Awesome GitHub RepositoriesCustom Plotting Integrations

Charts is a data visualization framework and charting library for iOS, tvOS, and macOS. It provides a set of graphical components used to render interactive line, bar, pie, and scatter charts to represent complex data sets. The project serves as an implementation of a charting library adapted specifically for the Apple ecosystem. It includes a rendering engine capable of plotting data points directly from database records. The framework covers a broad range of visualization capabilities, including interactive data exploration via zooming and panning gestures, visual style customization for c

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

Seaborn is a Python library designed for statistical data visualization. It functions as a high-level interface built on the Matplotlib ecosystem, providing specialized routines to explore and communicate complex patterns within datasets. The framework enables users to generate informative graphics through automated statistical aggregation, multi-plot faceting, and integrated regression modeling. The library distinguishes itself through a declarative approach to data mapping, which translates raw inputs into visual properties like color, size, and position. It includes a robust statistical tr

uPlot is a high-performance canvas time series charting library designed to render millions of data points with high frame rates. It functions as a high-frequency data visualizer and a real-time data stream plotter, utilizing the HTML5 Canvas API to maintain responsiveness when plotting large temporal datasets. The project distinguishes itself as a plugin-based visualization framework that allows for custom renderers to create specialized visuals such as heatmaps and box-and-whisker plots. It also serves as an interactive financial charting tool, specifically supporting OHLC charts, bars, and

ScottPlot is a cross-platform, high-performance charting library for .NET that renders interactive plots across desktop and web GUI frameworks including Windows Forms, WPF, MAUI, Avalonia, Blazor, and WinUI. It provides an optimized rendering engine capable of displaying millions of data points with interactive pan, zoom, and live data streaming, while also supporting image export to formats like PNG and SVG for file output, cloud applications, and notebooks. The library distinguishes itself through a comprehensive set of chart types including scatter, line, bar, pie, heatmap, financial, rada

sc-im est un tableur et gestionnaire de données en interface utilisateur texte. Il fournit un environnement piloté par clavier pour effectuer des calculs mathématiques et gérer des grilles de données au sein d'une interface en ligne de commande. L'application est scriptable, prenant en charge des fonctions personnalisées, des déclencheurs pilotés par événements et l'intégration de scripts externes pour automatiser les tâches de calcul. Elle permet en outre le chargement de modules compilés externes à l'exécution pour étendre ses capacités mathématiques. Le système couvre la gestion des données via le tri des lignes, le filtrage et les calculs de sous-totaux. Il prend en charge l'interopérabilité des données via l'importation et l'exportation des formats CSV, TAB, Markdown et XLSX. Les capacités supplémentaires incluent un mode d'exécution non interactif pour le traitement de données headless et la capacité d'envoyer des données vers un logiciel de traçage externe pour la visualisation.

Cette bibliothèque de visualisation de données C++ est un framework de traçage scientifique utilisé pour créer des graphiques 2D et 3D, des graphes de réseau et des cartes géographiques. Elle fonctionne comme une bibliothèque graphique multi-backend, découplant la logique de traçage de haut niveau des moteurs de rendu de bas niveau pour prendre en charge divers backends de sortie. Le projet se distingue par une API à double interface, fournissant à la fois une interface fonctionnelle globale pour le prototypage rapide et une interface orientée objet pour un contrôle précis. Il dispose d'un moteur de mise en page basé sur des composants pour gérer les grilles tuilées et les sous-graphiques, ainsi qu'un état de tracé en couches qui permet de superposer plusieurs séries de données sans effacer les axes. La bibliothèque couvre un large éventail de capacités de visualisation, incluant le traçage de fonctions mathématiques, les champs vectoriels et l'analyse de données multidimensionnelles via des cartes thermiques et des coordonnées parallèles. Elle inclut des outils spécialisés pour la visualisation de données géographiques, tels que les graphiques geobubble et geodensity, ainsi que des outils pour le rendu de réseaux de graphes dirigés et non dirigés. Les capacités générales incluent la gestion des axes, le stylisme esthétique avec des colormaps et l'exportation de graphiques de haute qualité. Le projet utilise CMake pour l'automatisation de la construction et la récupération des dépendances afin de faciliter l'installation sur différents systèmes d'exploitation.

This project is a collection of implementation patterns and source code examples for building desktop applications using various Python interface libraries. It provides reference implementations and architectural patterns for multiple frameworks, including PyQt, PySide, Tkinter, Kivy, and Streamlit. The repository distinguishes itself by offering specialized examples for diverse interface types, ranging from professional desktop software and native windows to reactive web-based data dashboards and data science tools. It includes specific reference material for cross-platform UI patterns, such

This project is a mathematical visualization library and a collection of algorithmic art. It serves as a data visualization guide and an interactive visualizer, providing a set of implementations for rendering complex geometric shapes and mathematical concepts through code. The collection focuses on generating aesthetic patterns and precise graphic elements, including fractals, Bezier curves, and Lissajous patterns. It uses recursive functions and iterative algorithms to produce complex geometric structures and algorithmic art. The library covers a range of capabilities including interactive

Makie.jl is a high-performance Julia data visualization library and hardware-accelerated plotting engine used to create interactive 2D and 3D visualizations. It functions as a reactive visualization framework where plots update automatically via observables and compute graphs, and as a vector graphics generator for high-resolution academic output. The system is distinguished by its backend-agnostic rendering pipeline, which supports OpenGL, WebGL, and ray-traced scenes. It employs a grammar-of-graphics approach to map variables to aesthetic attributes and utilizes a hierarchical scene graph t

Patchwork is a layout manager for combining multiple ggplot2 graphics into a single complex arrangement. It functions as a multi-plot composition tool and data visualization orchestrator, allowing independent graphics to be arranged into grids and nested layouts using additive and functional syntax. The system differentiates itself through a broadcast-based style application that propagates themes and scales across all subplots to maintain visual consistency. It also features guide-merging reconciliation to identify and collapse redundant legends into a single shared global guide. The framew