{"uid":"cap_uYI1F_yiWQpm5fgrafMj7","slug":"peer-feedback-string-normalisation-and-missing-value-fill-4fc62778","name":"Peer Feedback String Normalisation and Missing-Value Fill","description":"Peer feedback — String normalisation + Explicit missing-value fill: String normalisation + Explicit missing-value fill for supplied peer feedback records (review_count, actioned_comments). 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-education-23-037?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","course_group","date","review_count","actioned_comments"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"course_group":{"type":"string","default":"","maxLength":80},"review_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"actioned_comments":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","course_group":"group-a","review_count":10,"actioned_comments":1},{"date":"2026-10-02","row_id":"row-2","course_group":"group-b","review_count":20,"actioned_comments":2},{"date":"2026-10-03","row_id":"row-3","course_group":"group-a","review_count":15,"actioned_comments":3},{"date":"2026-10-04","row_id":"row-4","course_group":"group-b","review_count":30,"actioned_comments":4}],"maxItems":200,"minItems":1},"field":{"enum":["review_count","actioned_comments"],"type":"string","default":"review_count"},"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_b85Gez6RCC6cHvrl8KSpd","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":"Normalises strings and fills missing values (zero, mean, or median) for peer feedback records containing review_count and actioned_comments fields, across up to 200 rows in 2 independent reports.","exampleAgentPrompt":"I have up to 200 peer feedback rows with course_group, date, review_count, and actioned_comments — some review_count values are null. Can you normalise the strings and fill the missing review_count values using median imputation, generating 2 reports?","exampleUseCases":[{"title":"Median fill for missing review counts","prompt":"I've got a batch of 150 peer feedback records across several course groups and some review_count fields are null — can you normalise the strings and fill those missing values using median so I get clean data back in 2 reports?"},{"title":"Zero-fill missing actioned comments","prompt":"My peer feedback dataset has blank actioned_comments for several rows dated in October 2026. Please normalise the strings and fill those missing actioned_comments with zero across all rows, and give me 2 reports."},{"title":"Mean imputation before dashboard export","prompt":"Before I export our course group feedback to the dashboard, can you run string normalisation and fill any missing review_count values using mean imputation on these 80 rows? I need the 2 analytical reports your service produces."}],"resultDescription":"Two analytical reports covering the submitted peer feedback rows (up to 200): normalised string fields and explicitly filled numeric values for the chosen field (review_count or actioned_comments) using the selected method (zero, mean, or median).","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, date, course_group) causes row rejection","Invalid date format (not YYYY-MM-DD) fails schema validation","Numeric values outside ±1,000,000,000,000 boundary are rejected","Invalid method or field enum value causes request failure"],"whenToPreferThis":"Choose this endpoint when you have peer feedback records (review_count, actioned_comments) with missing or unnormalised values and need lightweight, offline string normalisation plus explicit numeric imputation (zero, mean, or median) for up to 200 rows at a very low cost — without requiring live lookups, ML predictions, or external data enrichment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T00:39:58.790Z","isFirstParty":false,"canonicalSlug":"peer-feedback-string-normalisation-and-missing-value-fill-4fc62778"}