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Null Coverage Daily Sum Series with IQR Outlier Flags
x402
Null Coverage Daily Sum Series with 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 2026-10-14).
Computes a daily sum time series and IQR-based outlier flags for null coverage data (missing_values and total_values) supplied by the caller, returning two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Null coverage — Daily sum series + IQR outlier flags: Daily sum series + IQR outlier flags for supplied null coverage records (missing_values, total_values). 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 daily sum time series aggregating the selected field (missing_values or total_values) by date, and (2) IQR-based outlier flags identifying rows or dates whose values fall outside the interquartile range. Both reports are computed locally from the supplied data with no external lookups.
Example use cases
Data pipeline quality audit
“I have daily null coverage logs for two dataset groups across October — here are 50 rows with row_id, date, dataset_group, missing_values, and total_values. Can you compute a daily sum series and flag any IQR outliers on the missing_values field so I can spot problem days?”
Total values anomaly detection
“I want to check if any dates in my dataset have an abnormally high or low total_values count — I have 120 records with dates and group labels. Run the daily sum series and IQR outlier flags on total_values and give me both reports.”
Data completeness trend monitoring
“We track null coverage across several dataset groups daily and I need to know which dates stand out as outliers. Can you take these 80 rows of missing_values and total_values records and produce a daily sum series plus IQR outlier flags for the missing_values field?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-03-140?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have batch null coverage records (up to 200 rows) and need both a daily aggregated sum series and IQR-based statistical outlier flags in a single paid call. Ideal for data quality workflows where you supply your own completeness metrics and want purely local, deterministic analytical output without any external data enrichment or prediction. Prefer alternatives if you need more than 200 rows, real-time streaming analysis, or more than two report types per call.
Side effects
- Fewer than 1 row provided — minimum 1 row required
- More than 200 rows submitted — hard cap enforced
- Missing required fields (row_id, date, dataset_group, missing_values, total_values) cause validation errors
- Malformed date strings not matching YYYY-MM-DD pattern rejected
- Numeric values outside the allowed range (-1T to +1T) rejected
- Invalid field selector (must be 'missing_values' or 'total_values')
- Insufficient variance in data may yield trivial or degenerate IQR results
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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