# Company Headcount Observations — Base-100 Series & Missing-Value Fill

> Company Headcount Observations — Base-100 Series & 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).

Transforms supplied company headcount and open-roles time series data into a Base-100 indexed series and fills explicit missing values, producing two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-12-169?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-base-100-series-missing-value-fill-4d42f6a6
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_71MpxVcQDfcjIKrr2aDu9

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-base-100-series-missing-value-fill-4d42f6a6 -d '<json body>'
```

Example prompt: I have daily headcount and open_roles records for two company groups from October 2026 — can you normalize them to a Base-100 index starting at row 0 and fill any missing headcount values using median imputation?

## When to prefer this

Choose this endpoint when you have pre-collected company headcount or open-roles time series data (up to 200 rows) and need both a Base-100 normalized trend series and missing-value imputation in a single call. It is ideal for offline or batch analytical use where the data is already available and no live lookup, prediction, or external data enrichment is required. Prefer this over general analytics platforms when you need a lightweight, pay-per-use computation that handles both normalization and gap-filling simultaneously.

## Known failure modes

- Input array exceeds 200 rows — request will be rejected
- base_index references a row index beyond the array length
- Selected field contains no non-null values, making mean/median fill undefined
- Date strings not matching YYYY-MM-DD pattern will fail schema validation
- Missing required fields (row_id, company_group, date) cause row rejection
- Payment of 0.01 USDC not provided or declined blocks the request

## How this service works

Company headcount observations — Base-100 series + Explicit missing-value fill: Base-100 series + 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

Two analytical reports: (1) a Base-100 indexed time series for the selected field (headcount or open_roles) anchored to the specified base_index row, normalizing all values relative to that reference point; and (2) a missing-value filled version of the same series using the chosen method (zero, mean, or median). Output covers up to 200 input rows grouped by company_group and date.

## 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"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/company-headcount-observations-base-100-series-missing-value-fill-4d42f6a6/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)