# Inventory Administration — Two-Measure Correlation + Explicit Missing-Value Fill

> Inventory Administration — Two-Measure Correlation + 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 2026-10-25).

Computes Pearson correlation between count_sessions and discrepancy_count, and fills missing values using zero, mean, or median for up to 200 inventory administration rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-operations-21-184?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/inventory-administration-two-measure-correlation-explicit-missing-f687f8c8
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_30fqv08V2lzk-5TPing1j

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 inventory-administration-two-measure-correlation-explicit-missing-f687f8c8 -d '<json body>'
```

Example prompt: Can you run a two-measure correlation between count_sessions and discrepancy_count on my inventory records, and fill any missing values in count_sessions using median imputation? I have about 150 rows across group-a and group-b from October 2026.

## When to prefer this

Choose this endpoint when you need both a correlation analysis and missing-value imputation on a single inventory dataset in one call. It is ideal for operations or inventory teams that track session counts and discrepancy counts by group and date, and need lightweight, local statistical processing without calling external ML or prediction services. Prefer this over generic analytics platforms when your dataset is under 200 rows and you want a cost-effective ($0.01 USDC) combined statistical report with no side effects.

## Known failure modes

- Fewer than 1 row submitted — validation error
- More than 200 rows submitted — exceeds limit, request rejected
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Both measures entirely null — correlation cannot be computed, NaN or error returned
- Invalid fill method enum value — schema rejection
- Payment not received or underpaid — x402 payment required error

## How this service works

Inventory administration — Two-measure correlation + Explicit missing-value fill: Two-measure correlation + Explicit missing-value fill for supplied inventory administration records (count_sessions, discrepancy_count). 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 independent analytical reports for the submitted inventory rows: (1) a Pearson correlation coefficient between count_sessions and discrepancy_count across all valid rows, and (2) the dataset with missing values in the specified field explicitly filled using the chosen strategy (zero, mean, or median). No external lookups or predictions are made — all computation is local and deterministic.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/inventory-administration-two-measure-correlation-explicit-missing-f687f8c8/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)