# Data Reconciliation — Equal-Width Histogram + Explicit Missing-Value Fill

> Data Reconciliation — Equal-Width Histogram + 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 2026-10-19).

Generates an equal-width histogram and fills missing values (zero/mean/median) for source_total and target_total reconciliation data across up to 200 rows, producing 2 analytical reports locally.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-11-175?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/data-reconciliation-equal-width-histogram-explicit-missing-value-fill-f03c1bc9
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_olffeObGdOjfwQWGFJuUx

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 data-reconciliation-equal-width-histogram-explicit-missing-value-fill-f03c1bc9 -d '<json body>'
```

Example prompt: I have 150 rows of reconciliation data with source_total and target_total values — some nulls — can you build an equal-width histogram with 10 bins for source_total and fill the missing values using median imputation?

## When to prefer this

Choose this endpoint when you need a lightweight, offline-style analytical report combining histogram bin distribution and missing-value imputation for reconciliation data (source_total vs target_total) without any external data lookups or live predictions. Ideal for pre-analysis data quality checks, audit prep, and distribution visualization for up to 200 rows at very low cost ($0.01 for 2 reports). Prefer this over general BI tools when you want a quick, deterministic local computation on structured reconciliation records.

## Known failure modes

- More than 200 rows submitted — schema enforces maxItems:200, excess rows will be rejected
- Invalid date format (must match YYYY-MM-DD pattern) — returns validation error
- bins value outside 1–30 range — rejected by schema
- source_total or target_total outside ±1,000,000,000,000 — rejected by schema
- Missing required fields (row_id, dataset_group, date) — validation error
- Empty rows array — minItems:1 enforced
- Invalid method enum value — only zero, mean, median accepted
- Invalid field enum — only source_total or target_total accepted

## How this service works

Data reconciliation — Equal-width histogram + Explicit missing-value fill: Equal-width histogram + Explicit missing-value fill for supplied data reconciliation records (source_total, target_total). 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: (1) an equal-width histogram of the specified field (source_total or target_total) divided into the requested number of bins, showing frequency distribution; (2) a missing-value fill report where nulls in the specified field are replaced using the chosen method (zero, mean, or median), applied to up to 200 input reconciliation rows. All computation is local with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "bins": {
   "type": "integer",
   "default": 5,
   "maximum": 30,
   "minimum": 1
  },
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "source_total",
     "target_total"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "source_total": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "target_total": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "source_total": 10,
     "target_total": 1,
     "dataset_group": "group-a"
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "source_total": 20,
     "target_total": 2,
     "dataset_group": "group-b"
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "source_total": 15,
     "target_total": 3,
     "dataset_group": "group-a"
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "source_total": 30,
     "target_total": 4,
     "dataset_group": "group-b"
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "source_total",
    "target_total"
   ],
   "type": "string",
   "default": "source_total"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/data-reconciliation-equal-width-histogram-explicit-missing-value-fill-f03c1bc9/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)