{"uid":"cap_1YVTKgQtoFgC9cKICXirx","slug":"land-parcel-observations-category-frequencies-two-measure-correlation-52e3462f","name":"Land Parcel Observations — Category Frequencies + Two-Measure Correlation","description":"Land parcel observations — Category frequencies + Two-measure correlation: Category frequencies + 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-14-108?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_cr8baEQIXRRtF9TJtTcEq","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":"Computes category frequency counts and Pearson/Spearman correlation between area_m2 and perimeter_m for up to 200 supplied land parcel observation rows.","exampleAgentPrompt":"Can you analyze these 150 land parcel records — compute the frequency of each station_group category and also calculate the correlation between area_m2 and perimeter_m? The rows have fields: row_id, station_group, date, area_m2, and perimeter_m.","exampleUseCases":[{"title":"Station group frequency audit","prompt":"I have 80 land parcel observation records each tagged with a station_group like 'group-a' or 'group-b'. Can you count how many records fall into each category and also check how strongly area_m2 and perimeter_m correlate across the whole dataset?"},{"title":"Parcel shape consistency check","prompt":"Here are 200 parcel survey rows with area and perimeter measurements. Run a correlation analysis between area_m2 and perimeter_m to see if larger parcels consistently have longer perimeters, and also give me the frequency breakdown by station_group."},{"title":"Land survey data QA report","prompt":"I've exported 60 rows from our land parcel database with date, station_group, area_m2, and perimeter_m. Can you produce a category frequency table for station_group and tell me the statistical correlation between the two numeric measures?"}],"resultDescription":"Returns two independent analytical reports: (1) a frequency table showing how many rows belong to each station_group category, and (2) a correlation metric (e.g. Pearson r) between the area_m2 and perimeter_m numeric columns, computed locally without any external data lookup or prediction.","failureModes":["More than 200 rows submitted — request rejected or truncated","Missing required fields (row_id, station_group, date, area_m2, perimeter_m) cause validation errors","All-null values in area_m2 or perimeter_m prevent correlation computation","Malformed date strings not matching YYYY-MM-DD pattern rejected","Payment of 0.01 USDC not provided or x402 protocol failure blocks the call"],"whenToPreferThis":"Choose this endpoint when you have pre-collected land parcel observation data (up to 200 rows) and need both a categorical frequency breakdown and a two-variable numeric correlation in a single API call at minimal cost. It is ideal for offline/batch statistical QA on parcel datasets where no live data lookup, geospatial enrichment, or external prediction is needed.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-29T12:54:10.824Z","isFirstParty":false,"canonicalSlug":"land-parcel-observations-category-frequencies-two-measure-correlation-52e3462f"}