{"uid":"cap_9cqCFuPX76lImjALD7EsT","slug":"land-parcel-observations-string-normalisation-two-measure-correlation-0c59606a","name":"Land Parcel Observations — String Normalisation + Two-Measure Correlation","description":"Land parcel observations — String normalisation + Two-measure correlation: String normalisation + Two-measure correlation 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-14-033?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}}},"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_cpk_UdhzplBxOHxl7ScRq","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":"Normalises string fields and computes a two-measure correlation analysis (area_m2 vs perimeter_m) for up to 200 land parcel observation records.","exampleAgentPrompt":"I have up to 200 land parcel observation rows with area_m2 and perimeter_m measurements and station group labels — can you run string normalisation on the group fields and compute a two-measure correlation between area and perimeter across all the records?","exampleUseCases":[{"title":"Parcel survey data quality check","prompt":"I've got a batch of land parcel survey records with area in square metres, perimeter in metres, and site group names that need cleaning — can you normalise the group strings and tell me how strongly area and perimeter correlate across the 150 rows?"},{"title":"Agricultural plot measurement analysis","prompt":"Here are 80 agricultural plot observations with area_m2, perimeter_m, and farm group labels across several dates — run string normalisation on the group names and give me a correlation report between the two numeric measures."},{"title":"Urban planning parcel dataset cleanup","prompt":"I'm preparing a land-use dataset with parcel area and perimeter readings from multiple station groups — can you clean up the station group strings and compute the correlation between area_m2 and perimeter_m for these 200 rows?"}],"resultDescription":"Two analytical reports: (1) a string normalisation report cleaning the station_group and other string fields across the submitted rows, and (2) a two-measure correlation report quantifying the statistical relationship between area_m2 and perimeter_m across up to 200 rows. No external lookups or predictions are included.","failureModes":["More than 200 rows submitted — request rejected with validation error","Missing required fields (row_id, date, area_m2, perimeter_m, station_group) cause row-level errors","Malformed date strings not matching YYYY-MM-DD pattern rejected","All-null numeric columns may prevent meaningful correlation computation","Payment failure returns 402 before processing begins"],"whenToPreferThis":"Choose this endpoint when you have land parcel observation records (with area_m2 and perimeter_m) that need both string field normalisation and a statistical correlation between the two numeric measures in a single cheap call. It is ideal for batch pre-processing of survey or cadastral data before downstream modelling. It is not suitable for real-time lookups, external data enrichment, geospatial operations, or datasets exceeding 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-28T12:43:29.346Z","isFirstParty":false,"canonicalSlug":"land-parcel-observations-string-normalisation-two-measure-correlation-0c59606a"}