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Join Coverage — Daily Sum Series + Explicit Missing-Value Fill
x402
Join Coverage — Daily Sum Series + Explicit 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).
Computes a daily sum time series for join coverage metrics (matched_rows, source_rows) and fills missing values using zero, mean, or median imputation, returning two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Join coverage — Daily sum series + Explicit missing-value fill: Daily sum series + 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
Two analytical reports covering: (1) a daily sum time series for the selected field (matched_rows or source_rows) aggregated across the supplied rows, and (2) an explicit missing-value fill report showing imputed values using the chosen method (zero, mean, or median). Results are based solely on the supplied data with no external lookups.
Example use cases
ETL pipeline join coverage audit
“I have daily join coverage records for two dataset groups across October 2026, about 60 rows. Can you compute the daily sums of matched_rows for each day and fill any missing dates using median imputation so I can see where my join rates dropped?”
Source row gap detection for data warehouse
“I need a daily sum series for source_rows in my warehouse join logs — I've got about 150 rows across multiple dataset groups. Please fill any missing-value gaps with zero so I can spot days where no source data arrived.”
Data quality report on join match trends
“Can you summarize my join coverage dataset by aggregating matched_rows into a daily sum series, using mean fill for any gaps? I have records tagged under group-a and group-b covering about 90 days and want two analytical reports out of it.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-09-145?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to aggregate daily sum totals and impute missing values for join coverage metrics (matched_rows, source_rows) from supplied tabular data, without requiring external data sources or live lookups. It is ideal for data engineering and ETL audit workflows where you have up to 200 pre-collected join coverage records grouped by date and dataset group, and need two structured analytical reports from a single low-cost call.
Side effects
- More than 200 rows submitted — request rejected due to maxItems constraint
- Missing required fields (row_id, date, dataset_group) on any row — validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Invalid field or method enum value — schema validation failure
- Empty rows array — minItems constraint violation
- Numeric values outside allowed range (±1,000,000,000,000) — schema rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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