# Savings Ledger — Secondary-Measure Weighted Mean + Explicit Missing-Value Fill

> Savings Ledger — Secondary-Measure Weighted Mean + 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 2026-10-30).

Computes a secondary-measure weighted mean and fills missing values in savings ledger records (deposit_amount, withdrawal_amount) for up to 200 rows, returning 2 analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-finance-23-187?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-30
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/savings-ledger-secondary-measure-weighted-mean-explicit-missing-value-37ac0fea
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_H5rvnA7OUQoc-ChwfCrhC

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 savings-ledger-secondary-measure-weighted-mean-explicit-missing-value-37ac0fea -d '<json body>'
```

Example prompt: I have a savings ledger with up to 200 rows including deposit_amount and withdrawal_amount fields — some values are missing. Can you fill the missing deposit_amount values using median imputation and then compute a secondary-measure weighted mean across the rows, grouped by instrument_group?

## When to prefer this

Choose this endpoint when you have savings ledger data (deposit/withdrawal records) with missing numeric values and need both missing-value imputation and a secondary-measure weighted mean in a single call. It is ideal for offline/batch statistical analysis of up to 200 rows at low cost ($0.01 USDC for 2 reports). Prefer this over general-purpose analytics tools when you specifically need weighted mean computation paired with structured missing-value fill on financial ledger data without any live lookup or external data dependency.

## Known failure modes

- More than 200 rows submitted — exceeds maxItems limit
- Missing required fields (row_id, instrument_group, date) in any row — validation error
- Invalid date format (not YYYY-MM-DD) — schema rejection
- Invalid enum value for field or method parameters
- All values for the target field are null — weighted mean may be undefined
- Numeric values outside the allowed range (±1,000,000,000,000) — validation error

## How this service works

Savings ledger — Secondary-measure weighted mean + Explicit missing-value fill: Secondary-measure weighted mean + Explicit missing-value fill for supplied savings ledger records (deposit_amount, withdrawal_amount). 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 per call: a secondary-measure weighted mean calculation and an explicit missing-value fill result for the specified field (deposit_amount or withdrawal_amount), computed locally across up to 200 supplied savings ledger rows. No external data is fetched or predicted.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/savings-ledger-secondary-measure-weighted-mean-explicit-missing-value-37ac0fea/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)