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Duplicate Observations — Record Quality Audit + Equal-Width Histogram
x402
Duplicate Observations — Record Quality Audit + Equal-Width Histogram is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-18).
Runs two local analytical reports on duplicate-observation data: a record quality audit and an equal-width histogram over up to 200 supplied rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Duplicate observations — Record quality audit + Equal-width histogram: Record quality audit + Equal-width histogram 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
Two independent analytical reports: (1) a record quality audit summarizing completeness, validity, and anomalies across the supplied duplicate-observation rows, and (2) an equal-width histogram bucketing the chosen field (duplicate_rows or total_rows) into the specified number of bins with counts per bin. Both reports are computed locally from the supplied data with no external lookups.
Example use cases
Daily deduplication pipeline quality check
“I need a record quality audit and histogram for yesterday's deduplication run — here are 6 rows across two dataset groups with their duplicate_rows and total_rows counts per date, use 10 bins and focus on the duplicate_rows field.”
Monthly data integrity review across groups
“Can you audit these 50 duplicate observation records from last month, split across dataset groups alpha and beta, and generate an equal-width histogram with 8 bins on the total_rows field so I can see the distribution?”
Spot-check new dataset for duplicate anomalies
“I just ingested a new dataset and want to spot-check it for duplicate issues — run a quality audit and 5-bin histogram on these 15 rows of duplicate_rows and total_rows values grouped by region and date.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-04-013?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need two simultaneous analytical reports (quality audit + histogram) on duplicate-observation tabular data without any external API calls, predictions, or live lookups. It is ideal for data engineering pipelines, ETL quality gates, or one-off data integrity checks where you supply the raw duplicate_rows and total_rows metrics and want a quick, cheap ($0.01 USDC) local analysis covering up to 200 rows across multiple dataset groups and dates.
Side effects
- More than 200 rows submitted — request rejected
- Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows) — validation error
- Date field not matching YYYY-MM-DD pattern — schema validation failure
- bins value outside 1–30 range — rejected
- Empty rows array — minimum 1 item required
- Non-numeric values in duplicate_rows or total_rows where numbers are expected — type error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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