{"uid":"cap_ryxhIJEg5FEZpUOicu_ds","slug":"shot-schedules-analytics-category-frequencies-two-measure-correlation-73f5e787","name":"Shot Schedules Analytics: Category Frequencies + Two-Measure Correlation","description":"Shot schedules — Category frequencies + Two-measure correlation: Category frequencies + Two-measure correlation for supplied shot schedules records (planned_hours, actual_hours). 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-13-108?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","asset_group","date","planned_hours","actual_hours"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"asset_group":{"type":"string","default":"","maxLength":80},"actual_hours":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"planned_hours":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","asset_group":"group-a","actual_hours":1,"planned_hours":10},{"date":"2026-10-02","row_id":"row-2","asset_group":"group-b","actual_hours":2,"planned_hours":20},{"date":"2026-10-03","row_id":"row-3","asset_group":"group-a","actual_hours":3,"planned_hours":15},{"date":"2026-10-04","row_id":"row-4","asset_group":"group-b","actual_hours":4,"planned_hours":30}],"maxItems":200,"minItems":1}}},"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_kIGFVSV3zs_Ut3e4Q9cmk","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":"Analyzes shot schedule records (planned_hours, actual_hours) to produce category frequency counts and a two-measure Pearson/correlation report — two independent analytical reports in a single call.","exampleAgentPrompt":"Analyze my shot schedule data — I have rows with asset_group, date, planned_hours, and actual_hours — and give me both a category frequency breakdown by asset group and a correlation report between planned and actual hours. Here are 4 rows: row-1, group-a, 2026-10-01, planned 10, actual 1; row-2, group-b, 2026-10-02, planned 20, actual 2; row-3, group-a, 2026-10-03, planned 15, actual 3; row-4, group-b, 2026-10-04, planned 30, actual 4.","exampleUseCases":[{"title":"Shoot day efficiency audit","prompt":"I've got 50 rows of shot schedule data with planned_hours and actual_hours per asset group. Can you calculate how frequently each asset group appears and whether planned hours actually correlate with actual hours shot?"},{"title":"Production budget variance analysis","prompt":"Run a category frequency count and a correlation between planned_hours and actual_hours on my shot schedule — here are the records for our two-week principal photography block across groups alpha, beta, and gamma."},{"title":"Post-production schedule accuracy review","prompt":"I want to see how well our shot scheduling predicted actual time spent. Analyze these 120 shot schedule rows — give me the frequency of each asset group and the correlation between what we planned and what we actually used."}],"resultDescription":"Returns two independent analytical reports: (1) a category frequency table showing how often each asset_group value appears across the supplied rows, and (2) a two-measure correlation report quantifying the statistical relationship between planned_hours and actual_hours across all rows. Both reports are computed locally from the supplied data with no external lookups.","failureModes":["Rows array is empty or missing — request rejected (minItems: 1)","More than 200 rows supplied — request rejected (maxItems: 200)","Missing required fields (row_id, asset_group, date, planned_hours, actual_hours) — validation error","Invalid date format (not YYYY-MM-DD) — schema validation failure","Insufficient numeric variance in planned_hours or actual_hours — correlation may be undefined or NaN","Payment of 0.01 USDC not included or rejected — 402 Payment Required response"],"whenToPreferThis":"Choose this endpoint when you need a quick, low-cost ($0.01 USDC) dual-report analytics pass on shot schedule data — specifically category frequency counts plus a planned-vs-actual hours correlation — without needing live data lookups, predictions, or professional assessments. Ideal for production teams wanting to audit scheduling accuracy offline using up to 200 rows of existing records in a single API call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-17T12:42:57.056Z","isFirstParty":false,"canonicalSlug":"shot-schedules-analytics-category-frequencies-two-measure-correlation-73f5e787"}