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Dataset Storage Trailing Mean Series + IQR Outlier Flags
x402
Dataset Storage 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 2026-10-15).
Computes trailing moving-average series and IQR-based outlier flags for dataset storage metrics (used_mb, row_count) across up to 200 supplied records.
Price / call$0.01
Success—
StatusUnknown
How this service works
Dataset storage — Trailing mean series + IQR outlier flags: Trailing mean 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
Returns two analytical reports: (1) a trailing mean series for the selected field (used_mb or row_count) computed over the specified rolling window, and (2) IQR-based outlier flags indicating which rows fall outside the interquartile range — all derived locally from the supplied data with no external lookups.
Example use cases
Detect storage spikes in data pipeline
“I have 50 daily storage snapshots for my ETL pipeline partitions — can you compute the trailing mean with a window of 5 for used_mb and flag any IQR outliers so I can see which days had abnormal disk usage?”
Monitor row count anomalies by group
“Here are 120 dataset storage records grouped by team, each with a date and row_count. Run a trailing mean with window 7 on row_count and flag anything that looks like an outlier using IQR — I want to catch any unexpected data drops or surges.”
Audit storage growth before capacity review
“Before our capacity planning meeting, can you take these 80 monthly dataset records and calculate the 4-period trailing mean for used_mb along with IQR outlier flags? I need to spot any months where storage ballooned unexpectedly.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-18-149?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a smoothed time-series view (trailing mean) and statistical anomaly detection (IQR outlier flags) on dataset storage metrics in a single call. It is ideal for monitoring storage growth trends and detecting usage spikes in pre-collected dataset records without requiring any external data sources or live database connections.
Side effects
- Fewer than 2 rows supplied — minimum input not met
- window parameter exceeds number of rows — trailing mean cannot be computed
- Invalid date format not matching YYYY-MM-DD pattern
- More than 200 rows submitted — exceeds maximum item limit
- Non-numeric or null values in selected field may reduce outlier detection accuracy
- Payment not completed — x402 payment required before response is returned
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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