Filter feeds or datasets by validation quality

Filter feed or dataset results by validation quality thresholds. This is a convenience wrapper around get_validation_report() that returns the original data filtered to only include feeds/datasets meeting your quality criteria.

Note: This function does not support GBFS validation reports at this time as GBFS validation reports are located at a different endpoint and have a different validation criteria.

Usage

filter_by_validation(
  data,
  max_errors = NULL,
  max_warnings = NULL,
  max_info = NULL,
  require_validation = TRUE
)

Arguments

data

A tibble from feeds(), mobdb_datasets(), or mobdb_search().

max_errors

Maximum number of validation errors allowed. Use 0 for error-free feeds. If NULL (default), no error filtering is applied.

max_warnings

Maximum number of validation warnings allowed. If NULL (default), no warning filtering is applied.

max_info

Maximum number of informational notices allowed. If NULL (default), no info filtering is applied.

require_validation

Logical. If TRUE (default), exclude feeds/datasets that have no validation data. If FALSE, include them in results.

Value

A filtered version of the input data frame containing only feeds/datasets that meet the specified quality criteria.

See also

get_validation_report() to inspect validation metrics, view_validation_report() to view full validation reports

Examples

if (FALSE) { # \dontrun{
# Find all California feeds with zero errors
ca_feeds <- feeds(
  country_code = "US",
  subdivision_name = "California",
  data_type = "gtfs"
)
clean_feeds <- filter_by_validation(ca_feeds, max_errors = 0)

# Find feeds with minimal issues
quality_feeds <- filter_by_validation(
  ca_feeds,
  max_errors = 0,
  max_warnings = 100
)

# Get historical BART datasets with improving quality
bart <- feeds(provider = "Bay Area Rapid Transit")
datasets <- mobdb_datasets(bart$id[1], latest = FALSE)
improving <- filter_by_validation(datasets, max_errors = 5, max_warnings = 3000)
} # }