{"uid":"cap_rFlHNVmbrKAFsclG1G7eR","slug":"tree-canopy-observations-equal-width-histogram-date-by-category-pivot-44f4f6af","name":"Tree Canopy Observations — Equal-Width Histogram + Date by Category Pivot","description":"Tree canopy observations — Equal-width histogram + Date by category pivot: Equal-width histogram + Date by category pivot 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-17-173?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"}}},"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_joPANM0QE9Sxb8e5dRlUO","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":"Generates an equal-width histogram and a date-by-category pivot table for tree canopy observation records (canopy_m2, plot_m2) — two analytical reports from supplied data, no external lookups.","exampleAgentPrompt":"Analyze my tree canopy survey records — here are 4 observations with canopy_m2 and plot_m2 values across two station groups (group-a and group-b) from October 2026. Give me a 5-bin equal-width histogram and a date-by-category pivot for the canopy_m2 field.","exampleUseCases":[{"title":"Urban tree survey distribution analysis","prompt":"I have 120 urban tree plot observations with canopy_m2 and plot_m2 measurements across 6 monitoring stations from March to June 2025. Can you generate a 10-bin equal-width histogram and a date-by-station pivot table for the canopy_m2 values so I can see how canopy coverage is distributed?"},{"title":"Reforestation monitoring pivot report","prompt":"I've collected 80 canopy observation records from our reforestation project, each tagged with a station_group and a date in 2024. Please run a date-by-category pivot and a 7-bin histogram on the plot_m2 field so I can compare plot sizes across groups over time."},{"title":"Ecology research canopy summary","prompt":"For my ecology paper I need a quick statistical breakdown of canopy area data — I have 50 rows of field measurements with station groups and dates from 2023. Can you produce a 5-bin histogram and a date-by-category pivot on canopy_m2 for me?"}],"resultDescription":"Returns two analytical reports derived from the supplied tree canopy observation rows: (1) an equal-width histogram showing frequency distribution of the chosen field (canopy_m2 or plot_m2) across the specified number of bins, and (2) a date-by-category pivot table cross-tabulating measurements by date and station_group. Both reports are computed locally from the provided data with no external data sources.","failureModes":["Exceeding 200 rows returns a validation error — batch must be split","Missing required fields (row_id, date, canopy_m2, plot_m2) causes row rejection or error","Invalid date format (not YYYY-MM-DD) triggers schema validation failure","Requesting more than 30 bins or fewer than 1 bin returns a validation error","Null values in canopy_m2 or plot_m2 may affect histogram bin computation","Payment failure (insufficient USDC balance) blocks the request at the x402 layer"],"whenToPreferThis":"Choose this endpoint when you have up to 200 tree canopy or plot observation records and need both a histogram distribution and a date-by-category pivot in a single low-cost call ($0.01 USDC). It is ideal for ecological, forestry, or urban greenery datasets where canopy_m2 and plot_m2 are the primary numeric fields and you need fast offline analytics without any live data lookup or external enrichment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-25T12:32:34.066Z","isFirstParty":false,"canonicalSlug":"tree-canopy-observations-equal-width-histogram-date-by-category-pivot-44f4f6af"}