Awesome GitHub RepositoriesPython Visualization

Matplotlib is a Python data visualization library and 2D plotting engine used to generate publication-quality figures and charts from numerical data. It serves as a numerical graphics library and data visualization toolkit for mapping data to visual elements. The library provides capabilities for producing static, animated, and interactive visualizations. This includes creating high-resolution figures for professional documents, generating moving graphics to illustrate data evolution over time, and building dynamic plots for interactive data exploration. The toolkit supports scientific plott

Bokeh is a Python data visualization library and interactive plotting framework used to create high-performance graphics and data dashboards that render in web browsers. It serves as a tool for generating standalone HTML documents, embedded components for digital notebooks, and full-stack web applications powered by a Python backend. The project distinguishes itself through its ability to handle large or streaming datasets while maintaining smooth interactivity. It enables linked brushing across multiple views, allowing data selected in one plot to automatically highlight corresponding data i

pyecharts is a Python visualization library and wrapper for the Echarts JavaScript engine. It translates Python data and configurations into JSON specifications to generate interactive web-based charts and graphs. The library provides specialized capabilities for geographic data mapping using a comprehensive library of map assets to visualize spatial information. It also includes utilities to capture rasterized snapshots of rendered web visualizations for export as static image files. The tool supports rendering interactive plots directly within data science notebook environments and exporti

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

Altair is a declarative data visualization library for Python based on the Vega-Lite grammar. It allows users to create statistical visualizations by mapping data fields to visual properties rather than writing imperative drawing code. The library focuses on interactive charting through a system of linked selections and filters that update multiple visualizations based on user input. It renders charts as JSON and HTML for display in web browsers and interactive notebooks. The project covers statistical data analysis and interactive data exploration, providing capabilities to export visuals a

Altair is a declarative data visualization library for Python that generates Vega-Lite specifications. It functions as a tool for mapping data to graphical marks using a high-level syntax, allowing users to describe the desired visual outcome instead of writing imperative drawing commands. The framework enables the creation of interactive charts and graphics, including linked views and filtered displays that respond to user input in real time. It supports the design of multi-view dashboards by combining visualizations into layered or faceted layouts. The library provides capabilities for sta

LearnPython is a programming tutorial consisting of a collection of practical code examples used to demonstrate Python language features and programming patterns. It serves as a comprehensive learning resource that implements core language concepts through functional code. The project provides specialized guides and samples covering several key domains. These include asynchronous network programming with event loops and coroutines, data visualization using numerical datasets for 2D and 3D plots, and web scraping for fetching content and automating login flows. It also features instructions on

This project is a comprehensive library of practical Python code examples and patterns. It provides a collection of scripts and snippets designed to demonstrate a wide range of programming tasks, from basic syntax to advanced implementation patterns. The repository focuses on several core domains, including the implementation of concurrency and multithreading examples, data analysis snippets for cleaning and manipulating tabular data, and various data visualization examples. It also covers automation scripts for file system management and a variety of general programming patterns. Additional

Smile is a comprehensive JVM machine learning library and statistical computing toolkit. It provides a suite of algorithms for classification, regression, and clustering, implemented natively for Java, Scala, and Kotlin. The project also functions as a deep learning framework, a natural language processing library, and an inference engine for large language models. The library distinguishes itself through GPU acceleration via LibTorch bindings and support for the ONNX model interchange format. It includes specialized capabilities for large language model inference, featuring Byte-Pair Encodin

Livebook is an interactive notebook platform for Elixir that provides a web-based environment for writing and running code cells alongside Markdown content, visualizations, and reproducible workflows. It serves as a multi-cloud auto-clustering tool that automatically discovers and joins Elixir nodes into clusters across Kubernetes, AWS ECS, and Fly.io for distributed execution, and also functions as a notebook deployment tool that packages notebooks into standalone web applications with authentication, secrets, and Docker support. The platform enables real-time collaborative editing, synchron

Lux 是一款自动化探索性数据分析工具，旨在为 pandas 数据帧生成智能视觉表示。它通过根据数据集的统计属性推荐最佳图表类型和轴映射来识别模式和趋势。 该工具作为一个交互式数据分析层，允许用户使用过滤器和通配符浏览和查询图表集合。它还充当可视化代码生成器，将自动生成的图表转换为程序代码或 HTML，以便在外部库中进行手动优化。 该系统涵盖了广泛的探索性分析功能，包括自动图表编码、通过步骤推荐进行引导式发现，以及将视觉配置导出为声明式规范的能力。 该项目直接集成到 pandas 中，通过交互式可视化组件覆盖默认的数据帧打印方式。

Polynote 是一个多语言笔记本环境和交互式文档系统，旨在在单个文档中执行多种语言的代码。它作为一个跨语言数据分析工具和 JVM 语言 IDE，允许用户结合可执行代码、富文本和数据可视化来原型化和记录技术工作流。 该系统的特点在于能够在不同的语言运行时（如 Python 和 JVM）之间共享数据和变量。它使用跨语言对象转换和数据包装来在运行时之间传递对象，从而实现多语言数据工作流。此外，它与 Apache Spark 集成，通过本地或远程集群提交来执行分布式数据处理任务。 该平台提供了一套全面的数据分析和可视化功能，包括用于运行时监控的实时符号表，以及对 Vega 规范渲染的支持。它使用基于坐标的解析来管理 JVM 和 Python 运行时的依赖关系，并提供具有自动补全和错误高亮功能的 IDE 增强编辑体验。 文档管理功能包括动态目录、跨笔记本内容搜索以及基于浏览器的备份恢复，以防止文件损坏导致的数据丢失。

missingno 是一个用于缺失数据模式可视化和分析的 Python 库。它提供了一套工具来分析数据集的完整性、映射数据缺口并量化变量中空值的数量。 该库通过空值相关性分析器和分层数据聚类工具脱颖而出。这些组件允许通过测量一个变量的缺失如何与另一个变量的缺失相关联，来检测系统性依赖和趋势。 该工具集涵盖了更广泛的数据质量审计和探索性分析功能。它包括使用线性和对数刻度进行列空值汇总的功能，以及用于识别记录中系统性缺口的基于矩阵的映射。

PyVista is a scientific 3D plotting framework and visualization library that provides a Python interface for rendering and analyzing spatial datasets using a VTK backend. It functions as a volumetric rendering engine and a 3D mesh analysis tool for computing geometric properties and performing boolean operations on surface and volumetric meshes. The project is distinguished by its ability to operate as a headless 3D renderer, generating high-quality renders and animations on remote servers without a physical display. It also features a lazy-accessor extension mechanism that allows the registr

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

Python library that makes it easy for data scientists to create charts.

Python+Numpy+OpenGL: fast, scalable and beautiful scientific visualization

The Point Processing Toolkit (pptk) is a Python package for visualizing and processing 2-d/3-d point clouds.

Text mode diagrams using UTF-8 characters and fancy colors

The power of Chart.js with Python