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Feature Availability Analytics: Equal-Width Histogram + Two-Measure Correlation
x402
Feature Availability Analytics: Equal-Width Histogram + Two-Measure Correlation 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).
Computes an equal-width histogram and a two-measure Pearson/linear correlation for supplied feature availability records (populated_features vs expected_features) in a single paid call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Feature availability — Equal-width histogram + Two-measure correlation: Equal-width histogram + Two-measure correlation for supplied feature availability records (populated_features, expected_features). 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) an equal-width histogram over the chosen field (populated_features or expected_features) showing bin edges and counts across up to 30 bins, and (2) a two-measure correlation report quantifying the linear relationship between populated_features and expected_features across the supplied rows — all computed locally from the submitted data, no external lookups.
Example use cases
ML pipeline feature completeness audit
“I have 120 rows of dataset feature records with populated_features and expected_features for each row — can you compute an equal-width histogram with 8 bins on populated_features and also show me the correlation between populated and expected features?”
Daily dataset group comparison
“Analyze my feature availability logs: I've got 80 rows tagged by dataset_group and date, and I want a 5-bin histogram on expected_features plus a two-measure correlation report between populated_features and expected_features.”
Data coverage distribution check
“I need to understand the distribution of how many features are populated vs expected across my 200 dataset records — can you run an equal-width histogram with 10 bins and tell me how strongly the two measures correlate?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-10-171?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a distribution summary (histogram) and a linear relationship check (correlation) on feature availability data in a single low-cost call. Ideal for ML data-quality pipelines, dataset audits, or monitoring jobs where you supply up to 200 rows of populated/expected feature counts and want fast, offline statistical analysis without any external data fetching or prediction.
Side effects
- Rows array is empty or missing — returns validation error
- More than 200 rows submitted — rejected with max-items error
- Non-numeric or null values in both populated_features and expected_features causing degenerate correlation
- bins parameter outside 1–30 range — schema validation failure
- date field not matching YYYY-MM-DD pattern — row rejected
- Insufficient variance in the chosen field leading to a trivial or undefined correlation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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