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https://github.com/deeplook/geohippy

Geo Hipster Pythonic environment for quick geospatial explorations based on popular tools and services.
https://github.com/deeplook/geohippy

analysis geo geospatial jupyter notebooks python

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Geo Hipster Pythonic environment for quick geospatial explorations based on popular tools and services.

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# Geohippy

[![image](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/deeplook/geohippy/blob/master/examples/index.ipynb)
[![image](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/deeplook/geohippy/main?urlpath=lab/tree/examples/index.ipynb)

**The Geo Hipster Pythonic environment for quick geospatial explorations.**

![image](https://github.com/deeplook/geohippy/raw/main/images/cables.gif)

## Introduction

**Geohippy** is a collection of libraries and clients for conducting interactive geospatial analysis and location intelligence in a Jupyter environment. The idea is to have a go-to environment ready to use and test online with no installation needed, or to install and run all or parts of it locally.

Most pieces come from the rich geospatial ecosystem in a Python 3 Jupyter kernel, with a few other kernels (Javascript, Typescript and C++) as a basis for installing others as well. This is a tiny sublist of available packages: JupyterLab, NumPy, GeoPandas, GeoPy, Matplotlib, Seaborn, Plotly, Geemap, Leafmap, Cartopy, Ipyleaflet, Folium, HoloViews, Datashader, Streamlit, Deck.gl, Kepler.gl, Mapbox GL, HERE MapWidget, H3, Ipycanvas, Ipycytoscape, and Xyzservices (the `environment.yml` file lists many more direct dependencies). For now a few example notebooks illustrate only the simplest use-cases for getting started.

More to come...