# Market Survey Observations — Base-100 Series + Explicit Missing-Value Fill

> Market Survey Observations — Base-100 Series + Explicit 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).

Computes a base-100 indexed time series and fills missing values (zero, mean, or median) for market survey observation records containing respondent counts and sample weights.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-06-169?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/market-survey-observations-base-100-series-explicit-missing-value-fill-2c9d2636
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_VhD_uLy2piRCC2g1a4Sgl

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 market-survey-observations-base-100-series-explicit-missing-value-fill-2c9d2636 -d '<json body>'
```

Example prompt: I have market survey data with respondent counts and sample weights for groups A and B across October 2026 — can you normalize it to a base-100 series starting at row index 0 and fill any missing respondent_count values using median imputation?

## When to prefer this

Use this endpoint when you have tabular market survey data (up to 200 rows) with respondent_count or sample_weight fields and need both a base-100 normalized index series and explicit missing-value imputation in a single call. Prefer this over generic analytics tools when you want deterministic, reproducible local computation without live external lookups, and when your data is already structured with row_id, company_group, and date identifiers.

## Known failure modes

- Input array is empty (minItems:1 violated) — request rejected
- More than 200 rows submitted (maxItems:200 violated) — request rejected
- base_index out of bounds (exceeds number of rows minus 1) — may produce error or undefined base
- Invalid date format (must match YYYY-MM-DD) — validation error
- Field or method enum value not recognized — defaults applied or error returned
- All values for chosen field are null — base-100 computation may be undefined

## How this service works

Market survey observations — Base-100 series + Explicit missing-value fill: Base-100 series + Explicit missing-value fill for supplied market survey observations records (respondent_count, sample_weight). 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 indexed time series for the chosen field (respondent_count or sample_weight) anchored at the specified base index row, and (2) the same dataset with explicit missing-value fill applied using the chosen method (zero, mean, or median). Covers up to 200 input rows, processed locally without external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "company_group",
     "date",
     "respondent_count",
     "sample_weight"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "company_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "sample_weight": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "respondent_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "company_group": "group-a",
     "sample_weight": 1,
     "respondent_count": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "company_group": "group-b",
     "sample_weight": 2,
     "respondent_count": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "company_group": "group-a",
     "sample_weight": 3,
     "respondent_count": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "company_group": "group-b",
     "sample_weight": 4,
     "respondent_count": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "respondent_count",
    "sample_weight"
   ],
   "type": "string",
   "default": "respondent_count"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/market-survey-observations-base-100-series-explicit-missing-value-fill-2c9d2636/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)