geeViz.chartingLib

Zonal Summary & Charting Library for GEE

geeViz.chartingLib provides a Python pipeline for running zonal statistics on ee.Image / ee.ImageCollection objects and producing Plotly charts (time series, bar, sankey). It mirrors the logic in the geeView JS frontend so that both human users and AI agents have a clean, efficient API for this common workflow.

Functions

chart_bar(df[, colors, title, y_label, ...])

Create a Plotly bar chart from a single-Image zonal stats DataFrame.

chart_grouped_bar(df[, colors, title, ...])

Create a grouped (or stacked) bar chart for multi-feature zonal stats.

chart_sankey(sankey_df, class_names, ...[, ...])

Create a Plotly Sankey diagram from transition data.

chart_time_series(df[, colors, chart_type, ...])

Create a Plotly time series chart from a zonal stats DataFrame.

detect_geometry_type(geometry)

Determine whether the input geometry represents a single region or multiple.

get_obj_info(ee_obj[, band_names])

Detect the type of a GEE object and read its thematic class metadata.

parse_continuous_results(raw_dict, obj_info, ...)

Parse continuous (mean/median/etc.) reduction results into a DataFrame.

parse_thematic_results(raw_dict, obj_info, ...)

Parse frequency histogram reduction results into a DataFrame with class names as columns.

prepare_for_reduction(ee_obj, obj_info[, ...])

Prepare a GEE object for reduction by stacking an ImageCollection into a single multi-band image.

prepare_sankey_data(ee_collection, ...[, ...])

Build a Sankey diagram dataset from class transitions across time periods.

reduce_region(image, geometry, reducer[, ...])

Run image.reduceRegion with sensible defaults.

reduce_regions(image, features, reducer[, ...])

Run image.reduceRegions and return the result as a DataFrame.

summarize_and_chart(ee_obj, geometry[, ...])

Run zonal statistics and produce a chart in one call.

zonal_stats(ee_obj, geometry[, band_names, ...])

Compute zonal statistics for a GEE Image or ImageCollection over a geometry.