{"uid":"cap_mGIkj5qe6zfm_lyAvHPl6","slug":"water-service-coverage-numeric-row-ordering-explicit-missing-value-fill-66d0df8a","name":"Water Service Coverage — Numeric Row Ordering + Explicit Missing-Value Fill","description":"Water service coverage — Numeric row ordering + Explicit missing-value fill: Numeric row ordering + Explicit missing-value fill for supplied water service coverage records (served_households, total_households). 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-economics-19-124?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","region","date","served_households","total_households"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"region":{"type":"string","default":"","maxLength":80},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"total_households":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"served_households":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","region":"group-a","row_id":"row-1","total_households":1,"served_households":10},{"date":"2026-10-02","region":"group-b","row_id":"row-2","total_households":2,"served_households":20},{"date":"2026-10-03","region":"group-a","row_id":"row-3","total_households":3,"served_households":15},{"date":"2026-10-04","region":"group-b","row_id":"row-4","total_households":4,"served_households":30}],"maxItems":200,"minItems":1},"field":{"enum":["served_households","total_households"],"type":"string","default":"served_households"},"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_zFYjsdUJoue9Dm_KxTAw-","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":"Sorts water service coverage rows numerically and fills missing served_households or total_households values using zero, mean, or median imputation, producing 2 analytical reports for up to 200 rows.","exampleAgentPrompt":"I have up to 200 rows of water service coverage data with some missing served_households values — can you sort the rows numerically and fill those gaps using median imputation, then give me two analytical reports?","exampleUseCases":[{"title":"Imputing missing household coverage for municipal report","prompt":"I have a dataset of 150 water service coverage records for various regions and some of the served_households values are null — please fill those missing values using the median and sort all rows numerically so I can use them in our quarterly municipal report."},{"title":"Zero-filling total_households for data pipeline","prompt":"Can you take my water utility records and fill any missing total_households values with zero, then order the rows numerically? I need two clean analytical reports to feed into our data pipeline."},{"title":"Mean imputation for regional water coverage audit","prompt":"I'm auditing water service coverage across 80 regions and there are gaps in the served_households column — fill those missing values using the mean, sort the records by row number, and produce the two analytical reports for me."}],"resultDescription":"Returns 2 analytical reports covering up to 200 water service coverage rows, with rows sorted numerically by row_id and missing values in the specified field (served_households or total_households) filled using the chosen method (zero, mean, or median). No external data is fetched; all computation is performed locally on the supplied data.","failureModes":["More than 200 rows submitted — request rejected due to maxItems constraint","Missing required fields (row_id, region, date, served_households, total_households) — validation error","Invalid date format (not YYYY-MM-DD) — schema validation failure","Invalid method or field enum value — request rejected","Payment not received or insufficient USDC — request not processed"],"whenToPreferThis":"Choose this endpoint when you have water service coverage records (served_households, total_households) with missing values that need imputation and numeric row ordering, and you want two bundled analytical reports at low cost ($0.01 USDC for up to 200 rows). It is a purely local, deterministic computation — ideal when you do not need live data lookups, predictions, or external integrations.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-30T12:35:57.799Z","isFirstParty":false,"canonicalSlug":"water-service-coverage-numeric-row-ordering-explicit-missing-value-fill-66d0df8a"}