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Null Coverage Analytics — Base-100 Series & Equal-Width Histogram
x402
Null Coverage Analytics — Base-100 Series & 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).
Computes a Base-100 index series and an equal-width histogram for null coverage data (missing_values, total_values) across up to 200 supplied rows, returning two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Null coverage — Base-100 series + Equal-width histogram: Base-100 series + 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 analytical reports: (1) a Base-100 index series showing the selected field's values normalized relative to the baseline row, and (2) an equal-width histogram breaking the selected field's distribution into the specified number of bins with counts per bin. Both reports are computed locally from the supplied data with no external lookups.
Example use cases
Missing data trend indexed over time
“I have 80 rows of daily dataset records with missing_values and total_values across two groups. Can you compute a Base-100 index series starting from row 0 on the missing_values field and also give me a 5-bin histogram so I can see how null coverage is distributed?”
Histogram of total values across datasets
“Run an equal-width histogram with 8 bins on the total_values field for my dataset records — I have 120 rows with row_id, dataset_group, date, missing_values, and total_values — and include the Base-100 series indexed from the first row.”
Data completeness audit across groups
“I need to audit null coverage across my pipeline datasets. Can you take these 200 rows and give me both a Base-100 normalized series and a 15-bin histogram on missing_values so I can spot which ranges have the worst data quality?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-03-163?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 both a normalized trend index and a distributional histogram in one call. It is ideal for data quality audits, pipeline monitoring summaries, or completeness reporting where you already have the raw counts and want fast local statistical summaries without any external data enrichment or prediction.
Side effects
- More than 200 rows supplied — request rejected (maxItems: 200)
- Missing required row fields (row_id, dataset_group, date, missing_values, total_values) — validation error
- bins parameter out of range (must be 1–30) — rejected
- base_index out of range (must be 0–199) — rejected
- All values are null/missing for the selected field — histogram may be empty or degenerate
- Non-date-formatted date strings — pattern validation failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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