# Geospatial Tile Processing — Numeric Row Ordering + Explicit Missing-Value Fill

> Geospatial Tile Processing — Numeric Row Ordering + 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 2026-11-02).

Sorts geospatial tile processing records by a numeric field and fills in missing values using zero, mean, or median strategies for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-weather-21-124?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-numeric-row-ordering-explicit-missing-82c0fadb
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_KjlAbj2Z1GK7uKAFW4bdH

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-numeric-row-ordering-explicit-missing-82c0fadb -d '<json body>'
```

Example prompt: I have a dataset of geospatial tile processing records with some missing tile_count values — can you sort the rows numerically by tile_count and fill in the missing ones using the median, for these 4 rows: row-1 on 2026-10-01 in group-a with tile_count 10 and processing_seconds 1, row-2 on 2026-10-02 in group-b with tile_count null and processing_seconds 2, row-3 on 2026-10-03 in group-a with tile_count 15 and processing_seconds 3, row-4 on 2026-10-04 in group-b with tile_count 30 and processing_seconds 4?

## When to prefer this

Choose this endpoint when you have a structured dataset of geospatial tile processing records (with tile_count and/or processing_seconds columns) and need both numeric row ordering and explicit missing-value imputation in a single call, without any live data lookup, prediction, or external action. It is ideal for data cleaning and preprocessing pipelines where datasets have up to 200 rows and you want reproducible, locally computed analytical reports at low cost ($0.01 USDC for 2 reports).

## Known failure modes

- Input exceeds 200 rows — request will be rejected
- Invalid date format not matching YYYY-MM-DD pattern — validation error
- Missing required fields (row_id, station_group, date) — schema validation failure
- Field values outside allowed numeric range (±1,000,000,000,000) — rejected
- Invalid method enum value (not zero/mean/median) — rejected
- Invalid field enum (not tile_count/processing_seconds) — rejected
- Payment not processed — endpoint returns 402

## How this service works

Geospatial tile processing — Numeric row ordering + Explicit missing-value fill: Numeric row ordering + Explicit missing-value fill 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 on the submitted geospatial tile processing records: one showing rows ordered numerically by the selected field (tile_count or processing_seconds), and one showing rows with missing values in that field explicitly filled using the chosen strategy (zero, mean, or median). Covers up to 200 input rows.

## 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"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/geospatial-tile-processing-numeric-row-ordering-explicit-missing-82c0fadb/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)