{"uid":"cap_XJ8fmGBzGJvHKy8wTft7c","slug":"sampling-observations-string-normalisation-exact-row-deduplication-c3c82d71","name":"Sampling Observations — String Normalisation + Exact Row Deduplication","description":"Sampling observations — String normalisation + Exact row deduplication: String normalisation + Exact row deduplication for supplied sampling observations records (sample_value, sample_weight). 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-15-020?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","sample_value","sample_weight"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"sample_value":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"sample_weight":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","sample_value":10,"dataset_group":"group-a","sample_weight":1},{"date":"2026-10-02","row_id":"row-2","sample_value":20,"dataset_group":"group-b","sample_weight":2},{"date":"2026-10-03","row_id":"row-3","sample_value":15,"dataset_group":"group-a","sample_weight":3},{"date":"2026-10-04","row_id":"row-4","sample_value":30,"dataset_group":"group-b","sample_weight":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_KOmpV_JFbzCSnvXm9aOfb","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 supplied sampling observation records (sample_value, sample_weight) for up to 200 rows, producing 2 analytical reports.","exampleAgentPrompt":"Can you clean up my sampling observations dataset — I have up to 50 rows with row_id, dataset_group, date, sample_value, and sample_weight fields — and run string normalisation plus exact row deduplication to get 2 clean reports back?","exampleUseCases":[{"title":"Survey sample deduplication before analysis","prompt":"I have 120 rows of survey sampling data with columns row_id, dataset_group, date, sample_value, and sample_weight — can you run string normalisation and exact row deduplication on them and give me the 2 reports so I can remove duplicates before running my analysis?"},{"title":"Data pipeline quality gate for sampling records","prompt":"Before we ingest today's batch of sampling observations into our pipeline, can you normalise the string fields and flag any exact duplicate rows? I have 80 records with row_id, dataset_group, date, sample_value, and sample_weight ready to send."},{"title":"Cleaning weighted sample dataset for reporting","prompt":"My team collected 60 weighted sample observations but we suspect there are duplicate entries and inconsistent string formatting in the dataset_group field — can you run the string normalisation and exact deduplication reports on these rows so we can clean it up before the weekly report?"}],"resultDescription":"Returns 2 analytical reports covering: (1) string normalisation findings for text fields in the supplied rows, and (2) exact row deduplication results identifying and flagging fully duplicate records across up to 200 input rows. No external lookups or predictions are made — all analysis is performed locally on the supplied data.","failureModes":["Input array exceeds 200 rows — request rejected","Missing required fields (row_id, dataset_group, date, sample_value, sample_weight) — validation error","Invalid date format (must match YYYY-MM-DD pattern) — schema validation failure","row_id empty or exceeds 80 characters — rejected","sample_value or sample_weight outside allowed range (-1e12 to 1e12) — rejected","Empty rows array (minItems: 1 not met) — error"],"whenToPreferThis":"Choose this endpoint when you have sampling observation records (with sample_value and sample_weight fields) that need string field normalisation and exact duplicate row detection in a single call. It is best suited for pre-analysis data cleaning pipelines where you want two focused reports (normalisation + deduplication) without any external API calls, predictions, or live lookups. Prefer this over general-purpose ETL tools when you need a lightweight, pay-per-use ($0.01 USDC) analytical pass on up to 200 rows of structured sampling data.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:38:12.887Z","isFirstParty":false,"canonicalSlug":"sampling-observations-string-normalisation-exact-row-deduplication-c3c82d71"}