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Dataset Partition Sizes — Daily Sum Series + Explicit Missing-Value Fill
x402
Dataset Partition Sizes — Daily Sum 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 daily sum time series and fills missing values for dataset partition size metrics (row_count or file_mb) across groups, returning two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Dataset partition sizes — Daily sum series + Explicit missing-value fill: Daily sum 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: (1) a daily sum time series aggregating the chosen metric (row_count or file_mb) by date across dataset groups, and (2) an explicit missing-value-filled version of the series using the specified fill method (zero, mean, or median). No external data fetched; analysis is performed on the supplied rows only.
Example use cases
Daily partition growth monitoring
“I have daily partition size records for my data lake with row counts and file sizes — can you compute the daily total row_count per day and fill any missing dates using median fill? Here are the records for the past 30 days across groups 'raw' and 'processed'.”
File size trend analysis with gap filling
“Can you run a daily sum series on the file_mb field for my dataset partitions and fill any missing values with zero? I'll give you about 120 rows across two dataset groups spanning September and October 2026.”
Data pipeline audit report generation
“I need two reports on my partition size data — a daily sum series and explicit missing-value fill — for the row_count metric, using mean imputation for gaps. The dataset has 80 rows across groups 'bronze', 'silver', and 'gold' from Q3 2026.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-07-145?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a daily sum aggregation and missing-value imputation for dataset partition size metrics (row_count or file_mb) in a single low-cost call. It is ideal for data engineering and pipeline monitoring use cases where you supply your own records (no external lookup) and need two complementary analytical views — aggregated totals and gap-filled series — on time-series partition data of up to 200 rows.
Side effects
- Input array is empty or exceeds 200 rows — rejected with validation error
- Invalid date format (not YYYY-MM-DD) in any row — schema validation failure
- Unknown fill method or field enum value — rejected at schema level
- All values for selected field are null — fill may produce degenerate or all-zero results
- Missing required row fields (row_id, dataset_group, date) — schema validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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