{"uid":"cap_j4ewpEJTeabaxEO1jK-Z2","slug":"land-parcel-observations-string-normalisation-equal-width-histogram-2e4cea51","name":"Land Parcel Observations — String Normalisation + Equal-Width Histogram","description":"Land parcel observations — String normalisation + Equal-width histogram: String normalisation + Equal-width histogram 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-14-031?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"bins":{"type":"integer","default":5,"maximum":30,"minimum":1},"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"}}},"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_eiI5rD4-RVHye7GU5C1qb","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 string normalisation and an equal-width histogram analysis on supplied land parcel observation records (area_m2, perimeter_m) for up to 200 rows.","exampleAgentPrompt":"I have 50 land parcel records with area_m2 and perimeter_m values — can you run string normalisation and an equal-width histogram with 10 bins on the area_m2 field and give me both reports?","exampleUseCases":[{"title":"Survey parcel size distribution analysis","prompt":"I've got 120 land parcel observation records from our latest cadastral survey with area_m2 and perimeter_m — can you normalise the string fields and generate an equal-width histogram with 8 bins for area_m2 so I can see how parcel sizes are distributed?"},{"title":"Perimeter measurement frequency binning","prompt":"Can you take these 80 land parcel rows and produce a 5-bin equal-width histogram on the perimeter_m field, along with string normalisation? I want to understand how perimeter lengths cluster across the dataset."},{"title":"Multi-group parcel data cleanup and summary","prompt":"I have parcel observation data from two station groups — about 150 rows total — with area_m2 measurements. Please run string normalisation and give me an equal-width histogram using 12 bins so I can spot any outliers in the area distribution."}],"resultDescription":"Returns two analytical reports: (1) a string normalisation report covering the text fields in the submitted records, and (2) an equal-width histogram report for the selected numeric field (area_m2 or perimeter_m) divided into the specified number of bins, including bin boundaries and row counts per bin. Both reports are computed locally from the supplied data with no external lookups.","failureModes":["More than 200 rows submitted — request rejected with validation error","bins value outside 1–30 range — validation error returned","Missing required fields (row_id, date, area_m2, perimeter_m, station_group) — schema validation failure","Invalid date format (not YYYY-MM-DD) — schema rejection","All values null for selected field — histogram cannot be computed","Payment not included or insufficient — x402 payment required response"],"whenToPreferThis":"Choose this endpoint when you have land parcel observation records (with area_m2 and perimeter_m fields) and need both string normalisation and an equal-width histogram in a single low-cost call. It is ideal for small-to-medium datasets (up to 200 rows) where no external data lookup or prediction is needed — purely local analytical computation on your supplied data. At $0.01 USDC for both reports, it is cost-effective for data cleaning and exploratory distribution analysis on parcel datasets.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-03T12:43:03.948Z","isFirstParty":false,"canonicalSlug":"land-parcel-observations-string-normalisation-equal-width-histogram-2e4cea51"}