Welcome to the documentation for EOmaps!
In short, EOmaps serves as a layer on top of matplotlib and cartopy to tackle the following points:
- 🔴 Speed-up and simplify the creation of maps
directly plot from unstructured 1D datasets (e.g. lists of coordinates and values)
reduce overhead to speed-up plotting of large datasets (>1M datapoints)
- 🔵 Allow a meaningful representation of datapoints as shapes with geographical dimensions
geodesic circles, ellipses, rectangles etc.
Voroni-diagrams, Delaunay triangulations
- 🟠 Offer a versatile set of tools to customize the appearance of the maps
add WebMap layers, overlays, markers, annotations etc. with only 1 line of code
classify the data and visualize the data-distribution with a colored histogram
plot multiple maps in one figure
- 🟡 Directly use the created maps as interactive data-analysis widgets
compare/overlay multiple data layers, WebMaps etc. in a single plot
add markers and annotations etc. by clicking on the map
use the mouse or keyboard to trigger custom functions on selected datapoints
(EOmaps retains access to all underlying functionalities of matplotlib and cartopy.)