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Null Coverage Analytics: Equal-Width Histogram + IQR Outlier Flags
x402
Null Coverage Analytics: 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 2026-10-14).
Generates an equal-width histogram and IQR-based outlier flags for null coverage data (missing_values or total_values) across up to 200 supplied rows, returning 2 independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Null coverage — Equal-width histogram + IQR outlier flags: Equal-width histogram + IQR outlier flags for supplied null coverage records (missing_values, total_values). 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 2 independent analytical reports: (1) an equal-width histogram dividing the chosen field (missing_values or total_values) into the specified number of bins with row counts per bin, and (2) an IQR-based outlier report flagging rows whose values fall below Q1-1.5*IQR or above Q3+1.5*IQR. All analysis is performed locally on supplied data with no external lookups.
Example use cases
Daily data quality audit
“I have 150 rows of daily null coverage records across 8 dataset groups from last month — can you build a 10-bin histogram and flag any IQR outliers in the missing_values field so I can see which days had abnormal null rates?”
Comparing total values distribution
“Run a histogram with 8 bins on the total_values field for these 50 dataset records and highlight any rows that fall outside the IQR bounds — I want to spot datasets that are unusually large or small.”
Weekly missing data anomaly detection
“Here are 200 rows of null coverage data across groups A, B, and C for the past quarter — use 15 bins and flag IQR outliers on missing_values so I can identify which dataset groups consistently have data quality problems.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-03-170?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have pre-collected null coverage records (missing_values and total_values per row) and need fast, local statistical profiling — specifically an equal-width histogram plus IQR outlier detection — without any external data lookups, predictions, or live data sources. Best suited for batch data quality audits of up to 200 rows where you want two complementary views (distribution shape + anomaly flags) in a single call at minimal cost.
Side effects
- rows array exceeds 200 items — request rejected
- missing required fields (row_id, missing_values, total_values, date, dataset_group) in any row — validation error
- bins value outside 1-30 range — validation error
- invalid date format (not YYYY-MM-DD) — schema rejection
- null values in the target field may affect IQR computation
- field enum value not 'missing_values' or 'total_values' — rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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