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Customer Segment Observations — String Normalisation + Equal-Width Histogram
x402
Customer Segment Observations — String Normalisation + 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 2026-10-25).
Normalises string fields and computes equal-width histograms for account_count or revenue_amount across up to 200 customer segment observation rows, returning two local analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Customer segment observations — String normalisation + Equal-width histogram: String normalisation + Equal-width histogram 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 analytical reports: (1) a string normalisation report showing cleaned/standardised string field values for company_group and date columns, and (2) an equal-width histogram report showing bin edges, bin widths, and observation counts per bin for the selected numeric field (account_count or revenue_amount), computed locally without external lookups.
Example use cases
Revenue distribution across customer groups
“I have 120 rows of customer segment data with account_count and revenue_amount. Can you normalise the strings and give me a 10-bin equal-width histogram on revenue_amount so I can see how revenue is distributed across segments?”
Account count frequency bucketing
“Run string normalisation and build a 5-bin equal-width histogram on account_count for my customer segment observation records — I've got about 80 rows with company_group, date, account_count, and revenue_amount fields.”
Segment data quality and distribution check
“I need to clean up the string fields in my customer segment dataset and see how account_count values spread across equal-width buckets — can you do string normalisation plus a 7-bin histogram on account_count for these 200 rows?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-16-031?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both string normalisation and equal-width histogram analysis on customer segment data (account_count or revenue_amount) in a single call at low cost ($0.01 USDC for both reports). It is ideal for offline/local analytical processing of up to 200 rows without requiring live data lookups, predictions, or external integrations. Prefer it over general-purpose analytics when you specifically need equal-width binning (as opposed to equal-frequency/quantile binning) and string standardisation together.
Side effects
- More than 200 rows submitted — request exceeds row limit
- Invalid date format (not YYYY-MM-DD) — validation error
- bins value outside 1–30 range — rejected by schema
- Missing required fields (row_id, company_group, date, account_count, revenue_amount) — schema validation failure
- Numeric values outside ±1,000,000,000,000 range — rejected
- Empty rows array — minItems constraint violation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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