Showing 4 open source projects for "google-visualization-python"

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  • 1
    Viking GPS data editor and analyzer

    Viking GPS data editor and analyzer

    Viking is a free/open source program to manage GPS data

    Viking is a free/open source program to manage GPS data. You can import, plot and create tracks, routes and waypoints, show OSM, Bing Aerial and other maps, geotag images, create routes using OSRM, see real-time GPS position (not in Windows), make maps using Mapnik (not in Windows), control items, etc. It is written in mostly in C (with some C++) & the GTK+3 toolkit. Viking is currently dual managed - with a corresponding Github presence...
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    Downloads: 210 This Week
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  • 2
    libpostal

    libpostal

    A C library for parsing/normalizing street addresses around the world

    A C library for parsing/normalizing street addresses around the world. Powered by statistical NLP and open geo data. libpostal is a C library for parsing/normalizing street addresses around the world using statistical NLP and open data. The goal of this project is to understand location-based strings in every language, everywhere. Addresses and the locations they represent are essential for any application dealing with maps (place search, transportation, on-demand/delivery services,...
    Downloads: 3 This Week
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  • 3
    Navigation Shortest Map Dhaval Kadia

    Navigation Shortest Map Dhaval Kadia

    Shortest Path Navigator with Directions and Distance

    Programmed on Language C. A nano-Infant of GOOGLE-MAP Optimized to Consume some MB instead of 50 GB of RAM This was Programmed Quarter Year ago in 2014
    Downloads: 0 This Week
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  • 4
    OCIViz

    OCIViz

    Visualize data from the opencellid.org project

    Open-Cell-Id-Visualization (OCIViz) ========================= Tools to visualize and analyze opencellid data. Create Googlemaps overlays and statistics. http://www.opencellid.org/ Contains (2013-06) >60million datasets of celltower information worldwide. This project wants to find out: * how much data was gathered where * quality of the coverage * what can you do with the data (localization etc.)
    Downloads: 0 This Week
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