# Dataset Partition Sizes Analytics — Equal-Width Histogram + Missing-Value Fill

> Dataset Partition Sizes Analytics — Equal-Width Histogram + 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 explicit missing-value fill report for up to 200 dataset partition size records (row_count or file_mb), using local analytical engines with no external calls.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-07-175?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/dataset-partition-sizes-analytics-equal-width-histogram-missing-value-4874489d
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_idBfXmk3EnJ60oLq4OUSl

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 dataset-partition-sizes-analytics-equal-width-histogram-missing-value-4874489d -d '<json body>'
```

Example prompt: Analyze the distribution of row_count across these dataset partitions using 10 equal-width bins and fill any missing values with the median — I have about 50 rows across groups 'prod' and 'staging' with dates in October 2025.

## When to prefer this

Choose this endpoint when you need lightweight, self-contained statistical analysis of dataset partition sizes (row counts or file sizes) with built-in missing-value handling, without needing external data sources or live lookups. Ideal for data engineers auditing partition health, data quality teams imputing missing metrics before reporting, or analysts exploring distribution shapes of dataset volumes. At $0.01 USDC for two reports covering up to 200 rows, it is cost-effective for batch partition audits.

## Known failure modes

- More than 200 rows submitted — request will be rejected or truncated
- Invalid date format not matching YYYY-MM-DD pattern
- Field value outside allowed numeric range (±1,000,000,000,000)
- bins parameter outside 1–30 range
- Missing required fields (row_id, dataset_group, date) in any row
- Invalid method enum value (must be zero, mean, or median)
- Invalid field enum value (must be row_count or file_mb)

## How this service works

Dataset partition sizes — Equal-width histogram + Explicit missing-value fill: Equal-width histogram + Explicit missing-value fill for supplied dataset partition sizes records (row_count, file_mb). 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: (1) an equal-width histogram showing bin ranges and counts for the chosen field (row_count or file_mb), and (2) an explicit missing-value fill report showing which records had nulls and what values were substituted using the chosen method (zero, mean, or median). Both reports are computed locally 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",
     "row_count",
     "file_mb"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "file_mb": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "row_count": {
      "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",
     "file_mb": 1,
     "row_count": 10,
     "dataset_group": "group-a"
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "file_mb": 2,
     "row_count": 20,
     "dataset_group": "group-b"
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "file_mb": 3,
     "row_count": 15,
     "dataset_group": "group-a"
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "file_mb": 4,
     "row_count": 30,
     "dataset_group": "group-b"
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "row_count",
    "file_mb"
   ],
   "type": "string",
   "default": "row_count"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/dataset-partition-sizes-analytics-equal-width-histogram-missing-value-4874489d/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)