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ggplot2 is a data visualization library for R based on a formal grammar of graphics. It provides a declarative plotting framework that allows users to create complex graphics by combining geometric objects, statistical summaries, and coordinate systems. The system is distinguished by a layered approach to composition, where visualizations are built incrementally by stacking independent geometric, statistical, and coordinate layers. It utilizes a hierarchical styling engine to manage non-data elements such as backgrounds, fonts, and margins, and includes a multi-panel faceting tool for splitti

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

This is an interactive notebook-based course that teaches machine learning from Python fundamentals through deep learning and natural language processing. It uses real datasets and multiple frameworks within a structured, hands-on curriculum that combines concise explanations with executable code cells, built-in datasets, and embedded exercise checkpoints. Learning progresses through data preparation and exploration, classical machine learning workflows, computer vision with convolutional neural networks, and natural language processing with deep learning, all delivered as a cohesive progressi

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.

Plotnine is a data visualization library for Python based on the Grammar of Graphics. It serves as a declarative statistical plotting framework and multi-panel plotting engine, allowing users to create complex charts by mapping data variables to visual properties such as position, color, and size. The project is distinguished by its use of a layered composition model and a statistical transformation engine that performs aggregations and computations before rendering visuals. It features a comprehensive system for multi-panel faceting, which enables the splitting of a single visualization into

PyQtGraph is a scientific plotting and graphics framework built for PyQt and PySide applications, providing fast, interactive 2D and 3D visualizations with GPU-accelerated rendering. It serves as both a real-time signal monitoring system for streaming time-series data and a toolkit for constructing interactive data dashboards with dockable panels, parameter trees, and custom widgets. The library also includes a node-based visual flowchart tool for building data processing pipelines and a scientific graphics export system that saves plots as PNG, SVG, or CSV and converts items to Matplotlib for

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