{"uid":"cap_Q6SqHPP8-NF9FUAZ6pISp","slug":"null-coverage-analyzer-category-frequencies-missing-value-fill-ad1742c8","name":"Null Coverage Analyzer — Category Frequencies & Missing Value Fill","description":"Null coverage — Category frequencies + Explicit missing-value fill: Category frequencies + Explicit missing-value fill for supplied null coverage records (missing_values, total_values). 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-03-112?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","missing_values","total_values"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"total_values":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"missing_values":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","total_values":1,"dataset_group":"group-a","missing_values":10},{"date":"2026-10-02","row_id":"row-2","total_values":2,"dataset_group":"group-b","missing_values":20},{"date":"2026-10-03","row_id":"row-3","total_values":3,"dataset_group":"group-a","missing_values":15},{"date":"2026-10-04","row_id":"row-4","total_values":4,"dataset_group":"group-b","missing_values":30}],"maxItems":200,"minItems":1},"field":{"enum":["missing_values","total_values"],"type":"string","default":"missing_values"},"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_1HcUob6TMLDAB206u1HEW","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 category frequencies and fills missing values (via zero, mean, or median) for null-coverage records supplied as row data, producing two local analytical reports.","exampleAgentPrompt":"I have up to 200 rows of null coverage data with dataset groups like 'group-a' and 'group-b', each with missing_values and total_values counts — can you run the category frequency report and fill missing_values using median imputation on them?","exampleUseCases":[{"title":"Data quality audit by group","prompt":"I have 150 rows of dataset records across groups 'finance' and 'ops', each with a date, missing_values, and total_values. Can you compute the category frequencies showing how often each group appears and fill in any null missing_values using median?"},{"title":"Zero-fill imputation for pipeline","prompt":"Before I feed this batch of 80 rows into my pipeline, I need any null total_values replaced with zero and a frequency breakdown of which dataset_group each row belongs to — can you run that analysis?"},{"title":"Mean imputation for completeness report","prompt":"I've got 60 daily records across three dataset groups with some missing_values entries that are null. Please fill those nulls using mean imputation and give me the category frequency distribution across the groups."}],"resultDescription":"Returns two local analytical reports: (1) a category frequency breakdown showing how often each dataset_group appears in the supplied rows, and (2) an explicit missing-value fill report where null entries in the chosen field (missing_values or total_values) are replaced using the selected method (zero, mean, or median). No external lookups or predictions are performed.","failureModes":["Rows array is empty or missing — validation error","More than 200 rows supplied — rejected with max-items error","missing_values or total_values outside allowed numeric range — rejected","date field not in YYYY-MM-DD format — pattern validation failure","Invalid fill method or field enum value — schema validation error","row_id missing or empty string — minLength validation failure"],"whenToPreferThis":"Choose this endpoint when you have up to 200 tabular rows of null-coverage data (missing_values + total_values per group/date) and need both a category frequency distribution AND a missing-value imputation (zero, mean, or median) in a single $0.01 call. It is ideal for lightweight, local data-quality audits without any external API calls, predictions, or professional assessments. Prefer it over general-purpose analytics when you specifically need null-coverage metrics grouped by dataset_group with explicit fill.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-16T06:47:38.389Z","isFirstParty":false,"canonicalSlug":"null-coverage-analyzer-category-frequencies-missing-value-fill-ad1742c8"}