Handle Missing Values and Anomalies

Nuna analytics workflows receive care records that may omit required fields or contain invalid numeric measurements. Write a function that returns a cleaned copy of the records and a report describing every missing value or anomaly.

A record is a dictionary. A field is missing when it is absent or its value is None. A numeric field is anomalous when it falls outside its inclusive [minimum, maximum] range. Replace every missing or anomalous field with None, preserve all other fields, and do not mutate the input list or its records.

Formal Specification

Implement clean_records(records, required_fields, bounds):

• records is a list of dictionaries.
• required_fields is a list of field names that every record should contain.
• bounds is a dictionary mapping selected numeric field names to [minimum, maximum] values.
• Return a dictionary with:
  • cleaned: the corrected list of records.
  • issues: a list of dictionaries containing record_index, field, and issue, where issue is either "missing" or "out_of_range".

Process fields in required_fields order and records in input order. For an out-of-range value, report only "out_of_range". Fields not listed in required_fields should remain unchanged.