16 مستودعات
Libraries for creating charts, plots, and interactive data visualizations.
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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
Interactive visualization library for modern web browsers.
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
Declarative statistical visualization library.
Penrose is a compiler that transforms structured mathematical notation into optimized SVG diagrams. It uses a three-stage pipeline of separate domain, substance, and style files to define mathematical objects, relationships, and visual presentation, then solves continuous optimization problems with user-defined spatial constraints and objectives to automatically arrange diagram elements. The system separates diagram content from visual style using distinct declarative languages, and provides a typed domain language with subtype hierarchies for mathematical objects. It supports embedding compi
Declarative diagramming and Venn visualization.
SandDance is a hardware-accelerated visualization library and web-based data explorer designed for the interactive analysis of large, non-aggregated datasets. It functions as an interactive data visualization tool that renders complex datasets and intricate visuals within a browser. The project provides an embeddable data canvas consisting of web components and tags, allowing for the integration of full visualization interfaces and interactive charts into external web applications. It utilizes WebGL hardware acceleration to efficiently render large volumes of data as interactive graphics. Th
Interactive visual data exploration tool.
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
Grammar of graphics implementation for Python.
Yellowbrick هي مكتبة لتصور تعلم الآلة وأداة تشخيص للنماذج مصممة لتحليل أهمية الميزات، وتوزيعات الأهداف، ومقاييس خطأ النموذج. تعمل كمجموعة أدوات مرئية لتشخيص نقص الملاءمة (underfitting) والإفراط في الملاءمة (overfitting) من خلال استخدام منحنيات التحقق والتعلم. يوفر المشروع مجموعات متخصصة لتقييم النماذج التنبؤية والتعلم غير الخاضع للإشراف. يتيح تحديد أعداد العناقيد المثلى عبر طرق الكوع (elbow methods) ومعاملات الصورة الظلية (silhouette coefficients)، وتقييم جودة المصنفات والمنحدرات من خلال منحنيات ROC، ومصفوفات الارتباك، ومخططات البواقي. تغطي المكتبة العديد من مجالات الإمكانيات عالية المستوى، بما في ذلك تحليل هندسة الميزات لتحديد المتغيرات التنبؤية، وضبط المعلمات الفائقة (hyperparameters) لتعديل تعقيد النموذج، وتشخيص خطأ الانحدار لتحديد نقاط البيانات المؤثرة. كما تتضمن أدوات لإسقاط تعلم المتشعبات (manifold learning) لتصور البيانات عالية الأبعاد ومتون النصوص. تتكامل الأداة مع واجهة برمجة تطبيقات Scikit-Learn لاستهلاك طرق الملاءمة والتنبؤ القياسية.
Visual diagnostic tools for machine learning models.
A python library for decision tree visualization and model interpretation.
Visualization and interpretation of decision trees.
Multiplatform plotting library based on the Grammar of Graphics
Multi-platform plotting library for statistical data.
Next-gen fast plotting library running on WGPU using the pygfx rendering engine
High-performance plotting using the pygfx engine.
Python histogram library - histograms as updateable, fully semantic objects with visualization tools. Python HYSTograms.
Enhanced histogram plotting for data analysis.