{"uid":"cap_UTCha-qzUuzsF5laK7Mbi","slug":"vendor-evaluation-date-category-pivot-explicit-missing-value-fill-3507b5a8","name":"Vendor Evaluation — Date×Category Pivot + Explicit Missing-Value Fill","description":"Vendor evaluation — Date by category pivot + Explicit missing-value fill: Date by category pivot + Explicit missing-value fill for supplied vendor evaluation records (supplied_score, maximum_score). 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-company-10-189?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","supplied_score","maximum_score"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"company_group":{"type":"string","default":"","maxLength":80},"maximum_score":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"supplied_score":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","company_group":"group-a","maximum_score":1,"supplied_score":10},{"date":"2026-10-02","row_id":"row-2","company_group":"group-b","maximum_score":2,"supplied_score":20},{"date":"2026-10-03","row_id":"row-3","company_group":"group-a","maximum_score":3,"supplied_score":15},{"date":"2026-10-04","row_id":"row-4","company_group":"group-b","maximum_score":4,"supplied_score":30}],"maxItems":200,"minItems":1},"field":{"enum":["supplied_score","maximum_score"],"type":"string","default":"supplied_score"},"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_49HC502iHjHkjdlk3ArFe","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 vendor evaluation scores by date and company group, and fills missing values using zero, mean, or median imputation — two analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you pivot our vendor evaluation data by date and company group, and fill any missing supplied_score values using median imputation? I have up to 50 rows with fields: row_id, company_group, date, supplied_score, and maximum_score.","exampleUseCases":[{"title":"Vendor scorecard gap analysis","prompt":"I have 80 vendor evaluation records with row_id, company_group, date, supplied_score, and maximum_score — some supplied_score values are null. Can you fill the missing supplied_scores using the mean and also pivot the data by date and company group so I can see scores across vendors over time?"},{"title":"Procurement performance cross-tab","prompt":"Take these 120 vendor evaluation rows and produce a date-by-category pivot on maximum_score, then fill any missing maximum_score values with zero so our procurement team gets a clean cross-tab report."},{"title":"Monthly vendor ranking cleanup","prompt":"We have 30 vendor evaluation entries across group-a and group-b with some gaps in the supplied_score column — please fill those nulls with the median and pivot the results by date so I can compare groups month by month."}],"resultDescription":"Two analytical reports derived from the supplied vendor evaluation records: (1) a date-by-category pivot table crossing dates against company groups for the selected field (supplied_score or maximum_score), and (2) the same dataset with missing values explicitly filled using the chosen method (zero, mean, or median). No external lookups or predictions are made; all computation is local to the supplied rows.","failureModes":["Fewer than 1 row provided — request rejected","More than 200 rows submitted — exceeds row limit","Invalid date format (not YYYY-MM-DD) — schema validation error","Missing required fields (row_id, company_group, date) — validation failure","All values for selected field are null — imputation may return null or zero depending on method","Payment of 0.01 USDC not provided — x402 payment required error"],"whenToPreferThis":"Choose this endpoint when you need both a pivot transformation and missing-value imputation on vendor evaluation data (supplied_score / maximum_score) in a single call, for up to 200 rows, at minimal cost. It is ideal for procurement analytics pipelines where vendor scores need reshaping into a date-category matrix and gaps need to be filled before downstream processing — without requiring an external data source, ML model, or professional assessment service.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T18:53:29.808Z","isFirstParty":false,"canonicalSlug":"vendor-evaluation-date-category-pivot-explicit-missing-value-fill-3507b5a8"}