# Time Series Completeness — Equal-Width Histogram + Missing-Value Fill

> Time Series Completeness — 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 2026-10-15).

Analyzes time series completeness records (observed vs expected data points) by building an equal-width histogram and filling missing values, producing two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-16-175?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/time-series-completeness-equal-width-histogram-missing-value-fill-72225836
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_XTcslDeKqQud_1Qragl88

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 time-series-completeness-equal-width-histogram-missing-value-fill-72225836 -d '<json body>'
```

Example prompt: Can you run an equal-width histogram with 10 bins and median missing-value fill on my time series completeness data — I have up to 50 rows each with a date, dataset_group, observed_points, and expected_points — and give me the two analytical reports?

## When to prefer this

Choose this endpoint when you need a fast, local statistical summary of time series completeness data — specifically an equal-width histogram and explicit missing-value fill — without any external data lookups or predictions. It is ideal for data quality pipelines, monitoring dashboards, or audit workflows where you supply up to 200 rows with observed and expected point counts and want two statistical reports for a flat $0.01 USDC fee. Prefer alternatives if you need real-time data fetching, forecasting, or more than 200 rows processed at once.

## Known failure modes

- More than 200 rows submitted — request will be rejected or truncated
- Invalid date format (not YYYY-MM-DD) causes row-level validation failure
- Bins value outside 1–30 range causes schema validation error
- All values in chosen field are null — fill and histogram may return degenerate results
- Missing required fields (row_id, date, observed_points, expected_points) cause row rejection
- Non-numeric values for observed_points or expected_points cause parsing errors

## How this service works

Time series completeness — Equal-width histogram + Explicit missing-value fill: Equal-width histogram + Explicit missing-value fill for supplied time series completeness records (observed_points, expected_points). 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 derived from the supplied completeness records: (1) an equal-width histogram distributing the chosen field (observed_points or expected_points) into the specified number of bins with counts per bin, and (2) a version of the series with missing values explicitly filled using the chosen method (zero, mean, or median). No external data is fetched; all computation is local.

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/time-series-completeness-equal-width-histogram-missing-value-fill-72225836/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)