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Parking Utilization - Date by Category Pivot
x402
Parking Utilization - 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 2026-10-15).
Pivots parking utilization records (occupied/available spaces) by date and zone category, returning a summary table up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Parking utilization - Date by category pivot: Date by category pivot for Parking utilization. Up to 200 supplied typed records. Local descriptive analytics; no enrichment or forecast. One of 25 new profiles across 20 shared operations in this industry. 0.01 USDC includes one bounded date by category pivot report.
Output
A date-by-category pivot table summarizing the chosen metric (occupied_spaces or available_spaces) cross-tabulated by date rows and zone columns, covering up to 200 input records with local descriptive analytics and no external enrichment or forecasting.
Example use cases
Daily occupancy breakdown by zone
“I have parking data for our downtown garage across zones North, South, and East for the past two weeks — can you pivot the occupied_spaces by date and zone so I can see which zones fill up on which days?”
Available spaces trend by parking area
“Pivot my parking lot availability data by date and category using available_spaces as the metric — I've got records for zones Red, Blue, and Green from November 1 through November 14, 2026.”
Event-day parking utilization report
“We tracked parking for our stadium lots during the season — zones Home, Away, and VIP — from September 5 to September 30, 2026. Can you create a date-by-zone pivot on occupied_spaces so I can spot which event days were most congested?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ar-analytics-parking-utilization-pivot?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have raw parking utilization records and need a quick descriptive pivot table broken down by date and zone category — ideal for local analytics without needing forecasting, enrichment, or external data sources. Best for datasets up to 200 records where the goal is summarizing occupied or available space counts across time and location.
Side effects
- Input array is empty or missing required fields (row_id, zone, date, occupied_spaces, available_spaces)
- More than 200 rows supplied — exceeds maxItems limit
- Date field does not match YYYY-MM-DD pattern
- Invalid field enum value (must be occupied_spaces or available_spaces)
- Payment not included or insufficient — x402 payment required ($0.01 USDC)
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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