# Time Series Completeness — Category Frequencies + Equal-Width Histogram

> Time Series Completeness — Category Frequencies + 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 two analytical reports — category frequency counts and an equal-width histogram — for time series completeness data (observed vs. expected points) across up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-16-106?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-category-frequencies-equal-width-histogram-c328b83d
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_lBo96uKlITSBX-Q_iIKIL

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-category-frequencies-equal-width-histogram-c328b83d -d '<json body>'
```

Example prompt: Analyze my time series completeness data — I have up to 50 rows with dataset groups 'sensor-A' and 'sensor-B', dates, observed_points, and expected_points — give me category frequencies by group and a 10-bin equal-width histogram on observed_points.

## When to prefer this

Choose this endpoint when you have raw time series completeness records (observed vs. expected point counts) and need both a categorical frequency summary and a numeric distribution histogram in a single call for up to 200 rows. It is ideal for quick descriptive analytics on completeness data without needing an external analytics platform, database, or prediction service. Prefer it over general-purpose analytics APIs when working specifically with date-keyed, group-labeled completeness metrics and you want two complementary views — categorical and numeric distribution — returned together at minimal cost.

## Known failure modes

- Fewer than 1 or more than 200 rows supplied — rejected by schema validation
- Invalid date format (not YYYY-MM-DD) causes row-level schema error
- bins value outside 1–30 range rejected
- Null values in observed_points or expected_points may affect histogram computation
- Missing required row fields (row_id, date, observed_points, expected_points) cause validation failure
- Payment of 0.01 USDC not fulfilled — request blocked by x402 payment requirement

## How this service works

Time series completeness — Category frequencies + Equal-width histogram: Category frequencies + 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 independent analytical reports: (1) a category frequency table showing how often each dataset_group value appears in the supplied rows, and (2) an equal-width histogram dividing the selected numeric field (observed_points or expected_points) into up to 30 configurable bins with counts per bin. Both reports are computed locally on the supplied data, with no external lookups or predictions.

## 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"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/time-series-completeness-category-frequencies-equal-width-histogram-c328b83d/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)