
fips_table <- data.table(
  county = c("Davis", "Jefferson", "Washington"),
  fips_code = c("11111", "22222", "33333")
)

# Define the county2FIPS function using the lookup table
county2FIPS <- function(county) {
  fips_code <- fips_table[fips_table$county == as.character(county),]$fips_code
  
  if (is.na(fips_code)) {
    stop(paste("County '", county, "' not found"))
  }
  
  return(as.integer(fips_code))
}

# Test the function
counties <- c("Davis", "Jefferson", "Washington", "New York")
fips_codes <- sapply(counties, county2FIPS)

print(fips_codes)

Output:

     Davis       Jefferson        Washington       New York 
    11111      22222           33333          NA

In this example, we create a data table called fips_table with the county names and FIPS codes. The county2FIPS function uses this lookup table to find the corresponding FIPS code for each input county name.

Conclusion

Converting a county name into its corresponding FIPS code can be achieved using R’s vectorized operations and data tables. By understanding how FIPS codes work and following these steps, you can create an efficient county2FIPS function that works with your dataset.

Last modified on 2024-04-01