# Building Footprint Observations — String Normalisation + Secondary-Measure Weighted Mean

> Building Footprint Observations — String Normalisation + Secondary-Measure Weighted Mean is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-04).

Performs string normalisation and secondary-measure weighted mean analysis on up to 200 building footprint observation records (footprint_m2, height_m), returning 2 analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-weather-16-034?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-11-04
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/building-footprint-observations-string-normalisation-secondary-653476a4
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_wHy2Y2NI2hOKwgjtOkyWF

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 building-footprint-observations-string-normalisation-secondary-653476a4 -d '<json body>'
```

Example prompt: Can you run string normalisation and a secondary-measure weighted mean on these building footprint records — I have 4 rows with fields row_id, station_group, date, footprint_m2, and height_m — and give me both analytical reports for the footprint_m2 field?

## When to prefer this

Choose this endpoint when you have tabular building footprint observation data (up to 200 rows) and need both string normalisation of categorical fields and a secondary-measure weighted mean — all computed locally without any external data lookup, prediction, or live API calls. It is best suited for offline analytical pipelines processing building measurement datasets where both data cleaning and weighted aggregation are needed together in a single call at low cost.

## Known failure modes

- More than 200 rows submitted — request rejected due to maxItems constraint
- Missing required fields (row_id, station_group, date, footprint_m2, height_m) cause validation errors
- Invalid date format (not YYYY-MM-DD) triggers pattern validation failure
- Null values in both numeric fields may produce undefined weighted mean results
- Invalid field enum value (not footprint_m2 or height_m) causes schema rejection
- Empty rows array rejected due to minItems constraint

## How this service works

Building footprint observations — String normalisation + Secondary-measure weighted mean: String normalisation + Secondary-measure weighted mean for supplied building footprint observations records (footprint_m2, height_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

Returns 2 analytical reports: a string normalisation report cleaning station_group and other string fields, and a secondary-measure weighted mean report computing weighted averages of the selected field (footprint_m2 or height_m) using the other numeric measure as the weight — all derived locally from the supplied rows without external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "station_group",
     "date",
     "footprint_m2",
     "height_m"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "height_m": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "footprint_m2": {
      "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",
     "height_m": 1,
     "footprint_m2": 10,
     "station_group": "group-a"
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "height_m": 2,
     "footprint_m2": 20,
     "station_group": "group-b"
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "height_m": 3,
     "footprint_m2": 15,
     "station_group": "group-a"
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "height_m": 4,
     "footprint_m2": 30,
     "station_group": "group-b"
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "footprint_m2",
    "height_m"
   ],
   "type": "string",
   "default": "footprint_m2"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/building-footprint-observations-string-normalisation-secondary-653476a4/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)