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Duplicate Observations Analytics: Trailing Mean Series + Missing-Value Fill
x402
Duplicate Observations Analytics: Trailing Mean Series + 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 2026-10-20).
Computes a trailing mean time series and fills explicit missing values for up to 200 duplicate-observation records, returning two analytical reports per call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Duplicate observations — Trailing mean series + Explicit missing-value fill: Trailing mean series + Explicit missing-value fill for supplied duplicate observations records (duplicate_rows, total_rows). 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
Two analytical reports per call: (1) a trailing mean time series computed over the specified window for the chosen field (duplicate_rows or total_rows), and (2) an explicit missing-value filled series using the selected method (zero, mean, or median). Both reports are derived locally from the supplied rows with no external lookups.
Example use cases
Data quality audit smoothing
“I'm auditing data quality for our pipeline and have 20 daily records across three dataset groups with duplicate_rows and total_rows counts. Can you compute a trailing mean with a window of 5 on the duplicate_rows field and fill any nulls using the mean method so I can see the smoothed trend?”
Missing value imputation for reporting
“Some entries in my duplicate observation log have null values for total_rows. I have 50 rows across two groups dated over the past two months — can you fill those missing values using the median method and also give me the trailing mean series with a window of 7?”
Rolling average for dataset group comparison
“I want to compare duplicate row trends across group-a and group-b over the last quarter. I have 100 daily records — please compute a trailing mean series with window size 4 on the duplicate_rows field and zero-fill any missing entries.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-04-154?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a trailing mean time series and explicit missing-value imputation for duplicate-observation metrics (duplicate_rows, total_rows) in a single call. It is ideal for lightweight, offline data quality analytics on up to 200 rows without needing a full analytics platform. Prefer it over general-purpose statistics APIs when your data is already structured as duplicate observation records with dataset groups and dates, and you need two complementary views — smoothed trend and gap-filled series — delivered together at low cost.
Side effects
- More than 200 rows submitted — exceeds maximum batch size
- Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows) causes validation failure
- Date strings not in YYYY-MM-DD format rejected by pattern validation
- Window size outside range 2–200 returns error
- Invalid enum value for field or method parameter causes schema rejection
- Payment of 0.01 USDC not included or declined results in 402 response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string | |
| window | integer |
Tags
x402
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