# Transport Ridership Category Frequencies & IQR Outlier Flags

> Transport Ridership Category Frequencies & 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 2026-10-25).

Computes category-level frequency counts and flags IQR-based outliers for transport ridership records (passenger_count or service_count) across up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-economics-05-107?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-25
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/transport-ridership-category-frequencies-iqr-outlier-flags-a3cce835
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_uPiXbsWcTh3h1wZaxdn3I

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 transport-ridership-category-frequencies-iqr-outlier-flags-a3cce835 -d '<json body>'
```

Example prompt: Analyze my transit dataset for category frequencies and IQR outlier flags on passenger_count — I have 4 rows: row-1 (2026-10-01, group-a, passenger_count=10, service_count=1), row-2 (2026-10-02, group-b, 20, 2), row-3 (2026-10-03, group-a, 15, 3), row-4 (2026-10-04, group-b, 30, 4). Give me both the frequency report and the outlier flags.

## When to prefer this

Choose this endpoint when you need both category frequency analysis and IQR-based outlier detection specifically on transport ridership data (passenger_count and/or service_count fields) in a single low-cost call. It is ideal for offline batch-style statistical audits of up to 200 records without requiring any live data lookup, prediction, or external service. Prefer it over general analytics tools when working with the structured ridership schema (row_id, region, date) and needing a fast, cheap ($0.01 USDC) dual-report output.

## Known failure modes

- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, region, date, passenger_count, service_count) cause validation errors
- Invalid date format (must match YYYY-MM-DD pattern) causes schema rejection
- Numeric values outside the allowed range (-1e12 to 1e12) rejected
- Empty rows array (minItems: 1 violated) causes error
- All-null values in selected field may produce empty or degenerate IQR results

## How this service works

Transport ridership — Category frequencies + IQR outlier flags: Category frequencies + IQR outlier flags for supplied transport ridership records (passenger_count, service_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) category frequency counts showing how many records fall into each region/category group, and (2) IQR-based outlier flags identifying which rows have statistically unusual values for the selected field (passenger_count or service_count). Both reports are computed locally without external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/transport-ridership-category-frequencies-iqr-outlier-flags-a3cce835/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)