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Join Coverage Duplicate Key Report and Missing Value Fill
x402
Join Coverage Duplicate Key Report and Missing Value Fill is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).
Analyzes join coverage records to identify duplicate keys and fill missing values in matched_rows or source_rows fields using zero, mean, or median imputation.
Price / call$0.01
Success—
StatusUnknown
How this service works
Join coverage — Duplicate key report + Explicit missing-value fill: Duplicate key report + Explicit missing-value fill for supplied join coverage records (matched_rows, source_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 independent reports: (1) a duplicate key report identifying any row_id values that appear more than once across the submitted records, and (2) a missing value fill report showing the original and imputed values for the target field (matched_rows or source_rows) using the chosen method (zero, mean, or median). Both reports are computed locally against the supplied data with no external lookups.
Example use cases
ETL pipeline data quality audit
“I just ran a join between my transactions and customers tables and got back 120 coverage rows — can you check them for duplicate row IDs and fill any missing source_rows values using the median? Here are the rows with row_id, date, dataset_group, matched_rows, and source_rows fields.”
Missing value imputation for reporting
“I have about 80 join coverage records across two dataset groups and some of the matched_rows values are null — can you fill those nulls using the mean and also flag any duplicate keys in the same pass?”
Data validation before downstream aggregation
“Before I aggregate my join coverage metrics, can you run a duplicate key check and fill any missing source_rows fields with zero for these 150 rows across group-a and group-b?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-09-070?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a combined duplicate-key detection and missing-value imputation pass over join coverage data (matched_rows, source_rows) in a single cheap call. Best suited for small-to-medium datasets up to 200 rows where both data quality reports are needed simultaneously. Prefer this over general-purpose analytics when your data specifically follows the join coverage schema with dataset_group and date dimensions.
Side effects
- Exceeds 200 row limit — request rejected or truncated
- Invalid date format not matching YYYY-MM-DD pattern — validation error
- missing required fields (row_id, dataset_group, date) — schema validation failure
- numeric values outside allowed range (-1T to 1T) — rejection
- empty rows array — schema minItems violation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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