# Geospatial Tile Processing — Exact Row Deduplication + Date by Category Pivot

> Geospatial Tile Processing — Exact Row Deduplication + 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 2026-11-02).

Deduplicates geospatial tile processing records and pivots date values by category (station_group), returning two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-weather-21-052?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-11-02
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/geospatial-tile-processing-exact-row-deduplication-date-by-category-77f4ec03
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_f1RaGl5NutiuzL0Tnx-Gg

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability geospatial-tile-processing-exact-row-deduplication-date-by-category-77f4ec03 -d '<json body>'
```

Example prompt: I have a batch of geospatial tile processing records with tile_count and processing_seconds — can you deduplicate the exact duplicate rows and also pivot the dates by station group? Here are my rows: row-1 (group-a, 2026-10-01, tile_count=10, processing_seconds=1), row-2 (group-b, 2026-10-02, tile_count=20, processing_seconds=2), row-3 (group-a, 2026-10-03, tile_count=15, processing_seconds=3). Run the analysis on the tile_count field.

## When to prefer this

Choose this endpoint when you have geospatial tile processing records (with tile_count and processing_seconds) and need both exact deduplication and a date-by-category pivot in a single low-cost call. It is best for datasets up to 200 rows where no live data lookup, external enrichment, or predictive modeling is needed — purely local analytical computation on supplied data.

## Known failure modes

- Exceeds 200-row limit — request rejected or truncated
- Invalid date format not matching YYYY-MM-DD pattern — validation error
- Missing required fields (row_id, station_group, date, tile_count, or processing_seconds) — schema validation failure
- Numeric values outside allowed range — rejection
- Empty rows array — schema validation failure
- Invalid field enum value (not tile_count or processing_seconds) — error

## How this service works

Geospatial tile processing — Exact row deduplication + Date by category pivot: Exact row deduplication + Date by category pivot for supplied geospatial tile processing records (tile_count, processing_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) an exact row deduplication report identifying and removing fully duplicated rows from the submitted geospatial tile processing records, and (2) a date-by-category pivot table showing the selected metric (tile_count or processing_seconds) cross-tabulated by date and station_group. Both reports are computed locally from the submitted data with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "station_group",
     "date",
     "tile_count",
     "processing_seconds"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "tile_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "station_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "processing_seconds": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "tile_count": 10,
     "station_group": "group-a",
     "processing_seconds": 1
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "tile_count": 20,
     "station_group": "group-b",
     "processing_seconds": 2
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "tile_count": 15,
     "station_group": "group-a",
     "processing_seconds": 3
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "tile_count": 30,
     "station_group": "group-b",
     "processing_seconds": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "tile_count",
    "processing_seconds"
   ],
   "type": "string",
   "default": "tile_count"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/geospatial-tile-processing-exact-row-deduplication-date-by-category-77f4ec03/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from market.datapackvibe.com](https://www.zero.xyz/host/market.datapackvibe.com/llms.txt)