{"uid":"cap_TpAcbulTRvX6H-QbFHZjW","slug":"sampling-observations-grouped-numeric-summary-explicit-missing-value-1cda2aa0","name":"Sampling Observations — Grouped Numeric Summary + Explicit Missing-Value Fill","description":"Sampling observations — Grouped numeric summary + Explicit missing-value fill: Grouped numeric summary + Explicit missing-value fill 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-15-099?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"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"}}},"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_O6lE1TgXBwuhi6TyE53jd","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":"Computes grouped numeric summary statistics and fills missing values (zero, mean, or median) for up to 200 sampling observation rows with sample_value and sample_weight fields, returning two analytical reports.","exampleAgentPrompt":"I have 150 sampling observation rows with sample_value and sample_weight fields — some sample_values are null. Can you group them by dataset_group, fill the missing sample_values using the median, and give me a grouped numeric summary?","exampleUseCases":[{"title":"Survey missing-value imputation and summary","prompt":"I have survey data with 120 rows where some respondents skipped the sample_value field. Group them by dataset_group, fill the blanks using the median, and summarize the numeric results per group."},{"title":"Quality control sampling statistics by batch","prompt":"Here are 80 quality-control sampling records across three production batches — some sample_weights are null. Fill those missing weights with zero and give me a grouped numeric summary broken down by dataset_group."},{"title":"Environmental monitoring data aggregation","prompt":"I've got environmental sampling readings across four monitoring sites with some missing sample_values. Can you group by site (dataset_group), impute nulls using the mean, and return a grouped numeric summary for all 200 rows?"}],"resultDescription":"Returns two analytical reports: (1) a grouped numeric summary of sample_value/sample_weight statistics broken down by dataset_group, and (2) the dataset with missing values in the chosen field explicitly filled using the selected method (zero, mean, or median). All computation is performed locally on the supplied data with no external lookups.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Invalid date format (not YYYY-MM-DD) causes row rejection","Empty rows array returns an error","sample_value or sample_weight values outside ±1,000,000,000,000 range are rejected","Unknown fill method (not zero, mean, median) causes a validation error","Missing required fields (row_id, dataset_group, date) cause row-level failures"],"whenToPreferThis":"Choose this endpoint when you have tabular sampling observation data with sample_value and sample_weight columns (up to 200 rows), need grouped numeric summaries by category, and want missing values imputed before aggregation — all in a single low-cost call. Prefer this over general-purpose analytics when the dataset fits the exact schema (row_id, dataset_group, date, sample_value, sample_weight) and you need both missing-value fill and grouped summary in one step without any live data fetching or external enrichment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:37:49.841Z","isFirstParty":false,"canonicalSlug":"sampling-observations-grouped-numeric-summary-explicit-missing-value-1cda2aa0"}