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Aggregation Checks — Two-Measure Correlation + Explicit Missing-Value Fill
x402
Aggregation Checks — Two-Measure Correlation + Explicit Missing-Value Fill is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-23).
Computes Pearson correlation between source_sum and aggregate_sum columns and fills missing values in a chosen field using zero, mean, or median imputation, across up to 200 aggregation check rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Aggregation checks — Two-measure correlation + Explicit missing-value fill: Two-measure correlation + Explicit missing-value fill 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 analytical reports: (1) a Pearson correlation result quantifying the linear relationship between source_sum and aggregate_sum across all supplied rows, and (2) a missing-value fill report showing which rows had null values in the specified field and what values were substituted using the chosen method (zero, mean, or median). No external data is fetched; all analysis is performed on the supplied rows only.
Example use cases
Reconciling source vs aggregate financial sums
“I've got a table of daily reconciliation records — each row has a row_id, group, date, source_sum, and aggregate_sum — can you calculate the correlation between the two sum columns and fill any nulls in aggregate_sum using the mean?”
Imputing missing values in pipeline aggregation data
“My partnership pipeline export has up to 150 rows with source_sum and aggregate_sum fields but some values are null — please fill the missing source_sum values using median and also tell me how correlated source_sum and aggregate_sum are.”
Data quality check on grouped aggregation records
“Before I send this batch of aggregation check records to our reporting system, can you run a correlation check between source_sum and aggregate_sum and zero-fill any missing aggregate_sum entries? There are about 80 rows grouped by dataset_group and dated from last month.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-17-184?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular aggregation check data with source_sum and aggregate_sum columns and need both a statistical correlation measure between those two fields and a missing-value imputation pass in a single API call. It is best suited for data reconciliation workflows, financial auditing, and pipeline QA where you want offline, local analytical computation (no external lookups) on up to 200 rows at low cost. Prefer alternatives if you need more than 2 analytical reports, more than 200 rows, live data enrichment, or a different pair of columns.
Side effects
- Fewer than 1 row submitted — request rejected
- More than 200 rows submitted — exceeds row limit
- Invalid date format (not YYYY-MM-DD) — schema validation error
- Both source_sum and aggregate_sum are null for most rows — correlation undefined or NaN
- Field enum value not one of source_sum or aggregate_sum — validation error
- Method enum not one of zero, mean, median — validation error
- row_id missing or empty string — required field error
- Insufficient non-null pairs for correlation — may return NaN or undefined correlation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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