# Land Parcel Observations — Numeric Row Ordering + Explicit Missing-Value Fill

> Land Parcel Observations — 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 land parcel observation rows numerically and fills missing area_m2 or perimeter_m values using zero, mean, or median imputation, returning two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-weather-14-124?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/land-parcel-observations-numeric-row-ordering-explicit-missing-value-4ec390f2
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_SKqeTpRlszaz-pvt-UDAg

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 land-parcel-observations-numeric-row-ordering-explicit-missing-value-4ec390f2 -d '<json body>'
```

Example prompt: I have up to 200 land parcel observations with area_m2 and perimeter_m fields, some values are missing — can you sort the rows numerically and fill in the missing area_m2 values using median imputation, then give me two analytical reports?

## When to prefer this

Choose this endpoint when you have land parcel observation data (with area_m2 and perimeter_m fields) that needs both numeric row ordering and missing-value imputation in a single call, returning two reports at once. It is ideal for preprocessing survey or cadastral datasets before analysis. Prefer it over generic data-cleaning tools when your data fits the parcel schema and you want statistically sound fill (zero, mean, or median) with no external dependencies or side effects.

## Known failure modes

- Rows array empty or missing — minItems:1 validation error
- More than 200 rows submitted — maxItems:200 exceeded
- Invalid date format (not YYYY-MM-DD) — pattern validation failure
- Field value not in enum [area_m2, perimeter_m] — schema validation error
- Method value not in enum [zero, mean, median] — schema validation error
- row_id missing or empty string — minLength:1 validation failure
- Numeric values outside ±1,000,000,000,000 bounds — schema rejection

## How this service works

Land parcel observations — Numeric row ordering + Explicit missing-value fill: Numeric row ordering + Explicit missing-value fill for supplied land parcel observations records (area_m2, perimeter_m). 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

Two structured analytical reports covering the supplied land parcel observation rows after numeric row ordering and explicit missing-value fill (using zero, mean, or median) for the selected field (area_m2 or perimeter_m). Reports are generated from local analytical engines with no live lookups or external data.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "station_group",
     "date",
     "area_m2",
     "perimeter_m"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "area_m2": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "perimeter_m": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "station_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "area_m2": 10,
     "perimeter_m": 1,
     "station_group": "group-a"
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "area_m2": 20,
     "perimeter_m": 2,
     "station_group": "group-b"
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "area_m2": 15,
     "perimeter_m": 3,
     "station_group": "group-a"
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "area_m2": 30,
     "perimeter_m": 4,
     "station_group": "group-b"
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "area_m2",
    "perimeter_m"
   ],
   "type": "string",
   "default": "area_m2"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/land-parcel-observations-numeric-row-ordering-explicit-missing-value-4ec390f2/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)