# Customer Segment Observations — Numeric Distribution & Missing-Value Fill

> Customer Segment Observations — Numeric Distribution & 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 2026-10-25).

Computes numeric distribution statistics and fills missing values (zero, mean, or median) for customer segment observation records (account_count, revenue_amount) across up to 200 rows, returning two analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-16-085?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-25
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/customer-segment-observations-numeric-distribution-missing-value-fill-3aaa5923
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_47tkFVMf437l_IFFX-6f1

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 customer-segment-observations-numeric-distribution-missing-value-fill-3aaa5923 -d '<json body>'
```

Example prompt: I have up to 200 rows of customer segment observations with account_count and revenue_amount fields — can you run a numeric distribution report AND fill any missing revenue_amount values using median imputation, for company groups like group-a and group-b across dates like 2026-10-01?

## When to prefer this

Choose this endpoint when you have up to 200 rows of customer segment observation records and need both a numeric distribution summary AND missing-value imputation in a single $0.01 call. It is purpose-built for account_count and revenue_amount fields segmented by company_group and date, with three imputation strategies (zero, mean, median). Prefer it over general-purpose analytics tools when you want offline, local-engine analysis with no external data access and a predictable flat cost.

## Known failure modes

- Rows array empty or missing — request rejected (minItems: 1 required)
- Rows exceed 200 items — request rejected (maxItems: 200)
- Invalid field value not in enum [account_count, revenue_amount] — validation error
- Invalid method value not in enum [zero, mean, median] — validation error
- Date strings not matching YYYY-MM-DD pattern — validation error
- row_id missing or empty string — validation error
- Numeric field values outside ±1,000,000,000,000 range — validation error
- Payment not completed via x402 protocol — request not processed

## How this service works

Customer segment observations — Numeric distribution + Explicit missing-value fill: Numeric distribution + Explicit missing-value fill for supplied customer segment observations records (account_count, revenue_amount). 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 numeric distribution report for the specified field (account_count or revenue_amount) covering statistics such as min, max, mean, median, and spread across the supplied rows; (2) a missing-value fill report showing original null positions and their imputed replacements using the chosen method (zero, mean, or median). Both reports are computed locally on the supplied data with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/customer-segment-observations-numeric-distribution-missing-value-fill-3aaa5923/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)