{"uid":"cap_iE0uOtfgHtSKrEHSBarw9","slug":"vextorium-csv-cleaner-and-normalizer-86192f82","name":"Vextorium CSV Cleaner and Normalizer","description":"232 pay-per-call data APIs for AI agents: official statistics and economy (ECB, Fed, Eurostat, World Bank, SEC, BOE, INE), crypto prices and sentiment, Spanish public data, compliance (sanctions, VAT, IBAN, LEI), science, weather, web and developer tools and local AI text tools. Pay in USDC via x402.","url":"https://api.vextorium.com/v1/csv-clean?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"to":{"enum":["json"],"type":"string","description":"Output format"},"from":{"enum":["csv"],"type":"string","description":"Input format"},"input":{"type":"string","description":"Raw CSV content to clean"}}},"responseSchema":{"type":"json","example":{"data":[{"age":25,"name":"Ana"}],"rows":2,"columns":["nombre","edad"],"privacy_notice":"This data is processed in memory and not stored.","applied_changes":["Nombres de columnas normalizados"]}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.02","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":"$0.02/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.02","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.02","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_k_07GLm8X95I6_wRdb4ES","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.02","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Cleans and normalizes raw CSV data — fixing column names, inferring types, removing duplicates and empty values — and returns the result as structured JSON.","exampleAgentPrompt":"Can you clean this CSV for me — normalize the column names, fix the data types, remove any duplicates and empty rows, and give me back the result as JSON? Here's the raw CSV content: 'nombre,edad\\nAna,25\\nAna,25\\nBob,'","exampleUseCases":[{"title":"Pipeline pre-processing for analytics","prompt":"I've got a raw CSV export from our sales system with messy headers, duplicate rows, and blank cells — can you clean it up and convert it to JSON so I can load it into our analytics pipeline?"},{"title":"Automated data quality check for uploads","prompt":"Before I insert this CSV into the database, can you normalize the column names, infer the correct data types, remove duplicates and empty values, and return the cleaned data as JSON so I can review what changed?"},{"title":"Agent-driven ETL data prep","prompt":"Take this CSV I scraped from the web, clean up the formatting — fix column names, drop blank rows, deduplicate — and hand me back a structured JSON array so my next step can process it properly."}],"resultDescription":"A JSON object containing: a 'data' array of cleaned and typed records, 'rows' count, a 'columns' array of normalized column names, an 'applied_changes' array listing every transformation performed (e.g. column name normalization, duplicate removal), and a 'privacy_notice' confirming data is not stored.","failureModes":["Invalid or malformed CSV content returns an error — the input must be parseable CSV text","Missing required 'input', 'from', or 'to' fields in the request body cause a validation error","Empty CSV input with no rows may return zero data rows or an error","Extremely large CSV payloads may hit in-memory processing limits","Unsupported 'from' format (anything other than 'csv') or 'to' format (anything other than 'json') will be rejected"],"whenToPreferThis":"Choose this endpoint when you have raw CSV data that needs cleaning, type normalization, deduplication, or column name standardization before downstream use, and you want the result in JSON format. It is especially useful in ETL pipelines, pre-database import workflows, or agent-driven data preparation steps. The privacy-safe, in-memory processing makes it suitable for handling sensitive data without persistence concerns.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:45:54.383Z","isFirstParty":false,"canonicalSlug":"vextorium-csv-cleaner-and-normalizer-86192f82"}