# Record Routing Analytics: Trailing Mean Series + Date-by-Category Pivot

> Record Routing Analytics: Trailing Mean Series + Date-by-Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).

Computes a trailing mean time series and a date-by-category pivot table for accepted_records and rejected_records fields in supplied record routing data (up to 200 rows, two reports per call).

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-19-152?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/record-routing-analytics-trailing-mean-series-date-by-category-pivot-62818979
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_VElm6XQBJhR68HWQLBltO

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-trailing-mean-series-date-by-category-pivot-62818979 -d '<json body>'
```

Example prompt: Can you run a trailing mean series with a window of 3 and a date-by-category pivot on my record routing data? I have accepted_records and rejected_records by date and dataset_group — here are my rows: [{"date":"2026-10-01","row_id":"r1","dataset_group":"group-a","accepted_records":100,"rejected_records":5},{"date":"2026-10-02","row_id":"r2","dataset_group":"group-b","accepted_records":200,"rejected_records":10}]. Use accepted_records as the field.

## When to prefer this

Choose this endpoint when you have up to 200 rows of record routing data with accepted/rejected record counts grouped by date and category, and you need both a rolling/trailing mean time series and a date-by-category pivot in a single cheap call ($0.01 USDC). It is a self-contained analytical engine with no external dependencies, making it ideal for lightweight, reproducible batch analytics on pipeline or data quality metrics without setting up your own compute.

## Known failure modes

- Fewer than 1 row supplied — minimum 1 row required
- More than 200 rows supplied — results truncated or rejected
- Invalid date format (must be YYYY-MM-DD)
- Window size less than 2 or greater than 200 — validation error
- Null or missing required fields (row_id, date, dataset_group) cause row-level errors
- Field enum value not one of 'accepted_records' or 'rejected_records' — rejected
- Payment of 0.01 USDC not completed — request blocked

## How this service works

Record routing — Trailing mean series + Date by category pivot: Trailing mean series + Date by category pivot 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

Returns two analytical reports: (1) a trailing mean time series for the chosen field (accepted_records or rejected_records) computed over the specified rolling window across the supplied rows, and (2) a pivot table breaking down values by date and dataset_group category. Results are based entirely on the supplied data 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"
  },
  "window": {
   "type": "integer",
   "default": 2,
   "maximum": 200,
   "minimum": 2
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/record-routing-analytics-trailing-mean-series-date-by-category-pivot-62818979/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)