{"uid":"cap_ZQErAbw3ux4_sFZ9e78Sj","slug":"tree-canopy-observations-quality-audit-string-normalisation-missing-0eb03300","name":"Tree Canopy Observations — Quality Audit, String Normalisation & Missing Value Fill","description":"Tree canopy observations — Record quality audit + String normalisation + Explicit missing-value fill: Record quality audit + String normalisation + Explicit missing-value fill for supplied tree canopy observations records (canopy_m2, plot_m2). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-weather-17-208?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","station_group","date","canopy_m2","plot_m2"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"plot_m2":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"canopy_m2":{"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","plot_m2":1,"canopy_m2":10,"station_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","plot_m2":2,"canopy_m2":20,"station_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","plot_m2":3,"canopy_m2":15,"station_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","plot_m2":4,"canopy_m2":30,"station_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["canopy_m2","plot_m2"],"type":"string","default":"canopy_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_sW46eBAr8-YF5ZaO_K4YQ","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 three analytical reports on tree canopy observation records: a record quality audit, string normalisation, and explicit missing-value fill for canopy_m2 and plot_m2 fields.","exampleAgentPrompt":"Can you audit the quality of my tree canopy observation records, normalise the station group strings, and fill any missing canopy_m2 values using median imputation? I have about 50 rows with fields for row_id, station_group, date, canopy_m2, and plot_m2.","exampleUseCases":[{"title":"Ecological survey data cleanup","prompt":"I've got 120 rows of tree canopy survey data with some messy station group names and a bunch of missing canopy_m2 values — can you run a quality audit, normalise the strings, and fill those gaps using the median?"},{"title":"Plot measurement validation for forestry report","prompt":"Before I submit this forestry report, can you check the quality of my 80 plot observation records, fix any inconsistent station group strings, and fill missing plot_m2 values with zero?"},{"title":"Automated QA pipeline for canopy monitoring","prompt":"Every week I get new tree canopy readings — can you audit the record quality, normalise station labels, and impute any missing canopy_m2 entries using the mean so I always have a clean dataset ready?"}],"resultDescription":"Three independent reports for up to 200 submitted rows: (1) a record quality audit flagging issues per row, (2) a string normalisation report for station_group and other text fields, and (3) a missing-value fill report showing imputed values for the chosen field (canopy_m2 or plot_m2) using the selected method (zero, mean, or median).","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, station_group, date, canopy_m2, plot_m2) causes rejection","Invalid date format (not YYYY-MM-DD) triggers a schema error","Numeric values outside allowed range cause rejection","Invalid enum value for method or field results in a schema error"],"whenToPreferThis":"Choose this endpoint when you have tree canopy or forestry plot observation records (with canopy_m2 and plot_m2 measurements) that need batch data quality auditing, string normalisation, and missing value imputation in a single cost-effective call. It is well-suited for ecological data pipelines, pre-analysis data cleaning, or before generating reports from survey data. Not appropriate for live data lookup, predictive modelling, or datasets exceeding 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T18:52:00.874Z","isFirstParty":false,"canonicalSlug":"tree-canopy-observations-quality-audit-string-normalisation-missing-0eb03300"}