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Customer Segment Observations — Equal-Width Histogram + IQR Outlier Flags
x402
Customer Segment Observations — Equal-Width Histogram + IQR Outlier Flags is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-16).
Computes equal-width histogram distribution and IQR-based outlier flags for customer segment observation records (account_count or revenue_amount) across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Customer segment observations — Equal-width histogram + IQR outlier flags: Equal-width histogram + IQR outlier flags 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) an equal-width histogram showing how values of the selected field (account_count or revenue_amount) are distributed across the specified number of bins, and (2) IQR-based outlier flags identifying which rows fall outside the interquartile range boundaries. Both reports are generated from the supplied row data using local analytical engines with no external lookups.
Example use cases
Detecting revenue outliers in sales segments
“I have 150 rows of customer segment data with company groups and monthly revenue figures — can you run the IQR outlier detection and equal-width histogram on the revenue_amount field using 8 bins so I can spot which segments are behaving unusually?”
Analyzing account count distribution across groups
“Take these 80 customer segment records with account_count values and give me the equal-width histogram with 5 bins plus flag any IQR outliers in account_count — I want to understand how account volume is distributed across my company groups.”
Quarterly segment audit for business review
“Before our Q4 business review, can you run the histogram and IQR outlier analysis on this batch of 200 customer segment observations for the revenue_amount field with 10 bins? I need to know which data points are statistical outliers.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-16-170?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 customer segment observation records and need both a distribution histogram and IQR outlier detection in a single paid call for either account_count or revenue_amount fields. It is well-suited for lightweight, self-contained statistical QA on tabular customer segment data without needing an external analytics platform.
Side effects
- More than 200 rows submitted — exceeds maxItems limit
- Invalid date format in rows — must match YYYY-MM-DD pattern
- Missing required row fields (row_id, company_group, date, account_count, revenue_amount)
- Bin count outside 1–30 range
- Invalid field selector — must be 'account_count' or 'revenue_amount'
- Null values in the selected numeric field may affect histogram or IQR calculations
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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