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Sampling Observations — Record Quality Audit + Equal-Width Histogram
x402
Sampling Observations — Record Quality Audit + Equal-Width Histogram 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).
Runs two local analytical reports on submitted sampling observation records: a data quality audit and an equal-width histogram, for up to 200 rows of sample_value/sample_weight data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Sampling observations — Record quality audit + Equal-width histogram: Record quality audit + Equal-width histogram 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
Two analytical reports delivered together: (1) a record quality audit flagging data completeness, null counts, and validity issues across the submitted rows; and (2) an equal-width histogram showing value distribution of the selected field (sample_value or sample_weight) across the specified number of bins. Both reports are computed locally on the supplied data with no external lookups.
Example use cases
Survey sample data quality check
“I have 150 survey records with sample_value and sample_weight fields and I need to know if there are any data quality issues — missing values, nulls, anomalies. Can you run a quality audit on them using 10 bins on sample_value?”
Distribution histogram for weighted samples
“Can you generate an equal-width histogram with 8 bins for my sample_weight field across 80 sampling observation records? I want to see the distribution before I run my analysis.”
Pre-analysis data profiling for dataset groups
“Before I send this dataset to my model, can you profile it for quality issues and produce a histogram of sample_value with 5 bins? I have about 200 rows tagged with dataset_group labels like 'control' and 'treatment'.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-15-013?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a lightweight, combined data quality audit and histogram report on up to 200 sampling observation records without any live external data lookups or predictions. It is ideal for pre-analysis data profiling, QA pipelines, or validating survey/experimental sample datasets before downstream statistical processing. Prefer this over generic analytics tools when your data specifically has sample_value and sample_weight columns and you want both a quality audit and distribution histogram in a single low-cost call.
Side effects
- More than 200 rows submitted — request rejected at max item limit
- Invalid date format not matching YYYY-MM-DD pattern causes validation error
- Missing required fields (row_id, dataset_group, date, sample_value, sample_weight) cause schema rejection
- bin count outside 1–30 range causes validation error
- Numeric values outside ±1,000,000,000,000 bounds rejected
- Empty rows array (minItems: 1) causes rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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