# Transaction Fee Observations — Two-Measure Correlation + Explicit Missing-Value Fill

> Transaction Fee Observations — 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 2026-10-28).

Computes Pearson/Spearman correlation between fee_units and transaction_count, and fills missing values using zero, mean, or median imputation, for up to 200 rows of transaction fee data.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-finance-03-184?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-28
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/transaction-fee-observations-two-measure-correlation-explicit-missing-00347c66
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_h_98MFQCirOtbyvyRHCa0

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 transaction-fee-observations-two-measure-correlation-explicit-missing-00347c66 -d '<json body>'
```

Example prompt: I have 50 rows of transaction fee observations with some nulls in fee_units — can you fill those missing values using median imputation and also compute the correlation between fee_units and transaction_count for me? Here's the data with row_id, instrument_group, date, fee_units, and transaction_count columns.

## When to prefer this

Choose this endpoint when you need both missing-value imputation and two-measure correlation computed together in a single $0.01 call on up to 200 rows of transaction fee data, without requiring any external data sources or live market lookups. It is ideal for pre-report data cleaning workflows, audit preparation, or exploratory analysis of fee-volume relationships where the data is already in hand.

## Known failure modes

- Fewer than 1 row supplied — minimum row count not met
- More than 200 rows submitted — exceeds maximum batch size
- Invalid date format (must match YYYY-MM-DD pattern)
- fee_units or transaction_count values outside the allowed range (-1,000,000,000,000 to 1,000,000,000,000)
- Missing required fields (row_id, instrument_group, date) on any row
- Invalid imputation method enum value (must be zero, mean, or median)
- Payment failure or insufficient USDC balance for the $0.01 call

## How this service works

Transaction fee observations — Two-measure correlation + Explicit missing-value fill: Two-measure correlation + Explicit missing-value fill for supplied transaction fee observations records (fee_units, transaction_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 analytical reports: (1) a correlation result quantifying the statistical relationship between fee_units and transaction_count across the supplied rows, and (2) a missing-value fill report where null entries in the specified field are replaced using the chosen method (zero, mean, or median), all 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",
     "instrument_group",
     "date",
     "fee_units",
     "transaction_count"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "fee_units": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "instrument_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "transaction_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "fee_units": 10,
     "instrument_group": "group-a",
     "transaction_count": 1
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "fee_units": 20,
     "instrument_group": "group-b",
     "transaction_count": 2
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "fee_units": 15,
     "instrument_group": "group-a",
     "transaction_count": 3
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "fee_units": 30,
     "instrument_group": "group-b",
     "transaction_count": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "fee_units",
    "transaction_count"
   ],
   "type": "string",
   "default": "fee_units"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/transaction-fee-observations-two-measure-correlation-explicit-missing-00347c66/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)