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Aggregation Checks — IQR Outlier Flags + Secondary-Measure Weighted Mean
x402
Aggregation Checks — IQR Outlier Flags + Secondary-Measure Weighted Mean 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).
Performs IQR-based outlier detection and secondary-measure weighted mean analysis on up to 200 aggregation check records with source_sum and aggregate_sum fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Aggregation checks — IQR outlier flags + Secondary-measure weighted mean: IQR outlier flags + Secondary-measure weighted mean for supplied aggregation checks records (source_sum, aggregate_sum). 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: (1) IQR outlier flags identifying which rows have source_sum or aggregate_sum values outside the interquartile range, and (2) a secondary-measure weighted mean computed across the supplied rows — both derived from the submitted data using local analytical engines, with no external lookups.
Example use cases
Flagging outliers in financial reconciliation data
“I have 80 rows of daily reconciliation data with source_sum and aggregate_sum values across two groups. Can you run IQR outlier flagging plus a weighted mean report on the source_sum field to see which rows are anomalous?”
QA check on ETL aggregation pipeline output
“We just ran our ETL pipeline and I have 150 rows of aggregation check results by dataset_group and date. Please run IQR outlier flags and a secondary-measure weighted mean on the aggregate_sum field so I can spot anything suspicious before sign-off.”
Statistical summary of multi-group dataset aggregates
“I've got 40 aggregation check records across three groups with source_sum and aggregate_sum columns. Can you give me both an IQR outlier report and a weighted mean breakdown on source_sum?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-17-177?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both IQR-based outlier flagging AND a weighted mean in a single paid call for aggregation check data (source_sum/aggregate_sum pairs), especially when your dataset is up to 200 rows and you want two reports for $0.01 USDC without any external lookups or live data dependencies.
Side effects
- Fewer than 1 row submitted — validation error
- More than 200 rows submitted — exceeds max item limit
- Missing required fields (row_id, dataset_group, date, source_sum, or aggregate_sum) — schema validation failure
- Invalid date format (not YYYY-MM-DD) — pattern validation error
- Numeric values outside ±1,000,000,000,000 range — schema validation failure
- Invalid field enum value — must be 'source_sum' or 'aggregate_sum'
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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