{"uid":"cap_mWWkKQ_C6xBrAGjIm0VbY","slug":"tree-canopy-observations-equal-width-histogram-explicit-missing-value-052ae395","name":"Tree Canopy Observations — Equal-Width Histogram + Explicit Missing-Value Fill","description":"Tree canopy observations — Equal-width histogram + Explicit missing-value fill: Equal-width histogram + Explicit missing-value fill for supplied tree canopy observations records (canopy_m2, plot_m2). 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-17-175?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","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_AGuHtMtDW75XBghaMKoih","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 an equal-width histogram and fills missing values for tree canopy observation records (canopy_m2, plot_m2) using a chosen fill method, returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"I have 50 tree canopy observation records with canopy_m2 and plot_m2 fields — some canopy_m2 values are null. Can you build a 10-bin equal-width histogram on canopy_m2 and fill the missing canopy_m2 values using median imputation?","exampleUseCases":[{"title":"Urban tree canopy coverage analysis","prompt":"I've got 120 tree plot observations from our city survey — can you create a 8-bin histogram of the canopy_m2 values and fill in any missing canopy_m2 entries using the median so I can see the full distribution?"},{"title":"Plot size distribution for land management","prompt":"Here are 75 plot records from our forest monitoring program. I need a 5-bin equal-width histogram of plot_m2 and want any missing plot_m2 values replaced with the mean — can you run those two reports?"},{"title":"Missing data imputation before ML pipeline","prompt":"Before I feed my tree canopy dataset into a model, I need to fill nulls in canopy_m2 using zero and also get a 15-bin histogram to check if the distribution looks reasonable — I have about 180 rows with row_id, station_group, date, canopy_m2, and plot_m2."}],"resultDescription":"Returns two analytical reports for the supplied records: (1) an equal-width histogram showing bin boundaries and frequency counts for the selected field (canopy_m2 or plot_m2) divided into the specified number of bins, and (2) an explicit missing-value fill report showing which rows had null values and what values were substituted using the chosen fill method (zero, mean, or median).","failureModes":["Exceeding 200 rows returns a validation error","Invalid date format (not YYYY-MM-DD) causes schema rejection","bins value outside 1–30 range fails validation","All values null for selected field may produce degenerate histogram","row_id missing or empty string triggers required field error","Payment of 0.01 USDC not included causes 402 response"],"whenToPreferThis":"Choose this endpoint when you have tabular tree canopy or plot area observation data and need both a distributional summary (histogram) and missing-value imputation in a single API call. It is purpose-built for ecological/forestry datasets with canopy_m2 and plot_m2 fields, processes up to 200 rows locally without external data lookups, and costs only $0.01 USDC for both reports together. Prefer it over general-purpose analytics when you specifically need equal-width binning with explicit null-fill on these domain-specific fields.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T18:51:09.817Z","isFirstParty":false,"canonicalSlug":"tree-canopy-observations-equal-width-histogram-explicit-missing-value-052ae395"}