# Competitor Supplied Prices — Daily Sum Series + Explicit Missing-Value Fill

> Competitor Supplied Prices — Daily Sum 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 2026-10-19).

Computes daily sum time series for competitor supplied price data (list_price or package_quantity) and fills missing values using zero, mean, or median imputation, returning two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-07-145?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/competitor-supplied-prices-daily-sum-series-explicit-missing-value-fill-c2bb6a06
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_GV9JT12Cs9VsKRCJei6_P

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-daily-sum-series-explicit-missing-value-fill-c2bb6a06 -d '<json body>'
```

Example prompt: I have competitor pricing records with some missing list_price values — can you compute the daily sum time series for list_price across all company groups and fill any missing values using median imputation? I have about 50 rows spanning October 2026.

## When to prefer this

Choose this endpoint when you have pre-collected competitor pricing data (list_price and/or package_quantity) with potential gaps that need imputation, and you want both a daily sum time series aggregation and explicit missing-value fill in a single low-cost call. It is best suited for offline batch analytical tasks on up to 200 rows of tabular pricing records, not for live price lookups or predictions.

## Known failure modes

- Exceeds 200 row limit — request rejected with validation error
- Invalid date format (not YYYY-MM-DD) — schema pattern validation failure
- Missing required fields (row_id, company_group, date) — object validation error
- Invalid field enum value — must be 'list_price' or 'package_quantity'
- Invalid method enum value — must be 'zero', 'mean', or 'median'
- Empty rows array — minItems:1 constraint violation
- Payment failure — x402 payment of 0.01 USDC not processed

## How this service works

Competitor supplied prices — Daily sum series + Explicit missing-value fill: Daily sum series + 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 local analytical reports: (1) a daily sum time series for the chosen field (list_price or package_quantity) aggregated across the supplied rows, and (2) an explicit missing-value fill report showing imputed values using the selected method (zero, mean, or median). Up to 200 input rows are supported per call.

## 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-daily-sum-series-explicit-missing-value-fill-c2bb6a06/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)