# Transport Ridership Weighted Mean & Missing Value Fill

> Transport Ridership Weighted Mean & 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).

Computes a secondary-measure weighted mean and fills missing values for supplied transport ridership records (passenger_count, service_count) across up to 200 rows, returning 2 analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-economics-05-187?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/transport-ridership-weighted-mean-missing-value-fill-b939b787
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_fJofsShJBjX3h5McCSaUd

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-weighted-mean-missing-value-fill-b939b787 -d '<json body>'
```

Example prompt: I have 150 rows of daily transit ridership data with some missing passenger_count values — can you compute the service_count-weighted mean for passenger_count and fill in the missing values using median imputation? Here are the records with row_id, region, date, passenger_count, and service_count fields.

## When to prefer this

Choose this endpoint when you have tabular transport ridership data (passenger_count, service_count) that needs both a weighted-mean aggregation and missing-value imputation in a single call, at very low cost ($0.01 USDC for 2 reports). Best for batch offline analysis of up to 200 rows where no live data lookup or external prediction is needed.

## Known failure modes

- More than 200 rows submitted — request rejected or truncated
- Missing required fields (row_id, region, date) — validation error
- Invalid date format not matching YYYY-MM-DD pattern — schema rejection
- All values for target field are null — weighted mean cannot be computed
- Numeric values outside allowed range (±1,000,000,000,000) — schema rejection

## How this service works

Transport ridership — Secondary-measure weighted mean + Explicit missing-value fill: Secondary-measure weighted mean + Explicit missing-value fill 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 2 analytical reports for up to 200 supplied rows: (1) a secondary-measure weighted mean result for the specified field (passenger_count or service_count), and (2) a missing-value fill report where nulls are replaced using the chosen method (zero, mean, or median). No external data is fetched; all computation is local to the supplied rows.

## 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"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/transport-ridership-weighted-mean-missing-value-fill-b939b787/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)