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Duplicate Observations Analytics: Record Quality Audit + Exact Row Deduplication + Equal-Width Histogram
x402
Duplicate Observations Analytics: Record Quality Audit + Exact Row Deduplication + 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 2026-10-16).
Runs three local analytical reports on duplicate observation data: a record quality audit, exact row deduplication, and an equal-width histogram for a specified numeric field.
Price / call$0.01
Success—
StatusUnknown
How this service works
Duplicate observations — Record quality audit + Exact row deduplication + Equal-width histogram: Record quality audit + Exact row deduplication + Equal-width histogram for supplied duplicate observations records (duplicate_rows, total_rows). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Three independent analytical reports returned for the submitted rows: (1) a record quality audit flagging missing, malformed, or outlier values; (2) an exact row deduplication report identifying and removing identical records; (3) an equal-width histogram with the specified number of bins over the chosen numeric field (duplicate_rows or total_rows), including bin boundaries and counts.
Example use cases
Data pipeline duplicate audit
“I've got a dataset of 50 observation records with row IDs, dates, dataset groups, and duplicate_rows and total_rows counts — can you audit their record quality, remove exact duplicates, and give me a 5-bin histogram over duplicate_rows so I can see the distribution?”
Dataset group deduplication review
“Run a quality audit and exact row deduplication report on my dataset observations; I have rows from groups alpha and beta across October 2026 — I want to see which rows are exact duplicates and a histogram of total_rows across 8 bins.”
Monthly duplicate trend histogram
“I have 200 rows of duplicate observation records for November 2026 across multiple dataset groups — please audit record quality, deduplicate exact rows, and generate a 15-bin histogram on the duplicate_rows field so I can understand the spread.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-04-219?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 tabular duplicate-observation records and need all three analyses — record quality audit, exact deduplication, and a histogram — in a single call at low cost ($0.01 USDC). It is ideal for offline/batch data quality checks on structured datasets without needing live lookups, external APIs, or ML predictions. Prefer alternatives if you need real-time deduplication, fuzzy matching, or more than 200 rows.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, date, dataset_group, duplicate_rows, total_rows) causes row rejection
- Invalid date format (not YYYY-MM-DD) triggers a pattern validation error
- bins value outside 1–30 range returns a schema validation error
- Null values for numeric fields are accepted but may affect histogram binning
- field enum value not 'duplicate_rows' or 'total_rows' causes a validation failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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