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Null Coverage Analytics — Trailing Mean Series + Explicit Missing-Value Fill
x402
Null Coverage Analytics — Trailing Mean Series + Explicit Missing-Value Fill is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-14).
Computes a trailing mean time series and fills missing values explicitly for supplied null coverage records (missing_values, total_values), returning 2 analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Null coverage — Trailing mean series + Explicit missing-value fill: Trailing mean series + Explicit missing-value fill for supplied null coverage records (missing_values, total_values). 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 2 analytical reports: a trailing mean time series computed over the specified window for the selected field, and an explicit missing-value fill report that replaces nulls using the chosen method (zero, mean, or median) — all computed locally on the supplied rows without external lookups.
Example use cases
Data quality monitoring dashboard
“I have daily null coverage records for two dataset groups over the past week — can you compute a trailing mean series with a window of 3 and fill any missing values using the mean method on the missing_values field? Here are my rows with row_id, dataset_group, date, missing_values, and total_values.”
Smoothing noisy missing-value counts
“My dataset has 50 rows of null coverage data by date and group, and the missing_values counts are pretty noisy — can you apply a trailing mean with a window of 5 and fill gaps with zero so I can see the smoothed trend?”
Imputing gaps in total_values for reporting
“I'm preparing a data quality report and need to fill in the blanks in my total_values column. Can you run the explicit missing-value fill using median and also give me the trailing mean series with a window of 4 across my 100 rows of null coverage records?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-03-154?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of null coverage records with missing_values and total_values fields and need both a trailing mean time series and explicit missing-value imputation in a single call. Ideal for data quality analytics pipelines where you want local, stateless computation without external data lookups or live predictions. At $0.01 USDC for 2 reports, it is cost-effective for lightweight data quality smoothing and gap-filling tasks.
Side effects
- Fewer than 1 row supplied — request rejected
- More than 200 rows supplied — exceeds limit
- Invalid date format (non-YYYY-MM-DD) — schema validation failure
- Invalid fill method or field enum value — request rejected
- Missing required fields (row_id, dataset_group, date) — schema error
- Window size outside 2–200 range — validation failure
- Payment not included or insufficient — x402 payment required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string | |
| window | integer |
Tags
x402
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