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Null Coverage — String Normalisation + Equal-Width Histogram
x402
Null Coverage — 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 2026-10-18).
Runs two local analytical reports — string normalisation and an equal-width histogram — on null coverage records (missing_values, total_values) for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Null coverage — String normalisation + Equal-width histogram: String normalisation + Equal-width histogram 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 two independent analytical reports: (1) a string normalisation report showing standardised representations of the chosen field values, and (2) an equal-width histogram report with bin edges, bin counts, and distribution summary — all computed locally without any external lookups or predictions.
Example use cases
Data completeness audit for pipeline
“I have 150 rows of daily null coverage data with missing_values and total_values fields. Can you normalize the missing_values strings and give me a 10-bin equal-width histogram so I can see how data completeness is distributed?”
Histogram of total values across groups
“Run a string normalisation and equal-width histogram report on my dataset — I want to analyze the total_values field across two dataset groups over the past month, use 8 bins please.”
Missing value distribution for QA report
“For our QA review, can you normalize the missing_values field and produce a 5-bin histogram across our 80 null coverage records? I need to see where the bulk of missing data is concentrated.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-03-031?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need two lightweight analytical reports — string normalisation plus a histogram — specifically on null coverage data (missing_values and total_values fields), all computed locally without any external API calls, predictions, or professional assessments. It is ideal for data quality pipelines, QA workflows, or profiling jobs where you want a cheap, fast, self-contained analysis of up to 200 rows for $0.01 USDC.
Side effects
- Rows array is empty or exceeds 200 items — validation error
- missing_values or total_values contain values outside ±1,000,000,000,000 — rejected
- bins parameter set outside 1–30 range — validation error
- Required row fields (row_id, date, dataset_group) missing or malformed — schema error
- Date strings not matching YYYY-MM-DD pattern — pattern validation failure
- field enum value not one of 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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