{"uid":"cap_vBsWs0eDHeZBAuMMWYd3x","slug":"url-canonicalization-string-normalisation-explicit-missing-value-fill-013524a2","name":"URL Canonicalization — String Normalisation + Explicit Missing-Value Fill","description":"URL canonicalization — String normalisation + Explicit missing-value fill: String normalisation + Explicit missing-value fill for supplied url canonicalization records (observed_urls, unique_urls). 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-web-20-037?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","site_group","date","observed_urls","unique_urls"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"site_group":{"type":"string","default":"","maxLength":80},"unique_urls":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"observed_urls":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","site_group":"group-a","unique_urls":1,"observed_urls":10},{"date":"2026-10-02","row_id":"row-2","site_group":"group-b","unique_urls":2,"observed_urls":20},{"date":"2026-10-03","row_id":"row-3","site_group":"group-a","unique_urls":3,"observed_urls":15},{"date":"2026-10-04","row_id":"row-4","site_group":"group-b","unique_urls":4,"observed_urls":30}],"maxItems":200,"minItems":1},"field":{"enum":["observed_urls","unique_urls"],"type":"string","default":"observed_urls"},"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_1S-SIxOju-qnRG62M2qvn","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 string fields and fills missing values for observed_urls and unique_urls columns in URL canonicalization datasets of up to 200 rows, producing two analytical reports.","exampleAgentPrompt":"I have a batch of URL canonicalization records with some missing observed_urls values — can you normalize the strings and fill in those nulls using the median method? I have about 50 rows with date, row_id, site_group, observed_urls, and unique_urls columns.","exampleUseCases":[{"title":"Impute missing URL metrics for site groups","prompt":"I've got 120 rows of URL canonicalization data with some null unique_urls entries across several site groups. Can you fill those missing values using the mean method and normalize the string fields so everything is consistent?"},{"title":"Clean web crawl dataset before reporting","prompt":"Before I run my weekly URL deduplication report, I need to clean my 80-row dataset — fill any missing observed_urls using zero imputation and normalize the string columns like site_group and date."},{"title":"Fix null counts in URL tracking export","prompt":"My URL tracking export has about 35 rows and a handful of null observed_urls values. Can you apply median imputation to fill those gaps and normalize the strings so it's ready for analysis?"}],"resultDescription":"Two analytical reports covering: (1) string normalisation results for the supplied URL canonicalization records, and (2) explicit missing-value fill results for the specified field (observed_urls or unique_urls) using the chosen imputation method (zero, mean, or median). Reports cover up to 200 input rows and are generated using local analytical engines with no external lookups.","failureModes":["More than 200 rows submitted — request rejected or truncated","Invalid date format not matching YYYY-MM-DD pattern — validation error","Missing required fields (row_id, site_group, date) — schema validation failure","Field enum value not recognised (must be 'observed_urls' or 'unique_urls') — error","Method enum value not recognised (must be 'zero', 'mean', or 'median') — error","Numeric values outside allowed range (±1,000,000,000,000) — rejection","Empty rows array — minimum 1 item required"],"whenToPreferThis":"Choose this endpoint when you have URL canonicalization tabular data (with observed_urls and unique_urls columns) that needs both string normalisation and explicit missing-value imputation in a single call, at low cost ($0.01 USDC for both reports). It is best suited for offline batch cleaning of up to 200 rows where no live lookup or external enrichment is needed. Prefer this over more complex pipeline tools when the task is purely local data cleaning with imputation method control (zero, mean, or median).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-03T12:43:35.171Z","isFirstParty":false,"canonicalSlug":"url-canonicalization-string-normalisation-explicit-missing-value-fill-013524a2"}