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Duplicate Observations — String Normalisation + Numeric Interval Filter
x402
Duplicate Observations — String Normalisation + Numeric Interval Filter is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Normalises dataset_group strings and filters duplicate_rows/total_rows values by a numeric interval for up to 200 duplicate-observation records, returning two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Duplicate observations — String normalisation + Numeric interval filter: String normalisation + Numeric interval filter for supplied duplicate observations records (duplicate_rows, total_rows). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Returns two analytical reports for the supplied duplicate-observation rows: (1) a string-normalisation report standardising dataset_group values, and (2) a numeric interval filter report identifying which rows have the specified field (duplicate_rows or total_rows) falling within the given minimum–maximum range. No external data is fetched; all analysis is performed on the supplied records.
Example use cases
Data quality audit for ETL pipeline
“I'm auditing our ETL pipeline and have 120 rows of duplicate observation data with messy dataset_group labels like 'Sales', 'sales ', and 'SALES'. Can you normalise those strings and filter the duplicate_rows field to only show records between 0 and 100?”
Filtering out-of-range deduplication metrics
“We track duplicate_rows and total_rows for 80 datasets every day. Can you run the numeric interval filter on total_rows, keeping only records where total_rows falls between 500 and 10000, and also normalise the dataset_group names across all rows?”
Monthly duplicate trend review by group
“I have 150 duplicate observation records from October grouped by department names that have inconsistent capitalisation. Please normalise the dataset_group strings and filter duplicate_rows between 10 and 75 so I can see which groups are in a healthy range.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-04-026?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to simultaneously normalise inconsistent string labels in a dataset_group column AND filter numeric duplicate-observation metrics (duplicate_rows or total_rows) by a numeric interval, all on supplied data without any external lookups. It is purpose-built for data quality workflows involving duplicate row auditing across named dataset groups, and delivers two complementary reports for a single low-cost call.
Side effects
- Fewer than 1 row supplied — request rejected
- More than 200 rows supplied — exceeds maximum batch size
- Invalid date format (not YYYY-MM-DD) — schema validation error
- minimum greater than maximum — may yield empty interval filter results
- null values in duplicate_rows or total_rows — rows may be excluded from numeric filter
- row_id missing or empty — required field validation failure
- field enum value not 'duplicate_rows' or 'total_rows' — rejected by schema
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| maximum | number | |
| minimum | number |
Tags
x402
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