# Aggregation Checks — Numeric Row Ordering + Explicit Missing-Value Fill

> Aggregation Checks — Numeric Row Ordering + 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 2026-10-15).

Sorts aggregation check rows numerically and fills missing source_sum or aggregate_sum values using zero, mean, or median imputation, producing two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-17-124?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/aggregation-checks-numeric-row-ordering-explicit-missing-value-fill-18af2ed5
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_0oLSbfavtdVPdN0dRviwU

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-numeric-row-ordering-explicit-missing-value-fill-18af2ed5 -d '<json body>'
```

Example prompt: I have up to 200 aggregation check rows with row_id, dataset_group, date, source_sum, and aggregate_sum fields — some source_sum values are null. Can you sort them numerically and fill the missing source_sum values using the median method, then give me two analytical reports?

## When to prefer this

Choose this endpoint when you need both numeric row ordering and null imputation on aggregation check data (source_sum + aggregate_sum pairs) in a single $0.01 call that delivers two reports. It is ideal for data reconciliation workflows where missing values must be filled before downstream aggregation validation, and where no live external data lookup or prediction is needed — pure local computation on up to 200 supplied rows.

## Known failure modes

- Fewer than 1 row supplied — request rejected
- More than 200 rows supplied — request rejected (maxItems limit)
- Invalid date format (not YYYY-MM-DD) — schema validation error
- source_sum or aggregate_sum values outside ±1,000,000,000,000 range — rejected
- Invalid method enum value (not zero/mean/median) — schema validation error
- Invalid field enum value (not source_sum/aggregate_sum) — schema validation error
- Payment not included or insufficient USDC — x402 payment required error

## How this service works

Aggregation checks — Numeric row ordering + Explicit missing-value fill: Numeric row ordering + 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 independent analytical reports covering: (1) numeric row ordering of the supplied aggregation check records by date or row sequence, and (2) explicit missing-value fill applied to the specified field (source_sum or aggregate_sum) using the chosen method (zero, mean, or median). Reports are generated locally without external lookups or predictions.

## 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"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/aggregation-checks-numeric-row-ordering-explicit-missing-value-fill-18af2ed5/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)