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Join Coverage Analytics — Numeric Row Ordering + Trailing Mean Series
x402
Join Coverage Analytics — Numeric Row Ordering + Trailing Mean Series 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 numeric row ordering and trailing mean series for join coverage records (matched_rows, source_rows) across up to 200 rows, returning two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Join coverage — Numeric row ordering + Trailing mean series: Numeric row ordering + Trailing mean series 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) a numeric row ordering of the supplied join coverage records ranked by the selected field (matched_rows or source_rows), and (2) a trailing mean series computed over the specified window size for the same field — both derived from the user-supplied data with no external lookups.
Example use cases
ETL pipeline coverage trending
“I have join coverage records from my ETL pipeline for the past week across two dataset groups — can you rank the rows by matched_rows and compute a trailing mean with a window of 3 so I can see which days had the best coverage?”
Data quality audit for source rows
“Run a numeric row ordering and trailing mean analysis on my source_rows join coverage data — I have 8 records across dataset groups 'inventory' and 'orders' from 2026-09-01 to 2026-09-08, window size 2. I want to spot anomalies in how source row counts changed over time.”
Comparing matched vs source row trends
“I want to understand the trend in my matched_rows for join coverage across 'region-east' and 'region-west' groups over 10 daily records in October 2026 — give me both the numeric ranking and the rolling mean with window 4.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-09-115?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both numeric row ranking and a rolling/trailing mean analysis on join coverage metrics (matched_rows or source_rows) in a single low-cost call. Ideal for data engineers auditing ETL pipeline join quality over time, especially when you have up to 200 timestamped records grouped by dataset and want two complementary views — ordering and trend smoothing — without any external data enrichment.
Side effects
- Fewer than 1 row supplied — request rejected
- More than 200 rows supplied — exceeds max item limit
- Window size exceeds number of rows — trailing mean may be undefined for early rows
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Missing required fields (row_id, dataset_group, date) — validation error
- Null values in matched_rows or source_rows — may produce null entries in output series
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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