{"uid":"cap_8URZfEwyxV3zuOPOFI2Ev","slug":"csv-training-data-column-statistics-validator-44f748b3","name":"CSV Training Data Column Statistics Validator","description":"Training example metadata — Column statistics: Column statistics for Training example metadata. Validate a declared CSV table contract, up to 1000 rows. Quoted cells supported; no external enrichment. Specialised preset in a shared 50-profile, 20-operation engine. 0.01 USDC includes one CSV column statistics report.","url":"https://market.datapackvibe.com/x402/assistant-bx-csv-training-data-column-stats?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"csv":{"type":"string","default":"example_id,created_on,label,text_length,sample_weight\nrecord-a,2026-01-01,group-a,10,2\nrecord-b,2026-01-02,group-b,20,3","maxLength":100000,"minLength":1},"maximum":{"type":"number","default":1000000000000,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":-1000000000000,"maximum":1000000000000,"minimum":-1000000000000},"delimiter":{"enum":[",",";","\t"],"type":"string","default":","},"max_cell_length":{"type":"integer","default":1000,"maximum":5000,"minimum":1},"allowed_categories":{"type":"array","items":{"type":"string","default":"","maxLength":100,"minLength":1},"default":["group-a","group-b"],"maxItems":100,"minItems":0}}},"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_f89QgnUIybC9ghwesYQhM","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":"Computes per-column statistics for a CSV training dataset and validates it against a declared table contract, supporting up to 1000 rows.","exampleAgentPrompt":"Can you run column statistics on this training CSV — delimiter is comma, numeric values should stay between 0 and 1000000, max cell length 500, and allowed categories are group-a and group-b: 'example_id,created_on,label,text_length,sample_weight\\nrecord-a,2026-01-01,group-a,10,2\\nrecord-b,2026-01-02,group-b,20,3'?","exampleUseCases":[{"title":"Validate ML training label categories","prompt":"I have a training CSV with a label column that should only contain 'cat', 'dog', or 'bird' — can you validate all the columns and tell me if any rows have unexpected category values? Here's the CSV data with comma delimiter and max cell length of 200."},{"title":"Check numeric ranges in training features","prompt":"Please analyze this training dataset CSV for me — I need column statistics and I want to make sure all numeric columns stay between -500 and 500, using comma as the delimiter and a max cell length of 1000."},{"title":"Audit sample weights before model training","prompt":"Before I kick off model training, can you compute column statistics on this CSV and validate that the sample_weight and text_length columns are within 0 and 10000? The CSV uses comma delimiters and allowed labels are 'positive' and 'negative'."}],"resultDescription":"Returns a per-column statistics report for the submitted CSV, including validation results against numeric range bounds, allowed category values, and cell length limits. Each column is analyzed for type, distribution, and contract compliance within the declared constraints.","failureModes":["CSV exceeds 1000 rows — only up to 1000 rows are validated","CSV string exceeds 100,000 character limit — request rejected","Cell content exceeds max_cell_length — validation failure flagged","Category values not in allowed_categories list — contract violation reported","Numeric values outside minimum/maximum bounds — out-of-range error returned","Malformed CSV with unmatched quotes or inconsistent columns — parsing error","Delimiter mismatch causing all data to appear as a single column"],"whenToPreferThis":"Choose this endpoint when you need fast, affordable ($0.01 USDC) per-column statistical analysis and contract validation for CSV-formatted machine learning training data up to 1000 rows. It is ideal for pre-training data quality checks where you need to verify numeric bounds, categorical label integrity, and cell length constraints in a single call. Prefer it over general-purpose CSV tools when your use case is specifically training data validation with declared schema contracts.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T06:51:00.735Z","isFirstParty":false,"canonicalSlug":"csv-training-data-column-statistics-validator-44f748b3"}