{"uid":"cap_C1X00vqdMYNm4q4SgRvGq","slug":"schema-conformity-analytics-numeric-interval-filter-missing-value-fill-093b11a2","name":"Schema Conformity Analytics — Numeric Interval Filter + Missing Value Fill","description":"Schema conformity — Numeric interval filter + Explicit missing-value fill: Numeric interval filter + Explicit missing-value fill for supplied schema conformity records (valid_records, checked_records). 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-02-135?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","valid_records","checked_records"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"dataset_group":{"type":"string","default":"","maxLength":80},"valid_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"checked_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","valid_records":10,"checked_records":1},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","valid_records":20,"checked_records":2},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","valid_records":15,"checked_records":3},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","valid_records":30,"checked_records":4}],"maxItems":200,"minItems":1},"field":{"enum":["valid_records","checked_records"],"type":"string","default":"valid_records"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_lnqMfy0fknUcFcr1cHoBS","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":"Filters schema conformity records (valid_records, checked_records) by a numeric interval and fills missing values using zero, mean, or median, returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"I have 150 schema conformity rows with valid_records and checked_records fields — can you filter valid_records to only keep values between 0 and 500, and fill any missing values using the median? I need two reports back.","exampleUseCases":[{"title":"Data Quality Pipeline Null Imputation","prompt":"I'm processing a batch of 80 schema conformity records and some valid_records entries are null — can you fill those missing values using the mean and also filter to only keep values between 10 and 1000?"},{"title":"ETL Conformity Range Validation","prompt":"Can you take my 200 checked_records rows and filter out anything outside the range of 0 to 100, then fill nulls with zero so I get clean reports for both my analytics runs?"},{"title":"Dashboard Data Cleanup Before Reporting","prompt":"Before I refresh our conformity dashboard, can you run an interval filter on valid_records keeping values between 5 and 50000 and use median fill for any missing entries across my 60 dataset_group rows?"}],"resultDescription":"Returns two independent analytical reports covering the up to 200 supplied schema conformity rows: one applying the numeric interval filter (excluding rows where the target field falls outside the specified minimum/maximum), and one applying explicit missing-value fill (replacing nulls with zero, mean, or median). Results are computed locally with no external lookups.","failureModes":["Input array exceeds 200 rows — request rejected","Missing required fields (row_id, date, valid_records, checked_records) cause validation errors","Date field does not match YYYY-MM-DD pattern — schema validation failure","Minimum value greater than maximum value — may produce empty filtered result set","Invalid enum value for method or field — schema validation rejection","Empty rows array (minItems: 1 violated) — rejected"],"whenToPreferThis":"Choose this endpoint when you need lightweight, local analytical processing of schema conformity metrics (valid_records, checked_records) with both interval-based range filtering and missing value imputation in a single call. It is ideal for data quality pipelines, ETL preprocessing, or dashboard refresh workflows where you have up to 200 rows and want two complementary cleaned reports without relying on external databases or prediction services. At $0.01 USDC for two reports, it is cost-effective for batch data cleaning tasks that don't require real-time lookups or ML-based predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:48:21.254Z","isFirstParty":false,"canonicalSlug":"schema-conformity-analytics-numeric-interval-filter-missing-value-fill-093b11a2"}