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Tree Canopy Observations — Equal-Width Histogram + Explicit Missing-Value Fill
x402
Tree Canopy Observations — Equal-Width Histogram + Explicit Missing-Value Fill is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-26).
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.
Price / call$0.01
Success—
StatusUnknown
How this service works
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.
Output
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).
Example use cases
Urban tree canopy coverage analysis
“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?”
Plot size distribution for land management
“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?”
Missing data imputation before ML pipeline
“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.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-17-175?utm_source=zero.xyzWhen to prefer
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.
Side effects
- 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
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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