# Company Headcount Observations — Numeric Distribution + Explicit Missing-Value Fill

> Company Headcount Observations — Numeric Distribution + 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).

Analyzes up to 200 company headcount observation records, producing a numeric distribution report and filling missing headcount or open_roles values using zero, mean, or median imputation.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-12-085?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-numeric-distribution-explicit-missing-41664a60
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_TkmwqbWmgB0c6sudPuNni

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-numeric-distribution-explicit-missing-41664a60 -d '<json body>'
```

Example prompt: I have 50 rows of company headcount observations with some missing headcount values — can you fill in the blanks using median imputation and also give me a numeric distribution report for the headcount field?

## When to prefer this

Choose this endpoint when you have a batch of up to 200 company headcount or open_roles records that need both a numeric distribution summary and missing-value imputation in a single call. It is ideal for HR analytics pipelines, workforce reporting, and data preparation workflows where you need to understand data spread and clean nulls before downstream use. It operates entirely on supplied data with no external lookups, making it fast, deterministic, and safe for sensitive workforce data.

## Known failure modes

- More than 200 rows submitted — request exceeds maxItems limit and will be rejected
- Missing required row fields (row_id, company_group, date, headcount, open_roles) — validation error
- Invalid date format (not YYYY-MM-DD) — pattern validation failure
- Invalid field enum value (must be 'headcount' or 'open_roles') — rejected
- Invalid method enum value (must be 'zero', 'mean', or 'median') — rejected
- Empty rows array — minItems violation
- Payment failure — 0.01 USDC not provided or x402 protocol error

## How this service works

Company headcount observations — Numeric distribution + Explicit missing-value fill: Numeric distribution + 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 for the supplied batch of up to 200 rows: (1) a numeric distribution summary for the selected field (headcount or open_roles), including statistics like min, max, mean, median, and spread indicators; and (2) an explicit missing-value fill report showing which rows had nulls and what values were imputed using the chosen method (zero, mean, or median). No external data is fetched; all analysis is performed locally on the supplied records.

## 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-numeric-distribution-explicit-missing-41664a60/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)