{"uid":"cap_D1fUfLCyhOPg2zMYClJUg","slug":"null-coverage-analytics-base-100-series-missing-value-fill-ab983ed2","name":"Null Coverage Analytics: Base-100 Series + Missing-Value Fill","description":"Null coverage — Base-100 series + Explicit missing-value fill: Base-100 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-03-169?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"},"base_index":{"type":"integer","default":0,"maximum":199,"minimum":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_O2lN2A8jaVPrJEtoTKrjj","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 Base-100 indexed time series and fills missing values (zero, mean, or median) for supplied null-coverage records, producing 2 analytical reports for up to 200 rows.","exampleAgentPrompt":"I have a dataset with missing_values and total_values per row across two groups over several dates — can you build a Base-100 indexed series starting at row index 0 and fill any missing_values using median imputation? Here are up to 200 rows: group-a on 2026-10-01 has 10 missing out of 1 total, group-b on 2026-10-02 has 20 missing out of 2 total, group-a on 2026-10-03 has 15 missing out of 3 total.","exampleUseCases":[{"title":"Data quality audit by group","prompt":"I have daily null coverage records for two dataset groups over October 2026 — each row has a row_id, dataset_group, date, missing_values, and total_values. Can you produce a Base-100 indexed series anchored at row 0 and fill any missing_values gaps using the median so I can compare data completeness between group-a and group-b?"},{"title":"Time series normalization for reporting","prompt":"I need to normalize my missing-value counts into a Base-100 time series so I can track trends over time. I have 150 rows with dates, dataset groups, and missing/total value counts — please index from row 0 and use zero-fill for any nulls in the missing_values field."},{"title":"Mean imputation before downstream pipeline","prompt":"Before I pass my dataset into a downstream model, I need to fill all null entries in the total_values field using mean imputation and also get a Base-100 indexed series starting at index 0. I have about 80 rows with row IDs, groups, and dates — can you run both reports?"}],"resultDescription":"Returns two analytical reports: (1) a Base-100 normalized time series indexed from the specified base_index row, and (2) an explicit missing-value-filled dataset where nulls in the chosen field are replaced using the selected method (zero, mean, or median). Both reports are computed locally from the supplied data with no external lookups.","failureModes":["Rows array is empty or exceeds 200 items — validation error","missing_values or total_values outside allowed numeric range (±1 trillion) — rejected","date field does not match YYYY-MM-DD pattern — schema validation failure","base_index out of range (0–199) — error","field or method enum value not recognized — schema rejection","Payment of 0.01 USDC not provided — 402 payment required"],"whenToPreferThis":"Choose this endpoint when you need both a Base-100 indexed time series and explicit missing-value imputation (zero, mean, or median) computed together in a single call on up to 200 rows of null-coverage data. It is ideal for offline/batch data quality analysis where no live data lookup or external prediction is needed and cost must be minimal ($0.01 USDC for 2 reports).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:58:11.940Z","isFirstParty":false,"canonicalSlug":"null-coverage-analytics-base-100-series-missing-value-fill-ab983ed2"}