{"uid":"cap_55PEAeTt1tM-hWt_gCxsm","slug":"sampling-observations-record-quality-audit-date-by-category-pivot-bc09bbdc","name":"Sampling Observations — Record Quality Audit + Date-by-Category Pivot","description":"Sampling observations — Record quality audit + Date by category pivot: Record quality audit + Date by category pivot 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-15-017?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_5rRfRdrtaz4tpX56WcE43","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 on up to 200 sampling observation rows: a record quality audit and a date-by-category pivot table, for sample_value or sample_weight.","exampleAgentPrompt":"Can you run a record quality audit and date-by-category pivot on my sampling observations? I have rows with row_id, dataset_group, date, sample_value, and sample_weight — up to 200 rows — and I want to analyze sample_value across groups.","exampleUseCases":[{"title":"Pre-analysis data quality check","prompt":"I have a dataset of 150 sampling observations with fields row_id, dataset_group, date, sample_value, and sample_weight. Can you audit the record quality and also pivot sample_value by date and category so I can see data issues before I run my analysis?"},{"title":"Weighted sample distribution review","prompt":"Before I submit my survey sample data for reporting, run a quality audit and date-by-category pivot on the sample_weight field — I've got about 80 rows with group labels and dates ranging across October 2026."},{"title":"Multi-group temporal sampling summary","prompt":"I collected sampling observations across two groups over 30 days. Can you check the record quality and give me a date-by-category breakdown of sample_value so I can spot any gaps or anomalies in the data?"}],"resultDescription":"Two analytical reports returned together: (1) a record quality audit flagging issues such as nulls, out-of-range values, or malformed dates across the submitted rows; and (2) a pivot table summarizing the selected field (sample_value or sample_weight) broken down by date and dataset_group category. No external data is fetched; all analysis is performed locally on the supplied rows.","failureModes":["Fewer than 1 row or more than 200 rows submitted — request rejected","Missing required fields (row_id, dataset_group, date, sample_value, sample_weight) — validation error","Date field not matching YYYY-MM-DD pattern — parse error","Numeric values outside the allowed range (-1e12 to 1e12) — rejected","Invalid field enum value (not sample_value or sample_weight) — error","Payment not included or insufficient — x402 payment required response"],"whenToPreferThis":"Choose this endpoint when you need both a data quality audit and a date-by-category pivot on sampling observation data in a single low-cost call. It is ideal for pre-processing checks on small-to-medium datasets (up to 200 rows) with sample_value and sample_weight fields grouped by category and date. Prefer it over separate audit or pivot tools when cost efficiency and co-located reports matter and no live external lookup or prediction is needed.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T00:54:20.409Z","isFirstParty":false,"canonicalSlug":"sampling-observations-record-quality-audit-date-by-category-pivot-bc09bbdc"}