{"uid":"cap_yQRKuN8Dpg7Cn1DyiO9W9","slug":"sampling-observations-record-quality-audit-exact-row-deduplication-43cb47a5","name":"Sampling Observations — Record Quality Audit + Exact Row Deduplication + Adjacent Row Changes","description":"Sampling observations — Record quality audit + Exact row deduplication + Adjacent row changes: Record quality audit + Exact row deduplication + Adjacent row changes for supplied sampling observations records (sample_value, sample_weight). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-analytics-15-217?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},"field":{"enum":["sample_value","sample_weight"],"type":"string","default":"sample_value"}}},"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_d2d-5Tkt4axlHOApnL-Y7","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 three local analytical reports on sampling observation rows: record quality audit, exact row deduplication, and adjacent row change detection for sample_value or sample_weight fields.","exampleAgentPrompt":"Can you run a full data quality audit, exact row deduplication check, and adjacent row change detection on my sampling observations — I have rows with row_id, dataset_group, date, sample_value, and sample_weight fields, and I want to analyze the sample_value column? Here are up to 200 rows to check.","exampleUseCases":[{"title":"Pre-analysis data quality check","prompt":"I have a batch of up to 150 sampling observation records with sample_value and sample_weight columns — can you run a record quality audit on them and flag any issues before I pass them to my model?"},{"title":"Duplicate row detection in sample exports","prompt":"Our data pipeline may be double-exporting rows — can you run an exact row deduplication report on these sampling observation records across dataset_group and date so I can see which rows are duplicates?"},{"title":"Consecutive change monitoring in sample series","prompt":"I want to see where sample_weight values changed between adjacent rows in my time-ordered sampling dataset — can you run the adjacent row changes report on these records grouped by dataset_group?"}],"resultDescription":"Returns three independent reports for up to 200 supplied rows: (1) a record quality audit flagging nulls, format violations, and anomalies in sample_value/sample_weight; (2) an exact row deduplication report identifying fully identical rows; and (3) an adjacent row changes report showing where consecutive rows differ in the selected field. All analysis is performed locally on the supplied data with no external lookups.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Missing required fields (row_id, date, dataset_group) cause row-level validation errors","Invalid date format (not YYYY-MM-DD) triggers schema validation failure","Values outside the allowed range (-1e12 to 1e12) may be rejected","Empty rows array returns an error","Payment failure via x402 protocol prevents execution"],"whenToPreferThis":"Choose this endpoint when you need three bundled analytical reports — quality audit, deduplication, and adjacent-row change detection — on sampling observation records in a single low-cost call. It is ideal for datasets up to 200 rows where all analysis can be done locally against supplied data with no need for external data enrichment, predictions, or real-time lookups. It is more cost-effective than calling three separate endpoints when all three report types are needed together.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:39:18.318Z","isFirstParty":false,"canonicalSlug":"sampling-observations-record-quality-audit-exact-row-deduplication-43cb47a5"}