# Social Post Observations — Adjacent Row Changes + Explicit Missing-Value Fill

> Social Post Observations — Adjacent Row Changes + 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 2026-10-24).

Computes adjacent-row changes and fills missing values (impressions or engagement_count) for up to 200 social post observation records using local analytical engines.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-news-13-162?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-24
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/social-post-observations-adjacent-row-changes-explicit-missing-value-64b5e3dc
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_fAZ-V-GyuTVoF0wvug7QE

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 social-post-observations-adjacent-row-changes-explicit-missing-value-64b5e3dc -d '<json body>'
```

Example prompt: I have 150 rows of social post data with dates, channel groups, impressions, and engagement counts — some impressions values are missing. Can you compute the adjacent row changes for impressions and fill the missing impressions values using median, across all rows?

## When to prefer this

Choose this endpoint when you have social post observation data (with impressions and/or engagement_count fields) that needs row-over-row delta analysis and missing-value imputation in a single, low-cost call. It is ideal for data cleaning and trend-detection pipelines where you need both change detection and gap-filling without external lookups or predictions, and where your dataset fits within 200 rows.

## Known failure modes

- More than 200 rows submitted — request rejected due to maxItems constraint
- Invalid date format (not YYYY-MM-DD) — validation error
- Missing required fields (row_id, channel_group, date) — schema validation failure
- Field value out of allowed numeric range — validation error
- Invalid enum value for 'field' or 'method' — rejected

## How this service works

Social post observations — Adjacent row changes + Explicit missing-value fill: Adjacent row changes + Explicit missing-value fill for supplied social post observations records (impressions, engagement_count). 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) an adjacent row changes report showing the delta between consecutive rows for the specified field (impressions or engagement_count), and (2) an explicit missing-value fill report where nulls in the target field are replaced using the chosen method (zero, mean, or median). Both reports operate on the supplied dataset of up to 200 social post observation rows.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/social-post-observations-adjacent-row-changes-explicit-missing-value-64b5e3dc/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)