{"uid":"cap_Qixf1aAgSZBlFNnyZ951o","slug":"travel-administration-string-normalisation-and-missing-value-fill-36415d55","name":"Travel Administration String Normalisation and Missing Value Fill","description":"Travel administration — String normalisation + Explicit missing-value fill: String normalisation + Explicit missing-value fill for supplied travel administration records (trip_count, recorded_cost). 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-operations-14-037?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","team_group","date","trip_count","recorded_cost"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"team_group":{"type":"string","default":"","maxLength":80},"trip_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"recorded_cost":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","team_group":"group-a","trip_count":10,"recorded_cost":1},{"date":"2026-10-02","row_id":"row-2","team_group":"group-b","trip_count":20,"recorded_cost":2},{"date":"2026-10-03","row_id":"row-3","team_group":"group-a","trip_count":15,"recorded_cost":3},{"date":"2026-10-04","row_id":"row-4","team_group":"group-b","trip_count":30,"recorded_cost":4}],"maxItems":200,"minItems":1},"field":{"enum":["trip_count","recorded_cost"],"type":"string","default":"trip_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_AxZpMP1_uc-4latCJHVpr","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) in travel administration records (trip_count, recorded_cost) for up to 200 rows, returning 2 analytical reports.","exampleAgentPrompt":"Clean up our travel administration records — I have 150 rows with team group, date, trip_count, and recorded_cost fields, and I need missing trip_count values filled using median imputation, with string normalisation applied across the dataset.","exampleUseCases":[{"title":"Fix null trip counts for monthly report","prompt":"I have 80 rows of travel admin data for October with some missing trip_count values — can you fill those nulls using the median and normalise the strings so the report is clean?"},{"title":"Impute missing travel costs with zero","prompt":"Our travel records have blank recorded_cost entries for some teams. Fill those missing values with zero and normalise the string fields across all 120 rows."},{"title":"Prepare team travel data using mean fill","prompt":"I need to prep our travel administration dataset — 200 rows with team_group and date — by normalising strings and filling any missing recorded_cost values using the mean. Can you run both reports?"}],"resultDescription":"Returns 2 independent analytical reports covering the up-to-200 submitted rows: one with string-normalised values and one with explicit missing-value fills applied to the specified field (trip_count or recorded_cost) using the chosen method (zero, mean, or median).","failureModes":["More than 200 rows submitted — request exceeds row limit","Invalid date format (not YYYY-MM-DD) causes schema validation failure","Missing required fields (row_id, team_group, date) triggers input rejection","Numeric values outside allowed range (±1 trillion) rejected","Invalid method enum value (not zero/mean/median) causes error","Empty rows array rejected (minItems: 1)"],"whenToPreferThis":"Choose this endpoint when you have travel administration records (trip_count, recorded_cost) with missing numeric values and need offline, local imputation (zero, mean, or median fill) plus string normalisation in a single low-cost call. Ideal for pre-reporting data cleaning on batches up to 200 rows without needing live lookups or external data sources.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-29T13:17:42.306Z","isFirstParty":false,"canonicalSlug":"travel-administration-string-normalisation-and-missing-value-fill-36415d55"}