28 个仓库
Modular libraries that provide components for rendering dynamic and interactive data visualizations.
Explore 28 awesome GitHub repositories matching data & databases · Data Visualization Libraries. Refine with filters or upvote what's useful.
D3 is a modular library providing low-level primitives for creating data-driven visualizations. It functions as a flexible framework that allows for direct control over visual presentation by mapping abstract data dimensions to graphical properties, such as position, color, and size, without imposing predefined chart abstractions. The library distinguishes itself by offering specialized tools for complex data representation, including algorithmic layouts for hierarchical structures and geographic projection utilities for mapping spherical coordinates. It also includes a comprehensive suite fo
Modular components like scales, axes, and shapes enable the construction of dynamic and interactive data visualizations.
Apache ECharts is a JavaScript data visualization library used for rendering interactive charts and complex data visualizations in web browsers. It functions as a canvas-based charting engine and a statistical data visualization suite that transforms datasets into visual representations. The framework provides specialized capabilities for three-dimensional data visualization, including the generation of 3D plots and globe visualizations. It also serves as a web-based geographic mapping tool for overlaying heatmaps, routes, and data distributions onto interactive maps. The library covers a br
Provides a comprehensive library for rendering interactive charts and complex data visualizations in web browsers.
ECharts is a JavaScript data visualization library and web charting framework used to render interactive 2D and 3D data plots within a web browser. It functions as a visualization engine that transforms raw data into customizable charts and graphs. The project includes a WebGL-based hardware acceleration engine specifically for producing three-dimensional plots and globe visualizations. This allows the library to handle large and complex datasets through GPU-accelerated rendering. The framework supports both canvas-based raster rendering and SVG-based vector rendering. It provides capabiliti
Functions as a modular library for rendering interactive charts and complex data visualizations in the browser.
Pygwalker is a library that transforms tabular data into interactive, drag-and-drop interfaces for exploratory analysis and visualization. It functions as a grammar-based framework that translates user interactions into declarative chart definitions, allowing for the creation of dynamic data exploration environments directly within notebooks or embedded web applications. The system distinguishes itself by offloading heavy analytical computations to backend kernels, which maintains responsiveness when visualizing large datasets. It supports the serialization of visual states into portable conf
Transforms tabular data into interactive drag-and-drop interfaces for exploratory analysis and visualization within notebook environments.
DearPyGui is a GPU-accelerated, immediate-mode graphical user interface framework for Python. It provides a high-performance toolkit for building interactive desktop applications by leveraging native hardware-accelerated rendering backends across multiple operating systems. By utilizing an immediate-mode execution model, the library offers direct control over the rendering loop and element state, enabling the creation of responsive, dynamic interfaces. The framework distinguishes itself through its ability to handle complex, high-frequency visual updates, making it suitable for real-time data
Displays structured data tables and manages grid-based positioning for data analysis.
ApexCharts is a comprehensive JavaScript charting library designed for building interactive, responsive, and data-driven visualizations within web applications. It functions as a versatile data visualization framework that supports a wide range of chart types, including categorical, statistical, and financial plots, enabling developers to construct complex dashboards and real-time monitoring interfaces. The library distinguishes itself through a deep commitment to accessibility and high-performance interactivity. It provides built-in support for keyboard navigation, screen readers, and high-c
Refreshes chart visuals automatically when underlying data series or configuration properties are modified.
This library provides a diagnostic toolkit for automated data profiling and exploratory analysis. It generates comprehensive statistical summaries and visual reports for tabular datasets, enabling users to identify distribution patterns, missing values, and quality anomalies through a unified interface. The project distinguishes itself by offering differential analysis, which allows for the comparison of two dataset versions to track structural and statistical changes over time. It supports large-scale data processing through lazy evaluation and provides interactive widgets that embed directl
Generates automated statistical reports and visual summaries for tabular data to identify quality issues.
This project is an exploratory data analysis framework and profiling tool designed to generate comprehensive statistical reports from Pandas and Spark DataFrames. It functions as a data quality profiler that identifies missing values, duplicates, and high correlations within tabular datasets. The tool distinguishes itself through specialized capabilities for time-series analysis, extracting temporal statistics, seasonality, and auto-correlation plots. It also includes a dataset comparison utility to identify structural or content changes between different versions of a dataset. The analysis
Generates detailed exploratory data analysis reports and descriptive statistics for Pandas and Spark DataFrames.
This project is an exploratory data analysis library and profiling tool for Pandas and Spark DataFrames. It automates the initial investigation of datasets by generating comprehensive descriptive analysis reports, statistical summaries, and data quality warnings. The system functions as a data quality profiler to detect missing values, duplicate rows, and type inconsistencies. It includes a dataset comparison tool for identifying structural and content shifts between different versions of the same data, as well as specialized tools for time-series analysis to calculate auto-correlation and se
Provides comprehensive statistical summaries and data quality assessments generated directly from Pandas and Spark dataframes.
Ydata-profiling is an automated exploratory data analysis framework designed to generate comprehensive statistical reports and visual summaries from dataframes. It functions as a diagnostic tool for assessing data quality, identifying missing values, duplicates, and outliers, while providing a scalable engine for profiling massive datasets across distributed enterprise environments. The project distinguishes itself through its ability to handle large-scale data through distributed task orchestration and lazy stream processing, which minimizes memory overhead during complex computations. It in
Generates comprehensive statistical reports and visual summaries directly from dataframes to identify patterns and quality issues.
