# Customer Segment Observations — Base-100 Series + Explicit Missing-Value Fill

> Customer Segment Observations — Base-100 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 2026-10-16).

Indexes customer segment time-series data to a base-100 scale and fills missing values in account_count or revenue_amount fields using zero, mean, or median imputation — up to 200 rows, two reports per call.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-16-169?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-16
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/customer-segment-observations-base-100-series-explicit-missing-value-953e783d
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_U1kjX4X6A65urSJljj2kw

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-base-100-series-explicit-missing-value-953e783d -d '<json body>'
```

Example prompt: I have customer segment data with dates, account counts, and revenue amounts for group-a and group-b — can you index account_count to base-100 starting from row 0 and fill any missing values using median imputation? I have about 50 rows.

## When to prefer this

Choose this endpoint when you need both base-100 series normalization and missing-value imputation applied to customer segment data (account_count or revenue_amount) in a single low-cost call. It is ideal for preprocessing up to 200 rows of time-series segment observations before charting or reporting, requiring no external data sources or live lookups. Prefer alternatives if you need string normalization, deduplication, correlation, or histogram analysis — those are handled by sibling endpoints on the same platform.

## Known failure modes

- Fewer than 1 row supplied — request rejected
- More than 200 rows submitted — request rejected, maxItems exceeded
- base_index references a row position outside the supplied row count — indexing fails
- Invalid date format (not YYYY-MM-DD) on any row — schema validation error
- Field value outside the allowed numeric range (±1 trillion) — validation rejection
- Unsupported method enum value — schema validation error

## How this service works

Customer segment observations — Base-100 series + Explicit missing-value fill: Base-100 series + 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: one showing the base-100 indexed series for the selected field (account_count or revenue_amount) anchored at the specified base_index row, and one showing the dataset with missing values explicitly filled using the chosen method (zero, mean, or median). Both reports are computed locally from the supplied rows 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"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/customer-segment-observations-base-100-series-explicit-missing-value-953e783d/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)