# Air Quality Observations — Numeric Interval Filter + IQR Outlier Flags

> Air Quality Observations — Numeric Interval Filter + IQR Outlier Flags is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-22).

Filters air quality observation rows by a numeric interval and flags statistical outliers using IQR analysis, returning two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-weather-10-130?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-22
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/air-quality-observations-numeric-interval-filter-iqr-outlier-flags-6947dead
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_lZBbHPlHeactRZrGlzht2

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 air-quality-observations-numeric-interval-filter-iqr-outlier-flags-6947dead -d '<json body>'
```

Example prompt: I have a batch of air quality readings with concentration values — can you filter them to only keep rows where concentration is between 0 and 150, and also flag any IQR outliers in the concentration field? Here are up to 200 rows with row_id, station_group, date, concentration, and observation_count.

## When to prefer this

Choose this endpoint when you have up to 200 air quality observation records and need both a numeric range filter and IQR-based outlier detection in a single call, without requiring live data fetching, prediction, or external integrations. It is ideal for offline data quality checks on batch datasets where concentration or observation_count needs statistical validation.

## Known failure modes

- More than 200 rows submitted — request rejected or truncated
- Invalid date format (not YYYY-MM-DD) causes row validation failure
- Minimum value greater than maximum value yields empty interval filter result
- Missing required fields (row_id, concentration, observation_count) cause schema rejection
- Null numeric values may be excluded from IQR computation

## How this service works

Air quality observations — Numeric interval filter + IQR outlier flags: Numeric interval filter + IQR outlier flags for supplied air quality observations records (concentration, 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

Two analytical reports covering: (1) rows filtered to the specified numeric interval for the chosen field (concentration or observation_count), and (2) IQR-based outlier flags for the same field, applied to all supplied rows. Results are computed locally with no external lookup.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "station_group",
     "date",
     "concentration",
     "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
     },
     "concentration": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "station_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "observation_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "concentration": 10,
     "station_group": "group-a",
     "observation_count": 1
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "concentration": 20,
     "station_group": "group-b",
     "observation_count": 2
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "concentration": 15,
     "station_group": "group-a",
     "observation_count": 3
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "concentration": 30,
     "station_group": "group-b",
     "observation_count": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "concentration",
    "observation_count"
   ],
   "type": "string",
   "default": "concentration"
  },
  "maximum": {
   "type": "number",
   "default": 100,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  },
  "minimum": {
   "type": "number",
   "default": 0,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/air-quality-observations-numeric-interval-filter-iqr-outlier-flags-6947dead/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)