# Time Series Completeness — Daily Sum Series + Equal-Width Histogram

> Time Series Completeness — Daily Sum 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).

Analyzes time series completeness records by producing a daily sum series and an equal-width histogram for observed_points or expected_points, using local analytical engines on up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-16-139?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-daily-sum-series-equal-width-histogram-8d9a37ef
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_vUVmKtkGCcyhSh6VY3kvg

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-daily-sum-series-equal-width-histogram-8d9a37ef -d '<json body>'
```

Example prompt: I have 50 rows of time series completeness data with observed_points and expected_points for each date — can you compute the daily sum series and a 10-bin equal-width histogram for the observed_points field?

## When to prefer this

Choose this endpoint when you need both a time-aggregated daily sum series and a frequency distribution histogram from completeness records in a single call. It is ideal for data quality monitoring workflows where you want to assess both temporal trends and value spread of observed or expected data point counts. Prefer it over single-report alternatives when you need two complementary analytical views at once for up to 200 rows of completeness data.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, date, observed_points, expected_points) causes rejection
- Invalid date format (non-YYYY-MM-DD) fails schema validation
- Bin count outside 1–30 range is rejected
- Null values in the selected field may be excluded or cause partial results
- Values outside the allowed numeric range (-1e12 to 1e12) will be rejected

## How this service works

Time series completeness — Daily sum series + Equal-width histogram: Daily sum 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 daily sum series aggregating the selected field (observed_points or expected_points) by date, and (2) an equal-width histogram with the specified number of bins showing the frequency distribution of values across the dataset. Both reports are computed locally on the supplied rows without 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"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/time-series-completeness-daily-sum-series-equal-width-histogram-8d9a37ef/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)