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name: structured-data description: "Use Presidio Structured for Pandas DataFrames, JSON-like data, structured mappings, processors, selection strategies, and safe CSV/batch recipes." disable-model-invocation: true metadata: disco-role: operating license: MIT

structured-data

Use this sub-skill when Presidio must detect or anonymize PII in structured values rather than one free-text string at a time.

Use this for

• Pandas DataFrame analysis and anonymization with PandasAnalysisBuilder and StructuredEngine.
• JSON-like dictionaries/lists with JsonAnalysisBuilder, manual StructuredAnalysis mappings, and JsonDataProcessor.
• Choosing DataFrame entity selection strategies: most_common, highest_confidence, or mixed.
• Overriding automatically generated field/entity mappings when column semantics are known.
• Reusing anonymizer OperatorConfig maps across structured columns or JSON paths.
• Safe CSV and batch-style recipes for dictionaries of columns or small CSV files.

Route elsewhere

• Free-text analyzer tuning, NLP engines, supported entities, recognizers, score thresholds, allow lists, or model installation → ../analyze-text/SKILL.md.
• Operator semantics, encryption/decryption, overlap/conflict behavior, custom operators, and detailed anonymizer errors → ../anonymize-text/SKILL.md.
• CLI scans over files/directories/stdin and CLI YAML config precedence → ../cli-scans/SKILL.md.
• Image, OCR, DICOM, or bounding-box redaction → ../image-redaction/SKILL.md.

Core workflow choices

1. Identify the data shape: Pandas DataFrame, JSON-like object, or CSV/batch dictionary.
2. Generate or provide a StructuredAnalysis(entity_mapping={field_or_path: entity_type}).
3. Pick the processor: default PandasDataProcessor for DataFrames, JsonDataProcessor for JSON-like objects.
4. Build an anonymizer operator map with entity-specific entries plus a safe DEFAULT fallback.
5. Run StructuredEngine.anonymize(...), then validate that the expected columns/paths changed and non-PII fields stayed stable.

Read next

• references/api-reference.md for imports, signatures, object behavior, defaults, and mutation notes.
• references/data-formats.md for DataFrame, JSON path, nested-list, CSV, and manual mapping formats.
• references/workflows.md for DataFrame, JSON, mapping override, operator reuse, and CSV/batch recipes.
• references/troubleshooting.md for processor mismatches, nested arrays, wrong mappings, selection strategy issues, pandas/model requirements, and operator fallback problems.

Safe bundled checks

• python scripts/structured_smoke.py --help
• python scripts/structured_smoke.py
• python scripts/presidio_csv_batch_smoke.py --help
• python scripts/presidio_csv_batch_smoke.py

The bundled scripts build tiny fixtures in memory or a temporary directory, use a no-download analyzer configuration, and do not assume access to this repository checkout.