3 个仓库
Awesome GitHub RepositoriesInteractive Data Exploration
Exploring datasets using interactive code cells that render results as rich media for analysis.
Distinct from Visual Data Explorers: Focuses on the interactive cell-based exploration process rather than specialized big data visual explorers.
Explore 3 awesome GitHub repositories matching data & databases · Interactive Data Exploration. Refine with filters or upvote what's useful.
Awesome Interactive Data Exploration GitHub Repositories
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- gopherdata/gophernotes
gopherdata/gophernotes
3,965在 GitHub 上查看Gophernotes 是 Jupyter 内核协议的后端实现，也是一个交互式运行时，支持在 Notebook 环境中执行 Go 语言代码。它作为 Go 语言执行引擎，允许用户将 Go 集成到 Jupyter 和 nteract 等多语言 Notebook 中。 该项目支持创建结合可执行源代码和富媒体的文档。它将内部数据类型映射为包括 HTML、JSON、LaTeX、PDF 和图像在内的多种格式，以提供执行结果的视觉表示。 该系统涵盖了一系列功能，包括执行系统 Shell 命令、管理 Notebook 执行上下文，以及跨不同操作系统链接第三方包。
Allows processing data in notebook cells and rendering results as HTML or JSON for easier analysis.
Goartificial-intelligencedata-sciencego - yhat/rodeo
yhat/rodeo
3,893在 GitHub 上查看Rodeo is an interactive Python notebook environment and integrated development environment designed for data science. It provides a workspace for combining executable code, rich text, and data visualizations within a single document to manage the lifecycle of research scripts. The platform facilitates data science workflow management, covering the process from initial data exploration to final model execution. It supports the development of Python scripting environments tailored for data analysis, modeling, and iterative hypothesis testing. The system utilizes a cell-based document structure
Enables iterative data analysis and hypothesis testing through interactive code cells and result visualization.
JavaScript - bloomberg/bqplot
bloomberg/bqplot
3,693在 GitHub 上查看bqplot is an interactive data visualization library for Jupyter notebooks. It implements a grammar of graphics model, allowing users to build complex 2D charts by combining marks, scales, and axes. The library distinguishes itself with specialized toolkits for financial charting, such as OHLC candlesticks and time-series analysis, and geographic data visualization, including choropleths and custom map projections for TopoJSON and GeoJSON data. It enables deep interaction through tools like lasso selection, rectangular brushing, and the ability to manually manipulate plot points or line data.
Enables interactive exploration of datasets using code cells that render rich, manipulatable visualizations.
TypeScript
