{"uid":"cap_Tu_8BVephlVa8p_eKDmOM","slug":"tourism-observations-string-normalisation-and-exact-row-deduplication-4f4d87f0","name":"Tourism Observations String Normalisation and Exact Row Deduplication","description":"Tourism observations — String normalisation + Exact row deduplication: String normalisation + Exact row deduplication 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-14-020?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"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}}},"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_92qnwDqLGhiY5Nu_UuLhb","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":"Normalises strings and deduplicates exact rows in tourism observation records containing visitor counts and overnight stays, producing 2 analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you clean up my tourism dataset — normalise the region strings and remove any exact duplicate rows? I have about 50 records with fields like row_id, region, date, visitor_count, and overnight_stays that need tidying before analysis.","exampleUseCases":[{"title":"Regional tourism data cleanup before reporting","prompt":"I've got 120 rows of tourism observations from different regions with visitor counts and overnight stays — can you normalise the region name strings and deduplicate any exact duplicate rows before I generate my quarterly report?"},{"title":"Deduplicating merged overnight stays datasets","prompt":"We merged two tourism data feeds and ended up with exact duplicate rows — please run deduplication on these 80 tourism records (visitor_count and overnight_stays included) and give me a report showing what was removed."},{"title":"Standardising string fields in visitor data","prompt":"My visitor count dataset has inconsistent region names across 150 rows — can you normalise those strings and also flag any exact duplicate rows in the tourism observations so I get clean data?"}],"resultDescription":"Two analytical reports covering: (1) string normalisation results showing how text fields like region were standardised, and (2) exact row deduplication results identifying and removing duplicate rows from the supplied tourism observation records. Results are computed locally with no external lookups.","failureModes":["Input array exceeds 200 rows — request rejected","Missing required fields (row_id, region, date, visitor_count, overnight_stays) on any row — validation error","Invalid date format (not YYYY-MM-DD) — schema validation failure","Numeric fields out of allowed range (±1 trillion) — rejection","Empty rows array (minItems:1 violated) — error response"],"whenToPreferThis":"Choose this endpoint when you have tourism observation records (visitor counts, overnight stays) that need both string normalisation and exact row deduplication in a single call, without requiring live lookups or external data sources. Ideal for batch data quality workflows on up to 200 rows at a very low cost ($0.01 USDC for 2 reports).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-29T12:53:34.057Z","isFirstParty":false,"canonicalSlug":"tourism-observations-string-normalisation-and-exact-row-deduplication-4f4d87f0"}