Apply Function Row-Wise and Merge Results to Data Frame

Applies a function to each row of a data frame and automatically merges the results back into a single data frame. This is a convenience wrapper around byNotEmpty with automatic result consolidation, handling NULL or empty inputs gracefully.

Usage

byNotEmptyAsDf(df, func)

Arguments

df: Data frame to iterate over. If NULL, not a data frame, or has zero rows, the function returns NULL without attempting iteration.
func: Function to apply to each row. The function receives one argument: a single-row data frame representing the current row. Should return a single-row data frame, a named list, or another structure that can be coerced to a data frame row.

Value

A data frame containing the merged results from all row applications, or NULL if the input data frame is empty, NULL, or invalid. Rows from individual function calls are combined using mergeDataframeList().

Details

This function combines byNotEmpty with automatic data frame consolidation, making it ideal for transforming data frames row-by-row when each transformation produces a data frame row as output.

Common use cases include:

Enriching each row with additional data from API calls
Expanding rows that contain nested data structures
Computing row-wise aggregations that return structured results

The function internally uses mergeDataframeList() to intelligently combine heterogeneous row results, handling varying column sets gracefully.

Examples

if (FALSE) { # \dontrun{
# Transform each resource row
steps <- loadChildSteps("/Workflow")$data[[1]]
enriched <- byNotEmptyAsDf(steps, function(row) {
  data.frame(
    stepName = row$name,
    status = row$runStatus,
    isFinished = row$runStatus == "FINISHED"
  )
})

# Expand nested structures
byNotEmptyAsDf(parentData, function(row) {
  # Load children for this parent
  children <- loadChildResources(row$resourceId)$data[[1]]
  # Return summary
  data.frame(parent = row$name, childCount = nrow(children))
})
} # }