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Join Coverage Analytics: Adjacent Row Changes + Equal-Width Histogram
x402
Join Coverage Analytics: Adjacent Row Changes + 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 2026-10-15).
Runs two local statistical reports on join coverage data (matched_rows, source_rows): adjacent row-to-row change analysis and an equal-width histogram, for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Join coverage — Adjacent row changes + Equal-width histogram: Adjacent row changes + Equal-width histogram 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 analytical reports: (1) an adjacent row changes report showing the delta in the chosen field (matched_rows or source_rows) between each consecutive record, and (2) an equal-width histogram dividing the field values into the specified number of bins with frequency counts per bin. All computation is performed locally on the supplied data with no external lookups.
Example use cases
ETL pipeline join quality audit
“I have daily join coverage records for my ETL pipeline — 30 rows with matched_rows and source_rows from January 2024. Can you run the adjacent row changes report and a 5-bin histogram on matched_rows so I can see where coverage drops between days?”
Data distribution check for source rows
“Here are 50 join coverage records grouped by 'warehouse' and 'retail' datasets with source_rows counts — can you compute a 10-bin equal-width histogram on source_rows to see how the values are distributed across ranges?”
Detecting coverage spikes between records
“I need to spot sudden jumps in matched_rows across these 20 consecutive join coverage records from my nightly sync — run the adjacent row changes analysis on matched_rows so I can flag any large deltas between rows.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-09-156?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have structured join coverage records with matched_rows and source_rows values and need both a temporal/sequential change analysis and a frequency distribution in one call. It is ideal for data engineers auditing ETL pipeline join quality, data quality teams monitoring coverage metrics, or analysts who want a quick dual statistical snapshot without setting up local tooling. It is not a live data connector or prediction service — you must supply all rows.
Side effects
- More than 200 rows submitted — request rejected due to maxItems constraint
- Missing required fields (row_id, date, dataset_group, matched_rows, source_rows) on any row — validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Bins parameter out of range (below 1 or above 30) — rejected
- All values null for chosen field — histogram may be empty or degenerate
- Payment of 0.01 USDC not completed — 402 payment required response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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