# Newsroom Assignments Weighted Mean & Missing-Value Fill

> Newsroom Assignments Weighted Mean & 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 2026-11-02).

Computes a secondary-measure weighted mean and fills missing values for newsroom assignment records (assigned_items, completed_items) across up to 200 rows, producing 2 analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-news-03-187?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-11-02
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/newsroom-assignments-weighted-mean-missing-value-fill-a650c881
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_IqtTKW611BqbCNNdpH_5i

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 newsroom-assignments-weighted-mean-missing-value-fill-a650c881 -d '<json body>'
```

Example prompt: Can you calculate the secondary-measure weighted mean and fill any missing values for my newsroom assignment data — I have 4 rows with channel groups 'group-a' and 'group-b', dates from 2026-10-01 to 2026-10-04, assigned_items and completed_items values, and I want to analyze the assigned_items field using median fill for nulls?

## When to prefer this

Choose this endpoint when you have structured newsroom assignment data (up to 200 rows) and need both a weighted mean computation and missing-value imputation in a single $0.01 call. Ideal for editorial analytics pipelines where assigned_items or completed_items contain nulls and you need clean aggregated statistics. Prefer over general-purpose computation tools when working specifically with channel-grouped, date-indexed newsroom assignment records and need two bundled reports at minimal cost.

## Known failure modes

- Rows array empty or exceeds 200-item limit — request rejected
- Invalid date format (not YYYY-MM-DD) — validation error
- Field value not in enum ['assigned_items','completed_items'] — rejected
- Method value not in enum ['zero','mean','median'] — rejected
- Numeric values outside ±1,000,000,000,000 range — rejected
- Missing required fields (row_id, channel_group, date) — validation error
- Payment of 0.01 USDC not provided — 402 response

## How this service works

Newsroom assignments — Secondary-measure weighted mean + Explicit missing-value fill: Secondary-measure weighted mean + Explicit missing-value fill for supplied newsroom assignments records (assigned_items, completed_items). 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 2 analytical reports covering: (1) secondary-measure weighted mean computed over the specified field (assigned_items or completed_items) across all provided rows, and (2) explicit missing-value fill results using the chosen method (zero, mean, or median), applied to the same dataset of up to 200 rows.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/newsroom-assignments-weighted-mean-missing-value-fill-a650c881/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)