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Time Series Completeness — Numeric Distribution + Equal-Width Histogram
x402
Time Series Completeness — Numeric Distribution + 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).
Generates a numeric distribution report and equal-width histogram for time series completeness data (observed_points vs expected_points) across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Numeric distribution + Equal-width histogram: Numeric distribution + Equal-width histogram for supplied time series completeness records (observed_points, expected_points). 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 sharing local engines: (1) a numeric distribution summary of the selected field (observed_points or expected_points) across the supplied rows, and (2) an equal-width histogram dividing values into the specified number of bins (1–30, default 5), showing frequency counts per bin. Input is limited to 200 rows per call.
Example use cases
Data pipeline completeness audit
“I have 120 rows of daily time series completeness data with observed_points and expected_points for two dataset groups. Can you generate a numeric distribution report and a 10-bin histogram on observed_points so I can see how my data coverage is distributed?”
Expected coverage gap profiling
“Run a histogram analysis on the expected_points field across my 80 completeness records — use 5 equal-width bins — so I can understand the shape of my expected coverage targets over this date range.”
Sensor reading completeness check
“I've got 150 rows of sensor time series completeness entries with dates from 2024-01-01 to 2024-05-30. Generate a numeric distribution and equal-width histogram with 8 bins for the observed_points column so I can spot where data gaps are concentrated.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-079?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, local (no external lookup) numeric distribution profiling and equal-width histogram bucketing for time series completeness records specifically structured with observed_points and expected_points fields. It is ideal when you want two reports (distribution + histogram) in a single $0.01 call for up to 200 rows. Prefer it over generic statistics APIs when your data is already in row-based completeness format and you want deterministic, offline-style analytics without any prediction, enrichment, or external data dependency.
Side effects
- More than 200 rows submitted — request rejected
- bins value outside 1–30 range — validation error
- Missing required row fields (row_id, date, observed_points, expected_points) — schema error
- Date strings not matching YYYY-MM-DD pattern — validation error
- All null values in selected field — distribution/histogram may be empty or error
- Invalid field enum value (not observed_points or expected_points) — schema error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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