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Time Series Completeness — Numeric Row Ordering + Trailing Mean Series
x402
Time Series Completeness — Numeric Row Ordering + Trailing Mean Series 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 numeric row ordering and trailing mean series analytics for time series completeness records (observed vs expected data points) over up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Numeric row ordering + Trailing mean series: Numeric row ordering + Trailing mean series 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 analytical engines: (1) a numeric row ordering report ranking the input rows by the selected field, and (2) a trailing mean series showing the rolling average of the selected field over the specified window size — all computed against the supplied time series completeness data without any live lookups or external calls.
Example use cases
IoT sensor data gap detection
“I have daily completeness records for my IoT sensor streams — each row has a date, a sensor group name, how many data points were observed, and how many were expected. Can you run numeric row ordering and a trailing mean with a window of 7 on the observed_points field across my 120 rows so I can spot where coverage is dropping?”
Pipeline monitoring completeness trend
“My data pipeline logs daily observed versus expected event counts for three dataset groups over the past 90 days. Please compute the numeric row ordering and trailing mean series with a window of 10 on expected_points so I can see the smoothed completeness trend for each group.”
Reporting dataset audit completeness
“I need to audit completeness for our reporting datasets — I'll give you 200 rows with dates, group labels, observed and expected point counts. Run both the numeric row ordering and trailing mean series (window size 3) on observed_points and give me the two reports.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-115?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need two complementary analytical views — row ordering and trailing mean — on time series completeness data (observed vs expected points) in a single low-cost call ($0.01 USDC). Ideal for data quality pipelines, monitoring dashboards, or audit workflows where you want to assess completeness trends without external data lookups or predictions.
Side effects
- Input array exceeds 200 rows — request will be rejected
- Missing required fields (row_id, date, observed_points, expected_points) cause validation errors
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- Window size outside 2–200 range is rejected
- Null values in numeric fields may affect trailing mean computation
- Payment of 0.01 USDC not fulfilled — endpoint returns 402 Payment Required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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