# Competitor Supplied Prices — Numeric Distribution + Explicit Missing-Value Fill

> Competitor Supplied Prices — 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 2026-10-15).

Analyzes up to 200 rows of competitor price data by computing a numeric distribution report and filling missing values in list_price or package_quantity using zero, mean, or median imputation.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-07-085?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/competitor-supplied-prices-numeric-distribution-explicit-missing-0d43832d
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_LbP2ByS0x4clv57fKlDOf

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 competitor-supplied-prices-numeric-distribution-explicit-missing-0d43832d -d '<json body>'
```

Example prompt: I have up to 200 rows of competitor price data with company group, date, list_price, and package_quantity — some list_price values are null. Can you run a numeric distribution report on list_price and fill in the missing values using median imputation?

## When to prefer this

Choose this endpoint when you already have structured competitor pricing data (up to 200 rows) and need both a distribution summary and missing-value imputation in a single call, without requiring any live market lookup, external enrichment, or predictive modeling. It is ideal for data cleaning pipelines before exporting or visualizing competitor price data, especially when null values in list_price or package_quantity need to be handled systematically.

## Known failure modes

- Exceeding 200 rows causes a rejection or truncation error
- Invalid or missing row_id, company_group, or date fields cause schema validation failures
- Date strings not matching YYYY-MM-DD pattern are rejected
- Choosing an unsupported imputation method (not zero, mean, or median) causes an error
- All values in the target field being null may cause mean/median to be undefined
- Numeric values outside the allowed range cause validation errors
- Empty rows array returns an error due to minItems:1 constraint

## How this service works

Competitor supplied prices — Numeric distribution + Explicit missing-value fill: Numeric distribution + Explicit missing-value fill for supplied competitor supplied prices records (list_price, package_quantity). 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: (1) a numeric distribution summary of the selected field (list_price or package_quantity) across up to 200 supplied rows, and (2) a dataset with missing values in the selected field explicitly filled using the chosen method (zero, mean, or median). No external lookups or predictions are made — all computation is performed locally on the supplied data.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/competitor-supplied-prices-numeric-distribution-explicit-missing-0d43832d/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)