# Record Routing Analytics: Adjacent Row Changes + Missing-Value Fill

> Record Routing Analytics: 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 2026-10-23).

Analyzes accepted_records and rejected_records columns in routing data by computing adjacent-row changes and filling missing values using zero, mean, or median imputation — returning two reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-19-162?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-23
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/record-routing-analytics-adjacent-row-changes-missing-value-fill-745e098e
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_EbXyY2Xl5tFcwTp7LnwVA

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 record-routing-analytics-adjacent-row-changes-missing-value-fill-745e098e -d '<json body>'
```

Example prompt: I have 4 rows of daily record routing data for group-a and group-b — can you run the adjacent row changes report and fill any missing accepted_records values using median imputation?

## When to prefer this

Use this endpoint when you have tabular record routing data with accepted_records and rejected_records columns and need two lightweight local analytical operations — adjacent-row change detection and missing-value imputation — without any external API calls, predictions, or live data enrichment. Ideal for data quality audits, pipeline monitoring, and preprocessing steps before further analysis. At $0.01 for both reports on up to 200 rows, it is cost-effective for frequent batch checks.

## Known failure modes

- More than 200 rows submitted — request will be rejected or truncated
- Invalid date format (not YYYY-MM-DD) causes validation error
- Missing required fields (row_id, date, dataset_group) causes schema rejection
- field enum value not one of accepted_records or rejected_records causes error
- method enum value not one of zero, mean, median causes error
- Empty rows array (minItems:1 violated) returns error

## How this service works

Record routing — Adjacent row changes + Explicit missing-value fill: Adjacent row changes + Explicit missing-value fill for supplied record routing records (accepted_records, rejected_records). 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-change report showing the delta between consecutive rows for the selected field (accepted_records or rejected_records), and (2) a missing-value fill report showing where nulls were found and what values were substituted using the chosen method (zero, mean, or median). Results cover up to 200 input rows with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/record-routing-analytics-adjacent-row-changes-missing-value-fill-745e098e/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)