# Brand Mention Inventories — Trailing Mean Series + Explicit Missing-Value Fill

> Brand Mention Inventories — 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 2026-10-20).

Computes trailing mean time series and fills missing values for brand mention inventory data (mention_count, source_count) across up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-18-154?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-20
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/brand-mention-inventories-trailing-mean-series-explicit-missing-value-a3e31a78
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_46UR04IFDwRKZiIPwD4lg

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 brand-mention-inventories-trailing-mean-series-explicit-missing-value-a3e31a78 -d '<json body>'
```

Example prompt: Take my brand mention inventory data for group-a and group-b (rows with dates, mention_count, and source_count), compute a trailing mean series with a window of 7 using the mention_count field, and fill any missing values using the mean method.

## When to prefer this

Choose this endpoint when you need to both smooth brand mention time series data via a trailing moving average AND handle missing values in a single paid API call. It bundles two analytical operations (trailing mean + missing-value imputation) for mention_count or source_count fields at a low flat cost. Prefer it over general-purpose analytics tools when working with brand mention inventory records grouped by company and date, especially when the dataset fits within 200 rows and no external data enrichment or prediction is needed.

## Known failure modes

- Input array exceeds 200 rows — request rejected
- Invalid date format (not YYYY-MM-DD) — validation error
- Window size outside 2–200 range — schema validation failure
- Missing required fields (row_id, date, company_group) — request rejected
- No rows supplied (empty array) — validation error
- Unsupported fill method value — enum validation failure

## How this service works

Brand mention inventories — Trailing mean series + Explicit missing-value fill: Trailing mean series + Explicit missing-value fill for supplied brand mention inventories records (mention_count, source_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

Returns two analytical reports: (1) a trailing mean series computed over the specified window for the target field, and (2) the same dataset with missing values explicitly filled using the chosen method (zero, mean, or median). Results cover up to 200 input rows and are produced entirely from supplied data using local analytical engines with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "company_group",
     "date",
     "mention_count",
     "source_count"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "source_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "company_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "mention_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "source_count": 1,
     "company_group": "group-a",
     "mention_count": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "source_count": 2,
     "company_group": "group-b",
     "mention_count": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "source_count": 3,
     "company_group": "group-a",
     "mention_count": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "source_count": 4,
     "company_group": "group-b",
     "mention_count": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "mention_count",
    "source_count"
   ],
   "type": "string",
   "default": "mention_count"
  },
  "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/brand-mention-inventories-trailing-mean-series-explicit-missing-value-a3e31a78/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)