Showing 4 open source projects for "python & plot"

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  • 1
    Lets-Plot

    Lets-Plot

    Multiplatform plotting library based on Grammar of Graphics

    Lets-Plot is a multiplatform plotting library based on the Grammar of Graphics. The library' design is heavily influenced by Leland Wilkinson work The Grammar of Graphics describing the deep features that underlie all statistical graphics.
    Downloads: 0 This Week
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  • 2
    PyG2Plot

    PyG2Plot

    Python3 binding Plotting Library

    PyG2Plot is a Python 3 binding for AntV G2Plot, an interactive and responsive charting library. It lets Python users create statistical charts through a small amount of code while relying on G2Plot’s grammar-of-graphics foundation. The library is inspired by pyecharts and is designed to make web-based charts available from Python workflows. Users create a Plot instance, set chart options, and render the result as an HTML file, HTML string, notebook preview, or JupyterLab output. ...
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  • 3
    Brand new cheatsheets and handouts

    Brand new cheatsheets and handouts

    Matplotlib 3.1 cheat sheet

    The Brand new cheatsheets and handouts repo is a compact, quick-reference summary of the most commonly used plotting commands and configurations in Matplotlib, intended to serve as a handy reference for experienced users who want to recall syntax or find the right function without digging into full documentation. It lays out common use cases (plot types, styling, figure configuration, saving/exporting, subplot layout, etc.) in a concise and organized format — often serving as a “cheat sheet”...
    Downloads: 0 This Week
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  • 4
    Django REST Pandas

    Django REST Pandas

    Serves up Pandas dataframes via the Django REST Framework

    Django REST Pandas (DRP) provides a simple way to generate and serve pandas DataFrames via the Django REST Framework. The resulting API can serve up CSV (and a number of other formats for consumption by a client-side visualization tool like d3.js. The design philosophy of DRP enforces a strict separation between data and presentation. This keeps the implementation simple, but also has the nice side effect of making it trivial to provide the source data for your visualizations. This...
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