Awesome GitHub RepositoriesDeclarative Data Visualization

AAChartKit is a declarative charting library and data visualization framework for iOS, iPadOS, and macOS. It functions as a multi-type statistical charting engine that renders a variety of plot types, including line, bar, bubble, box plot, and polar charts. The framework utilizes a Core Graphics vector rendering engine to draw visual elements with precise pixel control. It provides a system for interactive data visualization featuring built-in support for animations, zooming, panning, and user interaction events. The library covers broad capabilities for statistical data plotting and custom

ggpy is a Python library for statistical data visualization based on the grammar of graphics. It functions as a declarative framework for building complex charts by mapping data variables to visual properties through a structured coordinate system. The library enables the construction of composite visualizations by layering geometric shapes and statistical summaries. It utilizes a system of continuous and discrete scales to translate raw data into visual attributes and supports facet-based plotting to segment a single visualization into a grid of subplots based on variable categories. Visual

This project provides a collection of pre-built administrative dashboard templates and a comprehensive user interface kit designed for constructing professional management applications. It is built upon the Bootstrap framework, offering a set of responsive themes and layout blocks that adapt to various screen sizes. The framework distinguishes itself by providing modular, reusable building blocks that allow developers to assemble complex administrative interfaces. It includes specialized components for data grid management, enabling the organization, sorting, and filtering of large datasets,