# Financial Statement String Normalisation & Missing-Value Fill

> Financial Statement String Normalisation & 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).

Normalises string fields and fills missing revenue or expense values (zero, mean, or median) in up to 200 financial statement rows, returning two analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-finance-22-037?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/financial-statement-string-normalisation-missing-value-fill-8dbecf55
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_AkFP3pMG63srrYaIr1yZO

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 financial-statement-string-normalisation-missing-value-fill-8dbecf55 -d '<json body>'
```

Example prompt: Can you clean up my financial statement rows by normalising the strings and filling any missing revenue_amount values using median imputation? I have about 50 rows with fields like row_id, instrument_group, date, revenue_amount, and expense_amount.

## When to prefer this

Choose this endpoint when you need a lightweight, low-cost ($0.01 USDC) local analytical operation to normalise string fields and fill missing revenue or expense values in financial statement rows (up to 200 rows) without any live data lookup, prediction, or external action. It is well-suited for preprocessing financial data before downstream analysis or reporting pipelines.

## Known failure modes

- More than 200 rows submitted — exceeds maxItems limit
- Missing required fields (row_id, instrument_group, date) cause validation errors
- Date strings not matching YYYY-MM-DD pattern are rejected
- Amount values outside ±1,000,000,000,000 are rejected
- Invalid enum value for field or method parameters causes a 400 error
- Empty rows array (minItems:1 violated) returns an error

## How this service works

Financial statement inputs — String normalisation + Explicit missing-value fill: String normalisation + Explicit missing-value fill for supplied financial statement inputs records (revenue_amount, expense_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 two independent analytical reports covering the supplied financial statement rows after string normalisation has been applied and missing values in the specified field (revenue_amount or expense_amount) have been explicitly filled using the chosen method (zero, mean, or median). No external lookups or live predictions are included.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/financial-statement-string-normalisation-missing-value-fill-8dbecf55/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)