{"uid":"cap_5rB8T11NP6r5rtTkklZ5d","slug":"sampling-observations-numeric-interval-filter-date-by-category-pivot-5a09b437","name":"Sampling Observations — Numeric Interval Filter + Date by Category Pivot","description":"Sampling observations — Numeric interval filter + Date by category pivot: Numeric interval filter + 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-15-133?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"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_bEeEGnpqMzLEu_3JSbHEE","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":"Filters sampling observation records by a numeric value range and produces a date-by-category pivot table, returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"Filter my sampling observations so only rows where sample_value is between 5 and 50 are included, then give me a date-by-category pivot table — I have about 120 rows with row IDs, dates (YYYY-MM-DD), group labels, sample_value, and sample_weight.","exampleUseCases":[{"title":"Quality control batch sampling review","prompt":"I have 180 quality-control sample readings with row IDs, dates, product group labels, a measured sample_value, and a sample_weight. Filter out any rows where sample_value falls outside 10 to 500, then pivot the remaining data by date and product group so I can see which categories had readings in range each day."},{"title":"Survey response filtering by score range","prompt":"Here are 95 survey response records — each has a row ID, a date, a respondent group, a numeric score as sample_value, and a response weight as sample_weight. Keep only rows where sample_value is between 40 and 80, then show me a pivot of those filtered results broken down by date and respondent group."},{"title":"Environmental sensor interval analysis","prompt":"I've got 150 environmental sensor readings across several monitoring stations. Each row has a station ID as row_id, a collection date, a site_group as dataset_group, a sensor reading as sample_value, and a calibration weight as sample_weight. Filter to readings between -5 and 200, then cross-tabulate by date and site group so I can spot which stations were active on which days."}],"resultDescription":"Returns two analytical reports derived from the supplied rows: (1) a subset of records whose target field (sample_value or sample_weight) falls within the specified numeric interval [minimum, maximum], and (2) a pivot table crossing date against dataset_group categories, showing aggregated values for the filtered observations. Both reports are computed locally without external lookups or live data.","failureModes":["Rows array is empty or missing — API returns a validation error","More than 200 rows supplied — exceeds maxItems limit, request rejected","Date strings not matching YYYY-MM-DD pattern — validation error on date field","minimum greater than maximum — may return empty filtered set with no error","null sample_value or sample_weight values may be excluded from numeric computations","Missing required fields (row_id, dataset_group, date) — schema validation failure","Payment not processed — x402 payment required before results are returned"],"whenToPreferThis":"Choose this endpoint when you have up to 200 sampling observation records (with sample_value and sample_weight) and need two simultaneous analytical views: a numeric range filter and a date-by-category pivot. It is ideal for lightweight, offline-style analysis where no external data lookup or prediction is needed, and when you want both reports bundled at a flat $0.01 USDC cost rather than running two separate API calls.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:38:57.800Z","isFirstParty":false,"canonicalSlug":"sampling-observations-numeric-interval-filter-date-by-category-pivot-5a09b437"}