{"uid":"cap_DZz_RZIrOmbo4KUOExeZM","slug":"tourism-observations-string-normalisation-equal-width-histogram-a29c1d7c","name":"Tourism Observations — String Normalisation + Equal-Width Histogram","description":"Tourism observations — String normalisation + Equal-width histogram: String normalisation + Equal-width histogram for supplied tourism observations records (visitor_count, overnight_stays). 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-economics-14-031?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","region","date","visitor_count","overnight_stays"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"region":{"type":"string","default":"","maxLength":80},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"visitor_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"overnight_stays":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","region":"group-a","row_id":"row-1","visitor_count":10,"overnight_stays":1},{"date":"2026-10-02","region":"group-b","row_id":"row-2","visitor_count":20,"overnight_stays":2},{"date":"2026-10-03","region":"group-a","row_id":"row-3","visitor_count":15,"overnight_stays":3},{"date":"2026-10-04","region":"group-b","row_id":"row-4","visitor_count":30,"overnight_stays":4}],"maxItems":200,"minItems":1},"field":{"enum":["visitor_count","overnight_stays"],"type":"string","default":"visitor_count"}}},"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_aZOnyQtcolG1V6a-OtSoE","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 string normalisation and equal-width histogram analysis on up to 200 tourism observation records (visitor_count or overnight_stays fields).","exampleAgentPrompt":"Can you normalize the region strings and produce an equal-width histogram with 10 bins for the visitor_count field in my tourism dataset? Here are the rows: [{\"row_id\":\"r1\",\"region\":\" North East \",\"date\":\"2025-01-01\",\"visitor_count\":1200,\"overnight_stays\":340},{\"row_id\":\"r2\",\"region\":\"south west\",\"date\":\"2025-01-02\",\"visitor_count\":850,\"overnight_stays\":210}].","exampleUseCases":[{"title":"Regional visitor count distribution analysis","prompt":"I have 150 tourism observation records across different regions — can you normalize the region name strings and generate an equal-width histogram with 8 bins for the visitor_count field so I can see how visitor numbers are distributed?"},{"title":"Overnight stays binning for seasonal report","prompt":"Please run string normalization and produce a 5-bin equal-width histogram on the overnight_stays column for my tourism dataset — here are 80 rows covering Q3 across our coastal regions."},{"title":"Data quality and distribution check before pipeline","prompt":"Before I load this tourism data into our dashboard, can you normalize the text fields and give me an equal-width histogram with 12 bins on visitor_count so I can spot any skew or anomalies in the 200 rows I'm sending?"}],"resultDescription":"Returns two analytical reports: (1) a string normalisation report showing cleaned/standardised text values for the supplied rows, and (2) an equal-width histogram report for the selected numeric field (visitor_count or overnight_stays) divided into the specified number of bins, including bin boundaries and row counts per bin. Both reports are computed locally with no external lookups.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, region, date, visitor_count, overnight_stays) causes rejection","Invalid date format (not YYYY-MM-DD) fails schema validation","Bins value outside 1–30 range is rejected","All-null values in the selected numeric field may produce an empty or degenerate histogram","Malformed JSON in rows array returns a parse error"],"whenToPreferThis":"Choose this endpoint when you need a combined string normalisation pass plus a binned frequency distribution (histogram) on tourism-domain records — specifically visitor_count or overnight_stays — in a single low-cost ($0.01 USDC) call for up to 200 rows, with no need for live data lookups or predictions. Prefer it over general-purpose analytics tools when you want deterministic, offline computation on supplied data without external dependencies.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T12:30:50.571Z","isFirstParty":false,"canonicalSlug":"tourism-observations-string-normalisation-equal-width-histogram-a29c1d7c"}