Requirements

[runck014]

Describe how someone can get the exact same environment setup. For example:

1. Data quality requirements:

Example validation requirement

validate_input_data <- function(df) {
# Check required columns
required_cols <- c("PID", "TAX_YEAR", "PROPERTY_TYPE", "ESTIMATED_MARKET_VALUE")
missing_cols <- setdiff(required_cols, names(df))
if (length(missing_cols) > 0) {
stop(paste("Missing required columns:", paste(missing_cols, collapse=", ")))
}

# Check data completeness
completeness <- colSums(!is.na(df[,required_cols]))/nrow(df)
if (any(completeness < 0.9)) {
  warning(paste("Columns with >10% missing data:",
               paste(required_cols[completeness < 0.9], collapse=", ")))
}

# Return validated data
return(df)

}
2. Configuration management requirements
3. Model validation and diagnostics requirements
4. Reporting and output standardization requirements