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Record Routing Analytics: Numeric Interval Filter + Trailing Mean Series
x402
Record Routing Analytics: Numeric Interval Filter + 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 2026-10-23).
Applies a numeric interval filter and computes a trailing mean time series on accepted_records or rejected_records fields from supplied record routing data, returning two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Record routing — Numeric interval filter + Trailing mean series: Numeric interval filter + Trailing mean series for supplied record routing records (accepted_records, rejected_records). 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 analytical reports: (1) a filtered list of rows where the chosen field (accepted_records or rejected_records) falls within the specified minimum–maximum interval, and (2) a trailing mean time series computed over the chosen field using the specified window size. Both reports are derived purely from the supplied data, with no external lookups or predictions.
Example use cases
ETL pipeline rejection spike detection
“I have 30 days of ETL record routing data and want to filter rows where rejected_records fall between 5 and 100, then see a trailing mean over a window of 7 so I can spot unusual rejection spikes — can you run both reports on my dataset?”
Accepted records trend analysis by group
“Run an interval filter keeping only rows where accepted_records are between 10 and 1000, and compute a trailing mean with window size 3 on accepted_records across these dataset groups: group-a had 15 accepted on Oct 1, group-b had 80 on Oct 2, group-a had 500 on Oct 3.”
Data quality threshold monitoring
“I want to check which of my record routing rows fall within an acceptable range of 0 to 200 for rejected_records, and also see the trailing rolling average with a window of 4 — here are my 10 rows with dates and group names.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-19-126?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of time-stamped record routing data with accepted_records and rejected_records fields and need both a numeric range filter and a rolling mean analysis in a single low-cost call. It is ideal for lightweight ETL monitoring, data quality checks, or pipeline analytics where no external data lookup or prediction is required. It is not suitable for real-time streaming, datasets exceeding 200 rows, or analyses requiring external data enrichment.
Side effects
- Fewer than 1 row supplied returns an error
- More than 200 rows submitted exceeds the row limit
- Window size larger than the number of rows may produce sparse or empty trailing mean output
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- Minimum value greater than maximum value may return an empty filtered set
- Null values in the target field may be excluded from interval filtering and mean calculation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer | |
| maximum | number | |
| minimum | number |
Tags
x402
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