Open Source Python Data Visualization Apps for Android

Python Data Visualization Apps for Android

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Browse free open source Python Data Visualization Apps for Android and projects below. Use the toggles on the left to filter open source Python Data Visualization Apps for Android by OS, license, language, programming language, and project status.

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  • 1
    Every Door

    Every Door

    A dedicated app for collecting thousands of POI for OpenStreetMap

    The best OpenStreetMap editor for POIs and entrances. The best app for on-the-ground surveying for OpenStreetMap! Add shops and amenities, survey benches and trees, collect addresses, or use them as walking papers. This editor does not make you think. Just go to a mall, and start Every Door. You'll see mapped shops around you: tap on the checkmark for any that are still there, and add shops that are not on the map. That's the entire process: you can keep your entire town up-to-date thanks to this simple editor. There is also a micromapping mode for verifying and adding benches and street lamps. And an entrance mode for adding building attributes and entrances, which are merged automatically into building contours.
    Downloads: 1 This Week
    Last Update:
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  • 2
    XCSoar

    XCSoar

    ... the open-source glide computer

    XCSoar is a tactical glide computer for Android, Linux, macOS, and Windows.
    Downloads: 4 This Week
    Last Update:
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  • 3
    Portable Linux

    Portable Linux

    Portable Ubuntu Linux for Scientific Computing

    Released August 22, 2013 Lubuntu Blends: Biochemistry 13.04 (Raring) v5.44 Linux Kernel Image 3.8.0-29 Lubuntu Blends are pre-installed Wubi disk image remixes of Ubuntu and Debian Science meta packages, A custom boot loader allows installations to be copied and automatically booted from most external or USB flash drives. Once up and running, use earlier Lubuntu Remix README instructions here until documentation is updated. https://sourceforge.net/projects/portable-linux/files/ Installation 1. Download the Wubi installer http://releases.ubuntu.com/saucy/wubi.exe 2. Install any flavor of Ubuntu. 3. Swap out the root.disk with the ones provided here. Overview LAMP stack running on localhost (127.0.0.1). Scientific, productivity & media packages include R (Rattle Data Miner), GridEngine, Condor, cooperative computing tools, WINE, LibreOffice, Evolution, Clinica, Neuro Debian Desktop, PsycoPy, OpenVibe, 3DSlicer, Paraview, Openshot. Cheers, Gregory Remington
    Downloads: 8 This Week
    Last Update:
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  • 4
    MMdnn

    MMdnn

    Tools to help users inter-operate among deep learning frameworks

    MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML. MMdnn is a comprehensive and cross-framework tool to convert, visualize and diagnose deep learning (DL) models. The "MM" stands for model management, and "dnn" is the acronym of deep neural network. We implement a universal converter to convert DL models between frameworks, which means you can train a model with one framework and deploy it with another. During the model conversion, we generate some code snippets to simplify later retraining or inference. We provide a model collection to help you find some popular models. We provide a model visualizer to display the network architecture more intuitively. We provide some guidelines to help you deploy DL models to another hardware platform.
    Downloads: 0 This Week
    Last Update:
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  • 5
    sadsa

    sadsa

    SADSA (Software Application for Data Science and Analytics)

    SADSA (Software Application for Data Science and Analytics) is a Python-based desktop application designed to simplify statistical analysis, machine learning, and data visualization for students, researchers, and data professionals. Built using Python for the GUI, SADSA provides a menu-driven interface for handling datasets, applying transformations, running advanced statistical tests, machine learning algorithms, and generating insightful plots — all without writing code.
    Downloads: 0 This Week
    Last Update:
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