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Data Ingestion Batches — Trailing Mean Series + IQR Outlier Flags
x402
Data Ingestion Batches — Trailing Mean Series + IQR Outlier Flags is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-21).
Computes trailing mean time series and IQR-based outlier flags for received_rows and accepted_rows fields in data ingestion batch records (up to 200 rows, 2 reports per call).
Price / call$0.01
Success—
StatusUnknown
How this service works
Data ingestion batches — Trailing mean series + IQR outlier flags: Trailing mean series + IQR outlier flags for supplied data ingestion batches records (received_rows, accepted_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 analytical reports: (1) a trailing mean time series computed over the specified window for the chosen field (received_rows or accepted_rows), and (2) per-row IQR-based outlier flags indicating which records fall outside the interquartile range. Both reports are derived entirely from the supplied data with no external lookups.
Example use cases
ETL pipeline anomaly detection
“I have 90 days of daily ingestion batch logs with received_rows and accepted_rows per dataset group — can you compute a 7-day trailing mean and flag IQR outliers on the received_rows field so I can spot problematic ingestion days?”
Data acceptance rate quality monitoring
“Here are 60 records of our nightly ingestion batches. Run trailing mean smoothing with a window of 5 and flag any IQR outliers on the accepted_rows field — I want to see which nights had statistically unusual acceptance counts.”
Multi-group ingestion trend analysis
“I've got batch ingestion data across two dataset groups over the past 200 days. Can you compute the trailing mean series and IQR outlier flags for received_rows using a window of 14, so I can compare trend stability between the groups?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-01-149?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a rolling/trailing mean trend and IQR outlier detection on ingestion batch metrics (received_rows or accepted_rows) in a single call, without any external data dependencies. It is purpose-built for data engineering and ETL quality use cases and provides two statistical reports per call at minimal cost, making it ideal for lightweight batch anomaly detection pipelines that operate on self-contained historical records.
Side effects
- Fewer than 1 row supplied — minimum 1 row required
- More than 200 rows supplied — batch size limit exceeded
- Missing required fields (row_id, dataset_group, date, received_rows, accepted_rows) on any row
- Date values not matching YYYY-MM-DD format — pattern validation failure
- Window size outside 2–200 range — parameter validation error
- All numeric values null — insufficient data for statistical computation
- Payment not included or insufficient — x402 payment required at $0.01 USDC
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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