eomaps on Pypi

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A python package to visualize and analyze geographical datasets.

EOmaps aims to provide a comprehensive, flexible, well-documented and easy-to-use API to create publication-ready maps that can directly be used for interactive data analysis.

What can I do with EOmaps?

EOmaps is built on top of matplotlib and cartopy and integrates well with the scientific python infrastructure (e.g., numpy, pandas, geopandas, xarray etc.), allowing you to visualize point-, raster- or vector-datasets provided in almost any format you can imagine, no matter if you're dealing with just a few unsorted datapoints or multi-dimensional stacks of global high-resolution datasets.

Figures created with EOmaps are multi-layered, so you can (transparently) overlay and interactively compare your datasets with ease. With the accompanying GUI widget, you can quickly switch layers, change the layout, examine the large collection of features and web-map services, and explore the capabilities of EOmaps. Once you're map is ready, you can export it as high-resolution image or vector-graphic for further editing. Leveraging the powers of matplotlib, you can also embed interactive maps in Jupyter Notebooks, on a webpage or in GUI frameworks like Qt, tkinter etc..

Important

EOmaps is 100% free and open-source.
As such, acknowledgement is extremely important to allow continued support and development of the package.

Did EOmaps help in your research? $\Rightarrow$ Add a ✔️ Citation to your publication!

BibTeX

The following BibTeX entry uses a DOI that always points to the latest release of EOmaps!
(You can get the DOI for a specific version form the zenodo-page)

@software{eomaps,
  author       = {Raphael Quast},
  title        = {EOmaps: A python package to visualize and analyze geographical datasets.},
  doi          = {10.5281/zenodo.6459598},
  url          = {https://doi.org/10.5281/zenodo.6459598}
}

🚀 Getting started

Head over to the start-page of the 📖 Documentation to get an overview of all available features and functionalities!

Tip

For a quick hands-on introduction, checkout this article on dev.to:
Geographic data visualization and analysis with EOmaps: Interactive maps in python!

🔨 Installation

To install EOmaps (and all its dependencies) with the conda package-manager, simply use:

conda install -c conda-forge eomaps

Tip

To get a huge speedup, use mamba to solve the dependencies!

mamba install -c conda-forge eomaps

Advanced users can also use pip to install EOmaps (and selectively install optional dependency groups)
pip install eomaps       # install only minimal required dependencies
pip install eomaps[all]  # install all optional dependencies
...

For more detailes, have a look at the Installation Instructions or the quickstart guide "From 0 to EOmaps"!

🌟 Contribute

Interested in contributing to EOmaps? Awesome!
You can find detailed instructions on how to setup EOmaps for development in the Contribution Guide!