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Transformation Throughput Analytics: Trailing Mean Series + Date-by-Category Pivot
x402
Transformation Throughput Analytics: Trailing Mean Series + Date-by-Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-28).
Computes a trailing mean time-series and a date-by-category pivot table for transformation throughput records (processed_rows, duration_seconds) over up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Transformation throughput — Trailing mean series + Date by category pivot: Trailing mean series + Date by category pivot for supplied transformation throughput records (processed_rows, duration_seconds). 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: (1) a trailing mean time-series for the selected field (processed_rows or duration_seconds) computed with the specified window size, and (2) a pivot table cross-tabulating dates against dataset_group categories with aggregated values — both derived purely from the supplied rows with no external data.
Example use cases
ETL pipeline throughput trend smoothing
“I have daily ETL job logs with processed_rows counts across two groups — group-a and group-b — for the past week. Can you run a trailing mean series with window size 4 on the processed_rows field and also give me a date-by-category pivot so I can see how each group performed each day?”
Pipeline duration anomaly investigation
“My data pipeline has been running slow lately. I have 50 rows of transformation records with duration_seconds and processed_rows per dataset group across October. Can you calculate a rolling mean with window 5 on duration_seconds and pivot the data by date and group so I can spot which category is the bottleneck?”
Weekly throughput reporting for data team
“I need a weekly summary report for my data team. I have transformation throughput records for 200 rows spanning three groups — alpha, beta, gamma — over the last month. Please compute the trailing mean series (window of 7) for processed_rows and produce a date-by-group pivot table so we can review performance trends.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-13-152?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have local transformation throughput records (processed_rows, duration_seconds) and need both a rolling/trailing mean time-series and a date-by-category pivot in a single low-cost call. Ideal for data engineers and analysts who want offline analytical summaries of ETL or pipeline performance data without sending data to a heavyweight analytics platform. Best when data is already collected and you need two standard statistical views simultaneously for up to 200 rows at minimal cost.
Side effects
- Fewer than 1 row supplied — validation error
- window size larger than the number of supplied rows — trailing mean may return nulls or partial results
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- processed_rows or duration_seconds outside allowed numeric range — validation error
- More than 200 rows supplied — rejected at maxItems limit
- Missing required fields row_id, dataset_group, date — schema validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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