# Time Series Completeness — Base-100 Series + Secondary-Measure Weighted Mean

> Time Series Completeness — Base-100 Series + Secondary-Measure Weighted Mean 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).

Computes a Base-100 index series and a secondary-measure weighted mean for time series completeness records (observed vs expected data points), returning two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-16-166?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-secondary-measure-weighted-304e7bc8
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_e_zjyC-iRUXzfBXzHyv-z

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-secondary-measure-weighted-304e7bc8 -d '<json body>'
```

Example prompt: Take my time series completeness records for group-a and group-b across October 2026 — with observed and expected point counts per row — and give me both a Base-100 index series anchored to row 0 and a secondary-measure weighted mean report for the observed_points field.

## When to prefer this

Choose this endpoint when you have pre-collected time series completeness data (observed vs expected point counts) and need two specific statistical outputs — a Base-100 normalized index series and a weighted mean — computed offline against your supplied rows. Ideal for data quality monitoring, pipeline completeness reporting, or audit scenarios where you own the data and need fast, deterministic analytics without external API calls or live data lookups. Not suitable for live data fetching, forecasting, or professional data assessments.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, date, observed_points, expected_points) cause rejection
- Invalid date format (not YYYY-MM-DD) triggers a schema validation error
- base_index value out of range (0–199) returns an error
- Null values in observed_points or expected_points may affect weighted mean accuracy
- Submitting fewer than 1 row returns an error

## How this service works

Time series completeness — Base-100 series + Secondary-measure weighted mean: Base-100 series + Secondary-measure weighted mean 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 normalizing each row's field value relative to the chosen base index row, and (2) a secondary-measure weighted mean computed across the supplied completeness records (observed_points and expected_points). Both reports are computed locally on the supplied data with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "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-secondary-measure-weighted-304e7bc8/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)