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Time Series Completeness — Daily Sum Series + Equal-Width Histogram
x402
Time Series Completeness — Daily Sum Series + 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).
Analyzes time series completeness records by producing a daily sum series and an equal-width histogram for observed_points or expected_points, using local analytical engines on up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Daily sum series + Equal-width histogram: Daily sum series + 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: (1) a daily sum series aggregating the selected field (observed_points or expected_points) by date, and (2) an equal-width histogram with the specified number of bins showing the frequency distribution of values across the dataset. Both reports are computed locally on the supplied rows without external lookups.
Example use cases
Daily completeness rollup for sensor pipeline
“I have daily records for my IoT sensor pipeline with observed_points and expected_points from 2024-01-01 to 2024-03-31 — give me a daily sum series and a 5-bin histogram for observed_points so I can see where coverage drops off.”
Histogram of expected data point distribution
“Can you run a 15-bin equal-width histogram on the expected_points field across my 120 time series completeness records? I want to understand how spread out our expected volume is day-to-day.”
Audit completeness gaps across dataset groups
“I've got completeness logs for two dataset groups — group-a and group-b — with dates and observed vs expected point counts. Generate the daily sum series and a 8-bin histogram for observed_points so I can audit where each group falls short.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-139?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a time-aggregated daily sum series and a frequency distribution histogram from completeness records in a single call. It is ideal for data quality monitoring workflows where you want to assess both temporal trends and value spread of observed or expected data point counts. Prefer it over single-report alternatives when you need two complementary analytical views at once for up to 200 rows of completeness data.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, date, observed_points, expected_points) causes rejection
- Invalid date format (non-YYYY-MM-DD) fails schema validation
- Bin count outside 1–30 range is rejected
- Null values in the selected field may be excluded or cause partial results
- Values outside the allowed numeric range (-1e12 to 1e12) will be rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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