Open Source Python Data Visualization Software

Python Data Visualization Software

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

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    Build Agents and Models on One Platform

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  • 1
    Matplotlib

    Matplotlib

    matplotlib: plotting with Python

    Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things possible. Matplotlib ships with several add-on toolkits, including 3D plotting with mplot3d, axes helpers in axes_grid1 and axis helpers in axisartist. A large number of third party packages extend and build on Matplotlib functionality, including several higher-level plotting interfaces (seaborn, HoloViews, ggplot, ...), and a projection and mapping toolkit (Cartopy). Matplotlib is the brainchild of John Hunter (1968-2012), who, along with its many contributors, have put an immeasurable amount of time and effort into producing a piece of software utilized by thousands of scientists worldwide. Matplotlib is a Sponsored Project of NumFOCUS, a 501(c)(3) nonprofit charity in the United States. Matplotlib has support for visualizing information with a wide array of colors and colormaps.
    Downloads: 13 This Week
    Last Update:
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  • 2
    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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  • 3

    Waterloo

    Java-based scientific graphics

    Java-based scientific graphics with support for Java, Groovy, MATLAB, Python, the R statistical environment, Scala and SciLab.
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    Downloads: 0 This Week
    Last Update:
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