# Transport Ridership Adjacent Row Changes + Missing Value Fill

> Transport Ridership Adjacent Row Changes + 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 2026-10-26).

Computes adjacent row changes and fills missing values for transport ridership records (passenger_count, service_count) across up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-economics-05-162?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/transport-ridership-adjacent-row-changes-missing-value-fill-9c2716c3
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_KC9zexHHC7r261qregMz_

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-adjacent-row-changes-missing-value-fill-9c2716c3 -d '<json body>'
```

Example prompt: I have transit ridership data for two regions over the past week — can you compute the row-by-row changes in passenger_count and fill any missing values using median imputation? Here are up to 50 rows with row_id, region, date, passenger_count, and service_count.

## When to prefer this

Choose this endpoint when you need to simultaneously compute sequential row deltas AND impute missing values in transport ridership data (passenger_count or service_count) in a single API call. Ideal for transit analysts cleaning and exploring time-series ridership datasets of up to 200 rows without needing external data sources, predictions, or live lookups. The bundled two-report output makes it cost-effective at $0.01 USDC per call.

## Known failure modes

- Exceeds 200-row limit — request rejected
- Missing required fields (row_id, date, region) — validation error
- Invalid date format not matching YYYY-MM-DD pattern — rejected
- Invalid method enum value (must be zero, mean, or median) — error
- Invalid field enum value (must be passenger_count or service_count) — error
- Numeric values outside allowed range (-1T to +1T) — validation failure
- Empty rows array — error

## How this service works

Transport ridership — Adjacent row changes + Explicit missing-value fill: Adjacent row changes + 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

Two analytical reports: (1) an adjacent row changes report showing the delta between consecutive rows for the specified field, and (2) a missing value fill report with nulls replaced using the chosen method (zero, mean, or median) — applied to passenger_count or service_count across all 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-adjacent-row-changes-missing-value-fill-9c2716c3/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)