{"uid":"cap_SKqeTpRlszaz-pvt-UDAg","slug":"land-parcel-observations-numeric-row-ordering-explicit-missing-value-4ec390f2","name":"Land Parcel Observations — Numeric Row Ordering + Explicit Missing-Value Fill","description":"Land parcel observations — Numeric row ordering + Explicit missing-value fill: Numeric row ordering + Explicit missing-value fill for supplied land parcel observations records (area_m2, perimeter_m). 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-weather-14-124?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","station_group","date","area_m2","perimeter_m"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"area_m2":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"perimeter_m":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"station_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","area_m2":10,"perimeter_m":1,"station_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","area_m2":20,"perimeter_m":2,"station_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","area_m2":15,"perimeter_m":3,"station_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","area_m2":30,"perimeter_m":4,"station_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["area_m2","perimeter_m"],"type":"string","default":"area_m2"},"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_v2Z_g6CrgebOxyBLxN3vv","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 land parcel observation rows numerically and fills missing area_m2 or perimeter_m values using zero, mean, or median imputation, returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"I have up to 200 land parcel observations with area_m2 and perimeter_m fields, some values are missing — can you sort the rows numerically and fill in the missing area_m2 values using median imputation, then give me two analytical reports?","exampleUseCases":[{"title":"Clean surveyor parcel dataset nulls","prompt":"I've got a batch of land parcel survey records where some area_m2 readings are null — sort them in numeric row order and fill in those missing values using the median of the existing ones, then give me the two reports."},{"title":"Zero-fill missing perimeter measurements","prompt":"For this set of parcel observations, I need the rows ordered numerically and any missing perimeter_m values replaced with zero — can you run the two reports on that cleaned data?"},{"title":"Mean imputation for property boundary data","prompt":"I have around 150 land parcel records across multiple station groups with some missing area_m2 entries — please order them by row ID numerically, apply mean fill to the missing area values, and return both analytical reports."}],"resultDescription":"Two structured analytical reports covering the supplied land parcel observation rows after numeric row ordering and explicit missing-value fill (using zero, mean, or median) for the selected field (area_m2 or perimeter_m). Reports are generated from local analytical engines with no live lookups or external data.","failureModes":["Rows array empty or missing — minItems:1 validation error","More than 200 rows submitted — maxItems:200 exceeded","Invalid date format (not YYYY-MM-DD) — pattern validation failure","Field value not in enum [area_m2, perimeter_m] — schema validation error","Method value not in enum [zero, mean, median] — schema validation error","row_id missing or empty string — minLength:1 validation failure","Numeric values outside ±1,000,000,000,000 bounds — schema rejection"],"whenToPreferThis":"Choose this endpoint when you have land parcel observation data (with area_m2 and perimeter_m fields) that needs both numeric row ordering and missing-value imputation in a single call, returning two reports at once. It is ideal for preprocessing survey or cadastral datasets before analysis. Prefer it over generic data-cleaning tools when your data fits the parcel schema and you want statistically sound fill (zero, mean, or median) with no external dependencies or side effects.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T12:40:57.049Z","isFirstParty":false,"canonicalSlug":"land-parcel-observations-numeric-row-ordering-explicit-missing-value-4ec390f2"}