Showing 2 open source projects for "python library"

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  • Intelligent Retail Management Icon
    Intelligent Retail Management

    Retail space, product categories, planograms, automatic ordering, and shelf labels management

    Quant offers a wide range of solutions for retail. Within one integrated software system, it allows you to efficiently combine the management of retail space, shelf labels and marketing materials with task management, reporting and automatic replenishment.
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  • One Unified Time Tracking Software For Projects, Billing, Pay and Compliance Icon
    One Unified Time Tracking Software For Projects, Billing, Pay and Compliance

    For companies of all sizes looking for a Time Tracking software

    Replicon's time-tracking platform is scalable and configurable to support the diverse needs of small, mid & large businesses with a remote and globally distributed workforce. Replicon’s Time Tracking is a cloud-based, enterprise-grade solution that tracks employee time across projects, tasks, presence, and absence to facilitate client billing, project costing, and compliant payroll processing. The scalable and configurable platform offers seamless integration with common business technology stacks, such as ERP, CRM, Accounting, and payroll solutions. With AI-powered time capture, mobile apps, and labor compliance as a service, Replicon makes time tracking hassle-free.
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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.
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    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...
    Downloads: 0 This Week
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