# Account Research Coverage — Two-Measure Correlation + Date by Category Pivot

> Account Research Coverage — Two-Measure Correlation + Date by Category Pivot 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).

Runs two analytical reports on supplied account research coverage data: a Pearson-style correlation between researched_accounts and target_accounts, and a date-by-category pivot table.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-08-182?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/account-research-coverage-two-measure-correlation-date-by-category-dabb6f78
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_ULbAgT9nlPkQwvpmtar6g

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 account-research-coverage-two-measure-correlation-date-by-category-dabb6f78 -d '<json body>'
```

Example prompt: I have account research coverage records for two company groups — group-a and group-b — tracked daily from October 1 to October 4, 2026, with researched_accounts and target_accounts counts per row. Can you run the two-measure correlation between researched_accounts and target_accounts, and also give me a date-by-category pivot for researched_accounts, for up to 4 rows?

## When to prefer this

Choose this endpoint when you have up to 200 rows of account research coverage data with researched_accounts and target_accounts fields, and you need both a pairwise correlation between those two measures AND a date-by-category pivot in a single low-cost call ($0.01 USDC). Prefer this over general BI tools when you want a lightweight, self-contained analytical result without setting up a data warehouse or running live queries.

## Known failure modes

- Fewer than 1 row submitted — validation error
- More than 200 rows submitted — request rejected
- Missing required fields (row_id, date, company_group) — schema validation error
- Invalid date format (not YYYY-MM-DD) — pattern validation error
- Numeric values outside allowed range (-1T to 1T) — validation error
- Null values in both measures — correlation may be undefined or NaN

## How this service works

Account research coverage — Two-measure correlation + Date by category pivot: Two-measure correlation + Date by category pivot for supplied account research coverage records (researched_accounts, target_accounts). 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: (1) a correlation report showing the statistical relationship between the researched_accounts and target_accounts measures across all supplied rows, and (2) a date-by-category pivot table aggregating the selected measure (researched_accounts or target_accounts) broken down by date and company_group category. Both reports are computed locally on the supplied data with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/account-research-coverage-two-measure-correlation-date-by-category-dabb6f78/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)