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Sampling Observations — Equal-Width Histogram + IQR Outlier Flags
x402
Sampling Observations — 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).
Computes an equal-width histogram and IQR-based outlier flags for up to 200 sampling observation records (sample_value or sample_weight).
Price / call$0.01
Success—
StatusUnknown
How this service works
Sampling observations — Equal-width histogram + IQR outlier flags: Equal-width histogram + IQR outlier flags for supplied sampling observations records (sample_value, sample_weight). 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) an equal-width histogram partitioning the chosen field (sample_value or sample_weight) into the specified number of bins with counts per bin, and (2) IQR-based outlier flags identifying which rows contain values outside the interquartile fence. Both reports are computed locally from the supplied data with no external lookups.
Example use cases
Environmental sampling outlier detection
“I have 80 soil contamination readings from different sites dated this quarter — can you bin the sample_value field into 10 equal-width buckets and flag any IQR outliers so I know which sites need follow-up?”
Survey response weight distribution check
“Here are 150 survey responses with sample_weight values — run a histogram with 8 bins on the sample_weight field and tell me which records are statistical outliers by IQR.”
QC check on lab measurement batch
“I need to QA this batch of 60 lab measurements before reporting — bin the sample_value into 5 equal-width intervals and flag any rows that fall outside the IQR bounds so I can review them.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-15-170?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 tabular sampling observation records and need both a distributional summary (histogram) and anomaly identification (IQR outlier flags) in a single $0.01 call. It is ideal for lightweight, offline statistical QA of numeric measurement or weight data without needing an external data science platform. Prefer it over general analytics APIs when your data fits the specific sample_value/sample_weight schema and you want deterministic, reproducible results with no external data transmission beyond your supplied rows.
Side effects
- More than 200 rows submitted — request rejected due to maxItems limit
- Invalid date format (not YYYY-MM-DD) causes row validation failure
- sample_value or sample_weight outside ±1,000,000,000,000 range causes schema rejection
- bins parameter exceeds 30 or is less than 1 — validation error
- Missing required fields (row_id, date, dataset_group) causes row rejection
- All values are identical — histogram bins may be degenerate, IQR may be zero
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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