# Water Service Coverage — Date×Category Pivot + Missing-Value Fill

> Water Service Coverage — Date×Category Pivot + 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).

Pivots water service coverage records by date and region category, then fills missing values using zero, mean, or median imputation — returning two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-economics-19-189?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/water-service-coverage-date-category-pivot-missing-value-fill-80d51aba
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_LigbanxdphX8ANSg8PWWs

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 water-service-coverage-date-category-pivot-missing-value-fill-80d51aba -d '<json body>'
```

Example prompt: I have 50 rows of water service coverage data with region, date, served_households, and total_households columns — can you pivot them by date and category, then fill any missing served_households values using the median?

## When to prefer this

Choose this endpoint when you have tabular water service coverage records (served_households, total_households) that need to be pivoted by date and region category AND have missing values filled — all in a single paid call. It is ideal for utility data preprocessing pipelines, coverage gap reporting, and dashboard data preparation where both reshaping and imputation are needed together without external lookups or predictions.

## Known failure modes

- Input rows exceed 200 — request rejected with validation error
- Row missing required fields (row_id, region, date, served_households, total_households) — schema validation failure
- Date field does not match YYYY-MM-DD pattern — rejected with pattern error
- Field or method enum value not recognized — validation error
- All values are null for a column — mean/median imputation may return null or zero
- Payment of 0.01 USDC not completed — request blocked by x402 payment gate

## How this service works

Water service coverage — Date by category pivot + Explicit missing-value fill: Date by category pivot + Explicit missing-value fill for supplied water service coverage records (served_households, total_households). 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 structured analytical reports: (1) a date-by-category pivot table for the chosen field (served_households or total_households), and (2) the same dataset with missing values explicitly filled using the selected method (zero, mean, or median). Covers up to 200 input rows per call.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/water-service-coverage-date-category-pivot-missing-value-fill-80d51aba/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)