# Temperature Observations — Numeric Row Ordering + Base-100 Series

> Temperature Observations — Numeric Row Ordering + Base-100 Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-26).

Computes numeric row ordering and a base-100 index series for supplied temperature observation records (temperature_c or observation_count), returning two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-weather-01-117?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-26
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/temperature-observations-numeric-row-ordering-base-100-series-dde922e3
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_GJw8Skcxry9uWkcJjtEh3

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 temperature-observations-numeric-row-ordering-base-100-series-dde922e3 -d '<json body>'
```

Example prompt: I have 4 rows of temperature observations for two station groups — row-1 (group-a, 2026-10-01, 10°C, 1 obs), row-2 (group-b, 2026-10-02, 20°C, 2 obs), row-3 (group-a, 2026-10-03, 15°C, 3 obs), row-4 (group-b, 2026-10-04, 30°C, 4 obs) — can you rank them by temperature_c and produce a base-100 index series starting from row index 0?

## When to prefer this

Choose this endpoint when you have pre-collected temperature observation records (up to 200 rows) and need two lightweight analytical transformations — numeric row ranking and a base-100 index series — computed locally without live data fetching, forecasting, or external API calls. It is cost-effective at $0.01 USDC for both reports together and suits batch post-processing of station observation datasets.

## Known failure modes

- Input array is empty (minItems:1 violated) — request rejected
- More than 200 rows supplied (maxItems:200 exceeded) — request rejected
- Date field does not match YYYY-MM-DD pattern — validation error
- row_id missing or empty string — validation error
- temperature_c or observation_count outside allowed numeric range — validation error
- field enum value not 'temperature_c' or 'observation_count' — validation error
- base_index out of range 0–199 or exceeds actual row count — computation error

## How this service works

Temperature observations — Numeric row ordering + Base-100 series: Numeric row ordering + Base-100 series for supplied temperature observations records (temperature_c, observation_count). 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 independent analytical reports: (1) a numeric row ordering of the supplied records ranked by the chosen field (temperature_c or observation_count), and (2) a base-100 index series expressing each row's value relative to the designated base row. Both reports are computed locally from the supplied 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",
     "temperature_c",
     "observation_count"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "station_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "temperature_c": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "observation_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "station_group": "group-a",
     "temperature_c": 10,
     "observation_count": 1
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "station_group": "group-b",
     "temperature_c": 20,
     "observation_count": 2
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "station_group": "group-a",
     "temperature_c": 15,
     "observation_count": 3
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "station_group": "group-b",
     "temperature_c": 30,
     "observation_count": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "temperature_c",
    "observation_count"
   ],
   "type": "string",
   "default": "temperature_c"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/temperature-observations-numeric-row-ordering-base-100-series-dde922e3/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)