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Equipment Runtime Date-by-Category Pivot
x402
Equipment Runtime 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 2026-10-19).
Pivots equipment runtime and downtime hours data by date and machine category, returning a summary table of up to 200 records.
Price / call$0.01
Success—
StatusUnknown
How this service works
Equipment runtime - Date by category pivot: Date by category pivot for Equipment runtime. Up to 200 supplied typed records. Local numeric and data-quality processing; no external enrichment or forecasting. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded date by category pivot deliverable.
Output
Returns a date-by-category pivot table where rows represent dates and columns represent machine categories, with cells containing the aggregated value (run_hours or downtime_hours) for each date-category combination, computed locally from the supplied records without external enrichment.
Example use cases
Daily runtime comparison across machine groups
“I have a week's worth of equipment logs for two machine groups, Alpha and Beta — can you pivot the run_hours by date and machine category so I can see side-by-side how many hours each group ran each day? Here are the rows: row-1 Alpha 2026-11-01 8h run 0.5h down, row-2 Beta 2026-11-01 12h run 1h down, row-3 Alpha 2026-11-02 9h run 0h down, row-4 Beta 2026-11-02 11h run 2h down.”
Downtime hotspot analysis by category
“Can you pivot our equipment downtime_hours by date and machine category? I want to see which groups had the most downtime on which days. I'll give you 6 records: row-1 Press-A 2026-10-10 6h run 2h down, row-2 Press-B 2026-10-10 8h run 0.5h down, row-3 Press-A 2026-10-11 4h run 4h down, row-4 Press-B 2026-10-11 7h run 1h down, row-5 Press-A 2026-10-12 5h run 3h down, row-6 Press-B 2026-10-12 9h run 0h down.”
Monthly utilization summary for maintenance planning
“Please create a date-by-category pivot on run_hours for our three machine lines — Line-1, Line-2, Line-3 — across these 9 daily records for October: row-1 Line-1 2026-10-01 10h run 0h down, row-2 Line-2 2026-10-01 14h run 1h down, row-3 Line-3 2026-10-01 6h run 3h down, row-4 Line-1 2026-10-02 11h run 0.5h down, row-5 Line-2 2026-10-02 13h run 0h down, row-6 Line-3 2026-10-02 5h run 4h down, row-7 Line-1 2026-10-03 9h run 1h down, row-8 Line-2 2026-10-03 15h run 0h down, row-9 Line-3 2026-10-03 7h run 2h down.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-analytics-equipment-runtime-pivot?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have raw equipment operational records (up to 200 rows) and need a structured pivot table grouped by date and machine category for either run hours or downtime hours. It is ideal for quick local aggregation without needing an external analytics platform or BI tool. It is not suitable for time-series forecasting, anomaly detection, or datasets exceeding 200 records.
Side effects
- Missing required fields (row_id, machine, date, run_hours, downtime_hours) causes validation error
- Date strings not matching YYYY-MM-DD pattern are rejected
- More than 200 rows supplied triggers a max-items validation error
- Empty rows array (minItems:1 violated) returns an error
- Invalid field enum value (not run_hours or downtime_hours) returns a schema error
- Null numeric values are accepted but may result in blank pivot cells
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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