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Numeric Precision Comparisons — Equal-Width Histogram + IQR Outlier Flags
x402
Numeric Precision Comparisons — Equal-Width Histogram + 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).
Generates equal-width histogram distributions and IQR-based outlier flags for numeric precision comparison records (source_value vs transformed_value) across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Numeric precision comparisons — Equal-width histogram + IQR outlier flags: Equal-width histogram + IQR outlier flags for supplied numeric precision comparisons records (source_value, transformed_value). 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 for the submitted numeric comparison records: (1) an equal-width histogram showing bin ranges and row counts across the selected field (source_value or transformed_value), and (2) IQR-based outlier flags identifying which rows fall outside the interquartile range boundaries. Both reports are computed locally with no external lookups.
Example use cases
ETL pipeline transformation audit
“I have 120 rows from my ETL pipeline with original source_value and post-transformation transformed_value. Can you run a histogram with 8 bins and flag any IQR outliers on the source_value field so I can see where the distribution is skewed?”
Data quality check after normalization
“After running our normalization step, I want to check if the transformed_value column has any statistical outliers. Here are 80 rows with row_id, dataset_group, date, source_value, and transformed_value — run 5 bins and IQR outlier detection on transformed_value.”
Precision loss detection across dataset groups
“We suspect some rows in group-b have precision issues after our decimal rounding step. Can you analyze these 200 records — with row_id, date, dataset_group, source_value and transformed_value — using a 15-bin histogram and IQR outlier flags on source_value to find where the anomalies are?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-20-170?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, local statistical analysis of numeric precision comparison pairs (source vs transformed values) without any external data lookups or model inference. It is ideal for data engineers auditing ETL pipelines, validating transformation correctness, or detecting outliers in batch numeric records. Prefer it over general-purpose statistical tools when you need both a histogram and IQR outlier flags delivered together in a single lightweight call for up to 200 rows at minimal cost.
Side effects
- More than 200 rows submitted — request rejected due to maxItems limit
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- Missing required fields (row_id, dataset_group, date, source_value, transformed_value) causes rejection
- bins value outside 1–30 range causes validation error
- Numeric values outside ±1,000,000,000,000 range rejected
- All null source_value or transformed_value entries may produce degenerate histogram output
- Payment of 0.01 USDC not included or rejected causes 402 response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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