# Aggregation Checks — Trailing Mean Series + Explicit Missing-Value Fill

> Aggregation Checks — Trailing Mean Series + Explicit 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 2026-10-24).

Computes a trailing mean time series and fills missing values in aggregation check records (source_sum, aggregate_sum) for up to 200 rows, returning two analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-17-154?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-24
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/aggregation-checks-trailing-mean-series-explicit-missing-value-fill-4eb90dcb
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_4ebHPdP5_zQa3x4qkF272

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 aggregation-checks-trailing-mean-series-explicit-missing-value-fill-4eb90dcb -d '<json body>'
```

Example prompt: I have 150 rows of aggregation check data with dates and source_sum values — some source_sum entries are null. Can you compute a trailing mean series with a window of 7 days and fill the missing values using the mean method?

## When to prefer this

Choose this endpoint when you need both trailing mean smoothing and missing-value imputation applied to aggregation check records (source_sum / aggregate_sum) in a single $0.01 call covering up to 200 rows. It is especially useful for data quality pipelines that need to reconcile source and aggregate totals before reporting or downstream processing, without requiring any external data lookup or live computation infrastructure.

## Known failure modes

- Fewer than 1 row submitted — validation error
- More than 200 rows submitted — rejected with max-items error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Window size outside 2–200 range — rejected
- source_sum or aggregate_sum values outside ±1,000,000,000,000 — rejected
- Unknown fill method or field enum value — schema validation error
- Payment not included or insufficient — x402 payment required response

## How this service works

Aggregation checks — Trailing mean series + Explicit missing-value fill: Trailing mean series + Explicit missing-value fill for supplied aggregation checks records (source_sum, aggregate_sum). 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 per call: a trailing mean series (rolling window average over the specified field across sorted date rows) and an explicit missing-value fill report (nulls replaced using the chosen method — zero, mean, or median). Reports cover up to 200 input rows grouped by dataset_group and date.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/aggregation-checks-trailing-mean-series-explicit-missing-value-fill-4eb90dcb/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)