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Customer Segment Observations — String Normalisation + Explicit Missing-Value Fill
x402
Customer Segment Observations — String Normalisation + 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 2026-10-25).
Normalises string fields and fills missing values (account_count, revenue_amount) in customer segment observation records using zero, mean, or median imputation, returning two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Customer segment observations — String normalisation + Explicit missing-value fill: String normalisation + Explicit missing-value fill for supplied customer segment observations records (account_count, revenue_amount). 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 per call covering: (1) string-normalised company_group fields and (2) explicitly filled missing values for the chosen numeric field (account_count or revenue_amount) using the specified method (zero, mean, or median), applied across up to 200 input rows. No external lookups or predictions are included.
Example use cases
Imputing missing revenue in segment data
“I have 120 customer segment rows with some null revenue_amount entries. Can you fill those missing values using median imputation and also normalise the company_group strings for me?”
Zero-filling missing account counts
“My segment observation dataset has blank account_count values scattered across about 80 rows. Please fill those nulls with zero and clean up the company group labels.”
Pre-analysis data prep for segment report
“Before I run my segment analysis, I need to clean the data — normalise company_group text and use mean imputation on the account_count field across my 200 customer segment records.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-16-037?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need lightweight, local, deterministic data cleaning on customer segment observation records — specifically string normalisation of categorical fields (company_group) combined with missing-value imputation for numeric metrics (account_count or revenue_amount). Ideal for preprocessing pipelines where you want two bundled reports at low cost ($0.01) without any external API calls, predictions, or live data lookups, and your dataset fits within 200 rows.
Side effects
- More than 200 rows submitted — exceeds maxItems limit
- Invalid date format (not YYYY-MM-DD) causes validation error
- row_id missing or empty string fails minLength constraint
- Invalid method value outside zero/mean/median enum
- Invalid field value outside account_count/revenue_amount enum
- Numeric values outside ±1,000,000,000,000 range rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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