# Company Headcount Observations — Secondary-Measure Weighted Mean + Explicit Missing-Value Fill

> Company Headcount Observations — Secondary-Measure Weighted Mean + 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 2026-10-19).

Computes a secondary-measure weighted mean and fills missing values in company headcount observation records (headcount and open_roles) for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-12-187?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-19
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/company-headcount-observations-secondary-measure-weighted-mean-1e5c655b
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_qgRUehMEIHV2Ja8ZQwZxy

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 company-headcount-observations-secondary-measure-weighted-mean-1e5c655b -d '<json body>'
```

Example prompt: I have a batch of company headcount records (up to 50 rows across groups like 'engineering' and 'sales') with some null headcount values — can you compute the secondary-measure weighted mean using open_roles as the secondary measure and fill missing headcount values using median imputation?

## When to prefer this

Choose this endpoint when you have tabular company headcount or open_roles data with potential null values and need both a statistically weighted summary (using the secondary measure as weights) and clean missing-value imputation in a single low-cost call. It is ideal for HR analytics pipelines, workforce planning preprocessing, or any scenario where you need to normalize sparse headcount observations across company groups without connecting to an external data source.

## Known failure modes

- More than 200 rows submitted — request exceeds maxItems limit and will be rejected
- Missing required fields (row_id, company_group, date, headcount, or open_roles) cause validation errors
- Invalid date format (not YYYY-MM-DD) results in schema validation failure
- Invalid enum value for 'field' or 'method' parameter causes a bad request error
- Payment not provided or insufficient USDC balance results in 402 Payment Required
- All values for the target field are null — weighted mean cannot be computed meaningfully

## How this service works

Company headcount observations — Secondary-measure weighted mean + Explicit missing-value fill: Secondary-measure weighted mean + Explicit missing-value fill for supplied company headcount observations records (headcount, open_roles). 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: (1) a secondary-measure weighted mean computed over the specified field (headcount or open_roles), using the other measure as a weight; and (2) an explicit missing-value fill applied to null entries using the specified method (zero, mean, or median). Results cover up to 200 submitted rows and are computed locally without external data lookup.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/company-headcount-observations-secondary-measure-weighted-mean-1e5c655b/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)