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.)

A detailed overview on how to use EOmaps is given in the ⚙ Usage section.
Make sure to checkout the 🌐 EOmaps examples for an overview of the capabilities (incl. source code)!