{"uid":"cap_sJFzVDuwsPovByOtdCOqw","slug":"proposal-preparation-date-by-category-pivot-explicit-missing-value-fill-c5b493c8","name":"Proposal Preparation — Date by Category Pivot + Explicit Missing-Value Fill","description":"Proposal preparation — Date by category pivot + Explicit missing-value fill: Date by category pivot + Explicit missing-value fill for supplied proposal preparation records (completed_sections, planned_sections). 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-writing-08-189?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","document_group","date","completed_sections","planned_sections"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"document_group":{"type":"string","default":"","maxLength":80},"planned_sections":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"completed_sections":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","document_group":"group-a","planned_sections":1,"completed_sections":10},{"date":"2026-10-02","row_id":"row-2","document_group":"group-b","planned_sections":2,"completed_sections":20},{"date":"2026-10-03","row_id":"row-3","document_group":"group-a","planned_sections":3,"completed_sections":15},{"date":"2026-10-04","row_id":"row-4","document_group":"group-b","planned_sections":4,"completed_sections":30}],"maxItems":200,"minItems":1},"field":{"enum":["completed_sections","planned_sections"],"type":"string","default":"completed_sections"},"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_vUZ2-NfVhszTRqxCFAjvU","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":"Pivots proposal preparation data by date and document group, then fills missing values in completed_sections or planned_sections using zero, mean, or median imputation.","exampleAgentPrompt":"Take my proposal preparation records — up to 200 rows with row_id, document_group, date, completed_sections, and planned_sections — and run a date-by-category pivot on the completed_sections field, filling any missing values using median imputation, then give me both analytical reports.","exampleUseCases":[{"title":"Tracking proposal completion across teams","prompt":"I have 150 rows of proposal data with document groups like 'legal', 'finance', and 'ops', each with a date and completed_sections count. Some completed_sections values are null — can you pivot them by date and document group and fill those gaps with the median?"},{"title":"Planned section forecasting with zero fill","prompt":"Here's my proposal planning dataset with planned_sections per document group and date. A few rows have missing planned_sections — please pivot by date and category, and fill the blanks with zero so I can see the full grid."},{"title":"Comparing two metrics across proposal groups","prompt":"I've got proposal records with both completed_sections and planned_sections, organized by document group and date. Run the date-by-category pivot on planned_sections using mean fill for missing values and give me the two summary reports."}],"resultDescription":"Two analytical reports: (1) a date-by-category pivot table showing the selected field (completed_sections or planned_sections) broken down by date and document_group, and (2) the same dataset with all missing values explicitly filled using the chosen method (zero, mean, or median). Handles up to 200 rows per call.","failureModes":["Fewer than 1 row or more than 200 rows provided — request rejected","Invalid date format (not YYYY-MM-DD) — validation error","Field value out of range (beyond ±1,000,000,000,000) — schema violation","Unknown fill method or field enum value — invalid input error","All values missing for a group — mean/median imputation may produce NaN or fallback to zero","Payment not fulfilled — HTTP 402 returned"],"whenToPreferThis":"Choose this endpoint when you have structured proposal preparation records with date, document group, completed_sections, and planned_sections, and need both a pivot table view and clean missing-value imputation in a single low-cost call. Ideal when you need exactly two reports from the same dataset without external data lookup or prediction. Best for datasets up to 200 rows where local analytical computation is sufficient.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T12:31:19.271Z","isFirstParty":false,"canonicalSlug":"proposal-preparation-date-by-category-pivot-explicit-missing-value-fill-c5b493c8"}