Showing 3 open source projects for "html chart"

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    plotly.py

    plotly.py

    The interactive graphing library for Python

    plotly.py is a browser-based, open source graphing library for Python that lets you create beautiful, interactive, publication-quality graphs. Built on top of plotly.js, it is a high-level, declarative charting library that ships with more than 30 chart types. Everything from statistical charts and scientific charts, through to maps, 3D graphs and animations, plotly.py lets you create them all. Graphs made with plotly.py can be viewed in Jupyter notebooks, standalone HTML files, or hosted online using Chart Studio Cloud.
    Downloads: 3 This Week
    Last Update:
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  • 2

    Kanbanara

    Web-based Project Management System using the Kanban methodology

    ...Its Kanban board features projects, user-definable workflow with custom states, support for epic, feature, story, enhancement, defect, task, test, bug and transient cards, global and personal WIP limits, role-based columns (Owner, Reviewer or Quality Assurance), support for ghost cards (cards on their way to you or your own cards currently being reviewed or in QA), blockable cards, hidable cards, deferable cards, 46 card styles including a customisable one, 14-day future projection, Gantt Chart andcard backdrops. It also features a hierarchical workflow, global filter, backlog pyramid, force-directed graphs utilising d3.js, report generator, routine card manager, pair programming, support for continuing cards from one project to another. Full documentation in HTML and EPUB formats.
    Downloads: 0 This Week
    Last Update:
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  • 3
    PyG2Plot

    PyG2Plot

    Python3 binding Plotting 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. It also supports JavaScript callbacks through a JS helper, which makes advanced customization possible when chart behavior needs JavaScript logic. Overall, it is a useful visualization bridge for Python users who want AntV-style charts in scripts, notebooks, or web outputs.
    Downloads: 0 This Week
    Last Update:
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