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Dataset Storage Daily Sum Series and IQR Outlier Flags Analytics
x402
Dataset Storage Daily Sum Series and IQR Outlier Flags Analytics is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Computes daily sum time series and IQR-based outlier flags for dataset storage metrics (used_mb or row_count) from up to 200 supplied records
Price / call$0.01
Success—
StatusUnknown
How this service works
Dataset storage — Daily sum series + IQR outlier flags: Daily sum series + IQR outlier flags for supplied dataset storage records (used_mb, row_count). 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: (1) a daily sum time series showing the total of the selected metric (used_mb or row_count) aggregated per date, and (2) IQR-based outlier flags identifying which records or days fall outside the interquartile range bounds — all computed locally from the supplied data with no external lookups.
Example use cases
Detect storage spikes in ETL pipeline
“I have 120 rows of daily storage logs from our ETL pipeline with used_mb readings across three dataset groups — can you compute the daily total used_mb per day and flag which days are IQR outliers?”
Monitor row count anomalies across groups
“Here are 80 records of dataset storage tracking row_count for groups 'prod' and 'staging' over the past quarter — give me the daily sum series for row_count and highlight any outlier days using IQR.”
Audit historical dataset growth trends
“I'm auditing our data warehouse and need a daily aggregated view of used_mb across all my dataset groups for the past 6 months — 200 rows total — plus IQR outlier flags so I can spot unusual growth days.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-18-140?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have raw dataset storage records (up to 200 rows) with used_mb or row_count fields and need both a daily aggregated time series AND statistical outlier detection in a single low-cost call. Prefer this over general analytics APIs when you want IQR-specific outlier flagging on storage metrics without sending data to a heavyweight analytics platform. Ideal for lightweight, offline-style analysis where you supply the data and get back structured reports instantly.
Side effects
- Fewer than 1 row supplied — request rejected
- More than 200 rows submitted — exceeds limit, request rejected
- Invalid date format not matching YYYY-MM-DD pattern — validation error
- Missing required fields (row_id, dataset_group, date, used_mb, row_count) — schema error
- All values null for the selected field — IQR computation may be undefined
- Invalid field enum value (not 'used_mb' or 'row_count') — rejected
- Payment not included or insufficient — x402 payment required error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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