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Dataset Partition Sizes — Trailing Mean Series + Explicit Missing-Value Fill
x402
Dataset Partition Sizes — 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 2026-10-19).
Computes a trailing mean time series and fills missing values for dataset partition size records (row_count or file_mb) over up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Dataset partition sizes — Trailing mean series + Explicit missing-value fill: Trailing mean series + Explicit missing-value fill for supplied dataset partition sizes records (row_count, file_mb). 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 independent analytical reports covering: (1) a trailing mean time series computed over the specified window for the chosen field (row_count or file_mb), and (2) an explicit missing-value fill for the same field using the specified method (zero, mean, or median). Results are derived entirely from the supplied rows with no external lookups.
Example use cases
Smoothing row counts for data pipeline monitoring
“I have daily partition records for my data pipeline with row counts and some nulls — can you run a trailing mean with a window of 5 and fill the missing row_count values using the mean method?”
Detecting file size growth trends across dataset groups
“Can you compute a 4-period trailing mean on file_mb for my dataset partitions and fill any gaps with zero so I can spot storage growth trends over the last few months?”
Preparing cleaned metrics for a data quality report
“I need to clean up my partition size data before building a quality report — please fill missing row_count values using median and give me the trailing mean series with a window of 2.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-07-154?utm_source=zero.xyzWhen to prefer
Use this endpoint when you have up to 200 dataset partition size records (row counts or file sizes in MB) and need both a trailing moving average series and explicit null/missing-value imputation in a single call, without any external data fetching, prediction, or professional assessment. Ideal for data engineers or analysts who want lightweight, deterministic time-series smoothing and gap-filling on partition metrics.
Side effects
- Fewer than 1 row or more than 200 rows submitted — request rejected
- Invalid date format (not YYYY-MM-DD) — validation error
- Window size outside 2–200 range — validation error
- All values null for the chosen field — fill/mean computation may be undefined
- Field value outside allowed numeric range — validation error
- Missing required row properties (row_id, dataset_group, date) — validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string | |
| window | integer |
Tags
x402
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