Markmap is an interactive diagramming library that transforms hierarchical Markdown documents into navigable mindmaps. It functions as a data visualization component, converting structured text into graphical representations to assist in organizing and visualizing complex information. The library utilizes a parsing engine to interpret indentation levels and list markers, mapping them into nested data objects. These objects are rendered as scalable vector graphics, providing users with dynamic, zoomable, and collapsible diagrams that update reactively as the underlying source text changes. Th
Provides a library for converting structured text data into graphical representations.
Kepler.gl is a web-based geospatial visualization framework designed for rendering large-scale location datasets. It functions as a modular React mapping component that enables developers to embed interactive, high-performance geographic visualizations into web applications, serving as a comprehensive engine for building browser-based GIS dashboards. The library distinguishes itself through a highly extensible architecture that centers on centralized state management. By utilizing a predictable state-driven model, it allows for the programmatic control of map layers, filters, and viewport set
Overlays multiple data representations on a map to reveal complex patterns and relationships within geographic datasets.
gpui-component is a native desktop UI kit and component library built for the GPUI framework. It provides a collection of reusable user interface elements, a desktop layout engine for organizing application space, and a specialized data visualization library for rendering quantitative information. The project is distinguished by its high-performance rendering systems, including a virtualized data grid and list system designed to handle large datasets with low memory overhead. It also features a comprehensive data visualization toolkit for rendering charts, axes, and coordinate scales using li
Implements a modular toolkit for rendering high-performance charts and coordinate scales for quantitative data.
vue-echarts 是一个用于 Apache ECharts 库的声明式图表封装器和 Vue.js 组件。它作为一个数据可视化库,将配置和数据更新映射到渲染引擎,从而能够将交互式图形和图表作为可重用的 Web 组件进行嵌入。 该项目提供了一个通过主题配置和基于上下文的注入来管理视觉一致性的系统。它允许对可视化界面进行深度定制,包括使用作用域插槽(scoped slots)在工具提示中渲染自定义 HTML 标记,以及构建复杂的图形元素。 该库处理常见的可视化需求,如自动响应式调整大小、用户交互的事件绑定以及加载状态指示器的管理。为了保持性能,它采用了一种更新系统,计算部分配置更改以刷新图表,而无需执行完全重新初始化。
Offers a collection of modular components for rendering dynamic and interactive data visualizations.
PNChart is an iOS charting framework and data visualization library designed for rendering interactive visual data representations within native Apple mobile environments. It provides a toolkit for creating animated line and pie charts to illustrate data trends and proportional datasets. The library specializes in animated data representation, using motion effects and transitions to highlight information changes over time. It supports real-time chart data updates, allowing visualizations to reflect new information dynamically without rebuilding the entire user interface. The framework covers
A Swift library providing modular components for rendering dynamic, animated line and pie charts.
This project is a manifold learning and non-linear dimensionality reduction library used to project high-dimensional data into lower-dimensional spaces while preserving topological structure. It functions as a parametric embedding framework and a topological data visualization library for identifying clusters and patterns within complex datasets. The library distinguishes itself through parametric neural mapping, which uses neural networks to learn functional mappings that allow for out-of-sample projections and the reconstruction of original data. It supports supervised and semi-supervised d
Provides a toolkit for rendering topological data visualizations, including scatterplots and graph connectivity views.
This project is an SVG data visualization library and charting engine designed to render quantitative metrics and time-series data within a web browser. It provides a framework for creating concise visual representations of numerical data sets, such as line charts, scatterplots, and histograms. The library utilizes a component-based layout framework to organize visual elements into hierarchical structures with automated spacing and positioning. It includes a coordinate-space mapping tool that translates raw data values into pixel coordinates using linear scales and axis transformations. The
Provides a modular library for rendering time-series charts and quantitative data layouts within web documents.
metrics-graphics is a data visualization library and declarative graphics framework designed to create principled data graphics and layouts. It functions as a statistical graphics engine that maps raw data to geometric shapes and structured objects to render complex, data-driven layouts. The toolkit specializes in rendering time-series data through line charts and scatterplots using a consistent layout system. It also provides capabilities for statistical distribution mapping, including the creation of rug plots to represent one-dimensional data density. The system covers a broad surface of
Provides a library for creating principled data graphics and layouts optimized for concise representations of complex datasets.
react-chartjs-2 is a data visualization library that provides a set of React components to integrate the Chart.js library. It serves as a component-based charting interface for rendering dynamic data visualizations and graphs based on structured data sets. The project provides a declarative way to manage chart configurations and data updates. It maps component props to the underlying charting engine, allowing users to modify visual options and data dynamically to refresh displays. The library covers broader data visualization development, including the implementation of dynamic dashboards an
Provides a comprehensive collection of tools for generating interactive charts and graphs from structured data.
本项目是一个机器学习教育课程和学习平台,通过交互式 Jupyter Notebooks 提供。它作为掌握 Python 数据科学工具包的综合指南,为数值计算、表格数据操作和统计可视化提供结构化教程。 该课程包括 Scikit-Learn 的具体实现指南,以及关于构建、训练和部署神经网络及计算机视觉模型的 TensorFlow 实践课程。它涵盖了构建预测模型的端到端过程,从初始问题定义和任务分类,到通过交互式 Web 界面部署模型。 该项目涵盖了广泛的功能领域,包括多维数组的数值计算、探索性数据分析和数据预处理例程。它为监督和无监督学习、自动化机器学习流水线、超参数优化以及使用分类指标和交叉验证的模型评估提供了详细的工作流。 教育内容组织为一系列 Notebook,将 Python 代码与叙述性解释交织在一起,以记录数据科学工作流。
Integrates directly with tabular dataframes to generate visual exploration interfaces.