{"uid":"cap_4YyB9x6PFZLCWXAiam1KH","slug":"null-coverage-string-normalisation-equal-width-histogram-45f97098","name":"Null Coverage — String Normalisation + Equal-Width Histogram","description":"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.","url":"https://market.datapackvibe.com/x402/assistant-ib26-analytics-03-031?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_3ohr2q8eSuZtrTc0zHlE3","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":"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.","exampleAgentPrompt":"Take my null coverage records — I have 4 rows across group-a and group-b with missing_values and total_values — normalize the missing_values field strings and build a 5-bin equal-width histogram for it.","exampleUseCases":[{"title":"Data completeness audit for pipeline","prompt":"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?"},{"title":"Histogram of total values across groups","prompt":"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."},{"title":"Missing value distribution for QA report","prompt":"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."}],"resultDescription":"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.","failureModes":["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"],"whenToPreferThis":"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.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:57:36.494Z","isFirstParty":false,"canonicalSlug":"null-coverage-string-normalisation-equal-width-histogram-45f97098"}