{"uid":"cap_EwAAY5YMelRJLXFjVcMZq","slug":"water-service-coverage-numeric-row-ordering-trailing-mean-series-7bc6d285","name":"Water Service Coverage — Numeric Row Ordering + Trailing Mean Series","description":"Water service coverage — Numeric row ordering + Trailing mean series: Numeric row ordering + Trailing mean series 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-19-115?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"},"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_4w79_6xyltDqfEK5OaTSS","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":"Runs two local analytical reports on water service coverage data: numeric row ordering and a trailing moving-average series for served_households or total_households fields.","exampleAgentPrompt":"I have water service coverage records for several regions with served_households and total_households columns — can you sort those rows numerically by served_households and also compute a trailing mean with a window of 3 for me across up to 200 rows?","exampleUseCases":[{"title":"Regional coverage ranking for utility audit","prompt":"I have monthly water service data for 12 regions with served_households and total_households — sort all the rows numerically by served_households so I can see which regions are lowest and highest coverage."},{"title":"Smoothing noisy household series for trend reporting","prompt":"Our water coverage dataset has some noisy month-to-month swings in total_households — can you run a trailing mean with a window of 4 on the total_households field so I can see the smoothed trend?"},{"title":"Preparing ranked and smoothed data for dashboard","prompt":"I need two reports on our water service records: first, rank all rows by served_households in numeric order, and second, compute a 5-period trailing mean on served_households — we have about 150 rows total."}],"resultDescription":"Returns two analytical reports derived from the supplied water service coverage rows: (1) the rows reordered numerically by the values in the selected field (served_households or total_households), and (2) a trailing moving-average series computed over the specified window size for that same field. No external data is fetched; all computation is performed locally on the submitted rows.","failureModes":["Fewer than 1 or more than 200 rows submitted — rejected with validation error","Window size larger than number of submitted rows — trailing mean may be undefined for early rows","Missing required fields (row_id, region, date, served_households, total_households) — row rejected or error returned","Invalid date format (not YYYY-MM-DD) — validation failure","Null numeric values in the selected field — may produce nulls or gaps in trailing mean output","Malformed JSON payload — 400 bad request"],"whenToPreferThis":"Choose this endpoint when you have tabular water service coverage data (with served_households and total_households columns) and need two specific local analytics in one call: numeric row ordering/ranking and a trailing moving-average series. It is ideal for offline/batch analytical preprocessing of utility datasets without needing live lookups, predictions, or external enrichment. At $0.01 USDC for both reports on up to 200 rows, it is cost-effective for small-to-medium dataset analysis.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T12:35:28.332Z","isFirstParty":false,"canonicalSlug":"water-service-coverage-numeric-row-ordering-trailing-mean-series-7bc6d285"}