{"uid":"cap_2elUDdWoQYb0riR3k1xWV","slug":"null-coverage-analytics-trailing-mean-series-explicit-missing-value-875826d2","name":"Null Coverage Analytics — Trailing Mean Series + Explicit Missing-Value Fill","description":"Null coverage — Trailing mean series + Explicit missing-value fill: Trailing mean series + 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-03-154?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"},"window":{"type":"integer","default":2,"maximum":200,"minimum":2}}},"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_3pN2O6VvZIhdKFD8jWhTD","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 a trailing mean time series and fills missing values explicitly for supplied null coverage records (missing_values, total_values), returning 2 analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you run trailing mean and missing-value fill analytics on my null coverage dataset? I have 4 rows with date, row_id, dataset_group, missing_values, and total_values — use a window of 2, fill with median, and target the missing_values field.","exampleUseCases":[{"title":"Data quality monitoring dashboard","prompt":"I have daily null coverage records for two dataset groups over the past week — can you compute a trailing mean series with a window of 3 and fill any missing values using the mean method on the missing_values field? Here are my rows with row_id, dataset_group, date, missing_values, and total_values."},{"title":"Smoothing noisy missing-value counts","prompt":"My dataset has 50 rows of null coverage data by date and group, and the missing_values counts are pretty noisy — can you apply a trailing mean with a window of 5 and fill gaps with zero so I can see the smoothed trend?"},{"title":"Imputing gaps in total_values for reporting","prompt":"I'm preparing a data quality report and need to fill in the blanks in my total_values column. Can you run the explicit missing-value fill using median and also give me the trailing mean series with a window of 4 across my 100 rows of null coverage records?"}],"resultDescription":"Returns 2 analytical reports: a trailing mean time series computed over the specified window for the selected field, and an explicit missing-value fill report that replaces nulls using the chosen method (zero, mean, or median) — all computed locally on the supplied rows without external lookups.","failureModes":["Fewer than 1 row supplied — request rejected","More than 200 rows supplied — exceeds limit","Invalid date format (non-YYYY-MM-DD) — schema validation failure","Invalid fill method or field enum value — request rejected","Missing required fields (row_id, dataset_group, date) — schema error","Window size outside 2–200 range — validation failure","Payment not included or insufficient — x402 payment required"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of null coverage records with missing_values and total_values fields and need both a trailing mean time series and explicit missing-value imputation in a single call. Ideal for data quality analytics pipelines where you want local, stateless computation without external data lookups or live predictions. At $0.01 USDC for 2 reports, it is cost-effective for lightweight data quality smoothing and gap-filling tasks.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:58:00.281Z","isFirstParty":false,"canonicalSlug":"null-coverage-analytics-trailing-mean-series-explicit-missing-value-875826d2"}