{"uid":"cap_Q5mXFj1dPZ4eQrm3MNlFT","slug":"null-coverage-analytics-numeric-row-ordering-equal-width-histogram-dfd01e3f","name":"Null Coverage Analytics: Numeric Row Ordering + Equal-Width Histogram","description":"Null coverage — Numeric row ordering + Equal-width histogram: Numeric row ordering + 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.","url":"https://market.datapackvibe.com/x402/assistant-ib26-analytics-03-118?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"bins":{"type":"integer","default":5,"maximum":30,"minimum":1},"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","missing_values","total_values"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"total_values":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"missing_values":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","total_values":1,"dataset_group":"group-a","missing_values":10},{"date":"2026-10-02","row_id":"row-2","total_values":2,"dataset_group":"group-b","missing_values":20},{"date":"2026-10-03","row_id":"row-3","total_values":3,"dataset_group":"group-a","missing_values":15},{"date":"2026-10-04","row_id":"row-4","total_values":4,"dataset_group":"group-b","missing_values":30}],"maxItems":200,"minItems":1},"field":{"enum":["missing_values","total_values"],"type":"string","default":"missing_values"}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_d3aRFoAH6y90y6ZKfM4F_","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Analyzes user-supplied null coverage records (missing_values, total_values) by producing two local reports: a numeric row ordering and an equal-width histogram, for up to 200 rows.","exampleAgentPrompt":"Can you run a null coverage analysis on my dataset — sort the rows by missing_values and also give me an equal-width histogram with 10 bins? I have 4 rows: row-1 (group-a, 2026-10-01, 10 missing out of 100), row-2 (group-b, 2026-10-02, 20 missing out of 200), row-3 (group-a, 2026-10-03, 15 missing out of 150), row-4 (group-b, 2026-10-04, 30 missing out of 300).","exampleUseCases":[{"title":"Data quality audit by null rate","prompt":"I need to rank these 5 dataset groups by their missing_values and also see a histogram with 5 bins — here are my records: row-1 (group-a, 2026-01-01, 5 missing, 50 total), row-2 (group-b, 2026-01-02, 12 missing, 100 total), row-3 (group-c, 2026-01-03, 0 missing, 80 total), row-4 (group-a, 2026-01-04, 25 missing, 200 total), row-5 (group-b, 2026-01-05, 7 missing, 60 total). Analyze the missing_values field."},{"title":"ETL pipeline completeness check","prompt":"After our nightly ETL run I have 8 records with missing_values and total_values — can you order them numerically by missing_values and produce a 4-bin equal-width histogram so I can see where most of the gaps cluster? Records: row-1 group-etl 2026-03-01 missing=0 total=500, row-2 group-etl 2026-03-02 missing=50 total=500, row-3 group-etl 2026-03-03 missing=100 total=500, row-4 group-etl 2026-03-04 missing=200 total=500, row-5 group-etl 2026-03-05 missing=10 total=500, row-6 group-etl 2026-03-06 missing=75 total=500, row-7 group-etl 2026-03-07 missing=150 total=500, row-8 group-etl 2026-03-08 missing=300 total=500."},{"title":"Compare total_values spread across groups","prompt":"I want to analyze total_values instead of missing_values — can you sort my 6 rows by total_values and bin them into 3 equal-width buckets? Here are the rows: row-1 (group-x, 2026-06-01, missing=5, total=1000), row-2 (group-y, 2026-06-02, missing=10, total=250), row-3 (group-x, 2026-06-03, missing=2, total=5000), row-4 (group-y, 2026-06-04, missing=0, total=750), row-5 (group-z, 2026-06-05, missing=20, total=100), row-6 (group-z, 2026-06-06, missing=8, total=3000)."}],"resultDescription":"Returns two independent analytical reports computed locally: (1) a numeric row ordering of the selected field (missing_values or total_values) across the submitted rows, and (2) an equal-width histogram dividing the field's value range into the requested number of bins with counts per bin. No external lookups or predictions are made.","failureModes":["Fewer than 1 or more than 200 rows submitted — request rejected","Invalid date format (not YYYY-MM-DD) — validation error","bins parameter outside 1–30 range — validation error","null or missing row_id — validation error","field value not one of 'missing_values' or 'total_values' — validation error","Payment of 0.01 USDC not received — 402 response"],"whenToPreferThis":"Choose this endpoint when you have up to 200 records with null coverage metrics (missing_values, total_values) and need both a sorted row ordering and a histogram distribution in a single low-cost call. Ideal for lightweight data quality profiling, ETL monitoring, or dataset completeness audits where no external data, predictions, or professional assessments are needed.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:38:47.598Z","isFirstParty":false,"canonicalSlug":"null-coverage-analytics-numeric-row-ordering-equal-width-histogram-dfd01e3f"}