{"uid":"cap_GlKz7loM2HaPHHBKDZeog","slug":"simulation-caches-weighted-mean-date-by-category-pivot-308a0fa7","name":"Simulation Caches — Weighted Mean + Date-by-Category Pivot","description":"Simulation caches — Secondary-measure weighted mean + Date by category pivot: Secondary-measure weighted mean + Date by category pivot for supplied simulation caches records (cache_gb, simulation_seconds). 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-creative-08-185?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","asset_group","date","cache_gb","simulation_seconds"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"cache_gb":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"asset_group":{"type":"string","default":"","maxLength":80},"simulation_seconds":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","cache_gb":10,"asset_group":"group-a","simulation_seconds":1},{"date":"2026-10-02","row_id":"row-2","cache_gb":20,"asset_group":"group-b","simulation_seconds":2},{"date":"2026-10-03","row_id":"row-3","cache_gb":15,"asset_group":"group-a","simulation_seconds":3},{"date":"2026-10-04","row_id":"row-4","cache_gb":30,"asset_group":"group-b","simulation_seconds":4}],"maxItems":200,"minItems":1},"field":{"enum":["cache_gb","simulation_seconds"],"type":"string","default":"cache_gb"}}},"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_wq_Svw3kpT8Tjg_tp9gIp","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 a secondary-measure weighted mean and a date-by-category pivot table for up to 200 simulation cache records (cache_gb, simulation_seconds), returning two analytical reports in one call.","exampleAgentPrompt":"I have 4 simulation cache records — row-1 (group-a, 2026-10-01, cache_gb=10, simulation_seconds=1), row-2 (group-b, 2026-10-02, cache_gb=20, simulation_seconds=2), row-3 (group-a, 2026-10-03, cache_gb=15, simulation_seconds=3), row-4 (group-b, 2026-10-04, cache_gb=30, simulation_seconds=4) — can you compute the weighted mean and a date-by-category pivot on cache_gb for all of these?","exampleUseCases":[{"title":"Weighted mean of cache storage by group","prompt":"Here are 50 simulation cache records with asset groups and cache sizes in GB — compute the weighted mean of cache_gb across all of them and give me a date-by-category pivot so I can see how storage breaks down over time per group."},{"title":"Simulation runtime aggregation report","prompt":"I've got 120 simulation records with simulation_seconds values spread across several asset groups and dates — run the weighted mean and date pivot reports on simulation_seconds so I can spot which groups are consuming the most compute time."},{"title":"Capacity planning pivot for cache records","prompt":"Can you take these 80 cache records spanning October 2026 and produce both a weighted mean and a date-by-category breakdown of cache_gb? I want to understand peak cache usage by group across the month."}],"resultDescription":"Returns two analytical reports: (1) a secondary-measure weighted mean of the chosen field (cache_gb or simulation_seconds) across all submitted rows, and (2) a date-by-category pivot table cross-tabulating values by date and asset_group. No external lookups or predictions are made — all computation is performed locally on the supplied data.","failureModes":["Rows array empty or missing — validation error returned","More than 200 rows submitted — request rejected with max-items error","Invalid date format (not YYYY-MM-DD) — schema validation failure","field value not in enum [cache_gb, simulation_seconds] — validation error","null values in numeric fields may affect weighted mean calculation","row_id missing or empty string — required field validation failure"],"whenToPreferThis":"Choose this endpoint when you need both a weighted mean and a date-by-category pivot on simulation cache data (cache_gb or simulation_seconds) in a single call for up to 200 rows. It is ideal for offline/batch analytical use cases where you supply your own data and want two complementary statistical views without needing external data sources, predictions, or live lookups. Prefer it over general-purpose analytics tools when cost predictability ($0.01 per call for 2 reports) and schema-validated input matter.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-22T00:49:12.015Z","isFirstParty":false,"canonicalSlug":"simulation-caches-weighted-mean-date-by-category-pivot-308a0fa7"}