# Transaction Fee Observations — Base-100 Rebase + Missing Value Fill

> Transaction Fee Observations — Base-100 Rebase + 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 2026-10-26).

Applies Base-100 index normalization and explicit missing-value imputation to user-supplied transaction fee observation records, returning two analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-finance-03-169?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-26
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/transaction-fee-observations-base-100-rebase-missing-value-fill-47e3c6eb
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_1slKCj6KY6-m91CjMUYSE

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-base-100-rebase-missing-value-fill-47e3c6eb -d '<json body>'
```

Example prompt: I have a dataset of daily transaction fee observations with some missing values — can you rebase the fee_units column to a base-100 index starting at row 0 and fill any missing values using the median, for up to 200 rows grouped by instrument?

## When to prefer this

Choose this endpoint when you have pre-collected transaction fee or count time series data and need both index normalization (Base-100 rebasing) and missing value imputation in a single low-cost call. Ideal for offline/batch analytical preparation of financial fee datasets before visualization or further modeling, where no live data lookup, prediction, or external action is needed.

## Known failure modes

- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, date, instrument_group) cause validation errors
- base_index out of range for the number of supplied rows
- All values in the target field are null — mean/median imputation may be undefined
- Malformed date strings not matching YYYY-MM-DD pattern fail validation
- Fee or count values outside ±1,000,000,000,000 are rejected

## How this service works

Transaction fee observations — Base-100 series + Explicit missing-value fill: Base-100 series + 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

Two analytical reports per call: (1) a Base-100 rebased series for the specified field (fee_units or transaction_count), indexed relative to the chosen base row; (2) an explicit missing-value-filled version of the same records using the selected imputation method (zero, mean, or median). Covers up to 200 input rows.

## 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"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/transaction-fee-observations-base-100-rebase-missing-value-fill-47e3c6eb/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)