# Time Series Completeness — Base-100 Series + Equal-Width Histogram

> Time Series Completeness — Base-100 Series + Equal-Width Histogram 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).

Generates a Base-100 index series and an equal-width histogram for time series completeness data (observed vs expected data points) supplied by the caller.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-16-163?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-base-100-series-equal-width-histogram-249b0921
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_edhkwl20I9DYbBpjd3huU

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-base-100-series-equal-width-histogram-249b0921 -d '<json body>'
```

Example prompt: I have daily completeness records for two dataset groups — for each row I have an observed_points and expected_points value. Can you run a Base-100 rebase starting from row index 0 and also generate a 5-bin equal-width histogram on the observed_points field? I'll supply up to 30 rows.

## When to prefer this

Choose this endpoint when you have already collected time series completeness records (observed vs expected data points) and need both a normalized Base-100 trend view and a frequency distribution histogram in a single call. It is ideal for offline or batch data quality analysis where no live data fetching, prediction, or external enrichment is needed. Prefer this over general-purpose analytics services when you want a low-cost ($0.01 USDC), self-contained dual-report for up to 200 rows of completeness data.

## Known failure modes

- Fewer than 1 or more than 200 rows submitted — rejected by schema validation
- base_index out of range (must be 0–199 and within actual row count)
- bins value outside 1–30 range — schema rejection
- Missing required row fields (row_id, date, observed_points, expected_points) — validation error
- Null values in observed_points or expected_points may affect histogram binning
- Invalid date format (must be YYYY-MM-DD) — schema rejection
- Payment failure via x402 protocol — request not processed

## How this service works

Time series completeness — Base-100 series + Equal-width histogram: Base-100 series + Equal-width histogram 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

Returns two analytical reports: (1) a Base-100 index series where each row's selected field value is rebased relative to the chosen base index row, and (2) an equal-width histogram dividing the selected field's value range into the specified number of bins with counts per bin. Both reports are computed locally from the supplied rows 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",
     "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"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/time-series-completeness-base-100-series-equal-width-histogram-249b0921/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)