{"uid":"cap_uQu-foqJs05oXhzDgLUwq","slug":"data-ingestion-batches-two-measure-correlation-explicit-missing-value-e8d68cf5","name":"Data Ingestion Batches — Two-Measure Correlation + Explicit Missing-Value Fill","description":"Data ingestion batches — Two-measure correlation + Explicit missing-value fill: Two-measure correlation + Explicit missing-value fill for supplied data ingestion batches records (received_rows, accepted_rows). 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-analytics-01-184?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","received_rows","accepted_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"accepted_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"received_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","accepted_rows":1,"dataset_group":"group-a","received_rows":10},{"date":"2026-10-02","row_id":"row-2","accepted_rows":2,"dataset_group":"group-b","received_rows":20},{"date":"2026-10-03","row_id":"row-3","accepted_rows":3,"dataset_group":"group-a","received_rows":15},{"date":"2026-10-04","row_id":"row-4","accepted_rows":4,"dataset_group":"group-b","received_rows":30}],"maxItems":200,"minItems":1},"field":{"enum":["received_rows","accepted_rows"],"type":"string","default":"received_rows"},"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_X5iU9jpea9V9yybiV312A","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 Pearson correlation between received_rows and accepted_rows across up to 200 data ingestion batch records, while filling missing values using zero, mean, or median imputation, and returns two analytical reports.","exampleAgentPrompt":"Analyze the correlation between received_rows and accepted_rows across my 50 ingestion batch records — use median to fill any missing values — and give me two analytical reports.","exampleUseCases":[{"title":"ETL pipeline data quality audit","prompt":"I have 120 rows of daily ingestion batch data with received_rows and accepted_rows counts, some values are missing. Fill those gaps using the mean method and tell me how strongly the two measures are correlated across all my dataset groups."},{"title":"Batch acceptance rate investigation","prompt":"Can you run a correlation analysis between received_rows and accepted_rows for my ingestion batches? I have about 80 records, some nulls in accepted_rows — fill them with zero and give me both reports."},{"title":"Monthly ingestion trend correlation","prompt":"Here are 200 rows of monthly ingestion batch stats grouped by dataset_group with dates. Use median imputation for any missing received_rows values and compute the two-measure correlation report between received and accepted rows."}],"resultDescription":"Two analytical reports covering: (1) Pearson correlation coefficient between received_rows and accepted_rows across the submitted batch records, and (2) the dataset with explicit missing-value fills applied using the chosen method (zero, mean, or median). Reports are computed locally from supplied data with no external lookups.","failureModes":["More than 200 rows submitted — request exceeds maxItems limit","Missing required fields (row_id, date, dataset_group) on any row — validation error","Date field does not match YYYY-MM-DD pattern — schema validation failure","Numeric values outside allowed range (±1,000,000,000,000) — rejected","All values for one measure are null after imputation — correlation cannot be computed","Payment of 0.01 USDC not included — 402 payment required response"],"whenToPreferThis":"Choose this endpoint when you have up to 200 data ingestion batch records with received_rows and accepted_rows metrics and need both missing-value imputation and a correlation analysis between those two measures in a single low-cost call. It is ideal for data engineers auditing ETL pipeline quality or acceptance rates without needing external data, predictions, or professional assessments.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-16T18:48:40.234Z","isFirstParty":false,"canonicalSlug":"data-ingestion-batches-two-measure-correlation-explicit-missing-value-e8d68cf5"}