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Feature Availability Analytics — Grouped Numeric Summary + Trailing Mean Series
x402
Feature Availability Analytics — Grouped Numeric Summary + 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 2026-10-19).
Computes a grouped numeric summary and a trailing mean time series for feature availability records (populated_features, expected_features) from up to 200 supplied rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Feature availability — Grouped numeric summary + Trailing mean series: Grouped numeric summary + Trailing mean series for supplied feature availability records (populated_features, expected_features). 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 sharing the same input data: (1) a grouped numeric summary breaking down populated_features and/or expected_features statistics by dataset_group, and (2) a trailing mean time series over the specified window size for the chosen field — all computed locally from the supplied rows with no external lookups.
Example use cases
ML feature coverage trend analysis
“I'm tracking feature availability across my ML datasets. Here are 50 daily records with populated_features and expected_features for groups 'model-a' and 'model-b' — can you compute a grouped numeric summary and a 7-day trailing mean for the populated_features field?”
Data pipeline quality monitoring
“We have daily logs of how many features actually populated vs how many were expected across our ingestion pipelines. Can you group these 120 rows by dataset_group and compute a trailing mean over a window of 5 to spot degrading fill rates?”
Feature store completeness reporting
“I need a report on feature store completeness — here are 200 rows with populated_features and expected_features across four groups and the last three months. Please give me the grouped numeric summary and trailing mean series using a window of 10 for the expected_features field.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-10-090?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 feature availability records with populated_features and expected_features values and need both a group-level numeric summary and a trailing mean time series in a single low-cost call ($0.01 USDC). It is ideal for data quality monitoring, ML feature store audits, and pipeline health checks where you supply your own data and need offline analytical computation without any external data lookups or predictions.
Side effects
- Fewer than 1 row supplied — minimum item count not met
- More than 200 rows supplied — exceeds maxItems limit
- Invalid date format (must match YYYY-MM-DD pattern)
- Missing required fields (row_id, dataset_group, date, populated_features, expected_features)
- Window value outside allowed range of 2–200
- Field value not one of the allowed enum values: populated_features, expected_features
- Null numeric values in all rows may produce degenerate statistics
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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