20 مستودعات
Tools for rendering additional data fields alongside price information on charts.
Distinct from Data Visualization: Focuses on custom indicator line rendering, distinct from general data visualization.
Explore 20 awesome GitHub repositories matching data & databases · Custom Data Line Visualization. Refine with filters or upvote what's useful.
This project is a collection of interactive Python notebooks and educational resources designed for mastering data science, machine learning, and numerical computing. It provides a series of practical guides and tutorials covering deep learning, big data processing, and statistical analysis. The repository features specialized instructional suites for implementing classical machine learning algorithms, building deep learning model architectures, and managing AWS cloud infrastructure. It includes dedicated notebooks for data visualization and numerical computing exercises. The project covers
Demonstrates how to add labels, legends, and colorbars to charts for improved clarity.
Backtrader is a Python framework designed for the development, backtesting, and live execution of algorithmic trading strategies. It provides a comprehensive environment for quantitative finance, allowing users to simulate trading logic against historical market data or connect directly to brokerage platforms for automated real-time trading. The project distinguishes itself through a unified event-driven architecture that treats backtesting and live trading with the same API. This consistency is supported by a flexible data-feed abstraction layer that normalizes diverse financial sources, ena
Renders additional data fields alongside standard price information by attaching indicators to custom lines for plotting.
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
Allows placing markers and descriptive labels at precise coordinates to highlight data trends.
This project is a client-side data visualization framework and SVG charting library used to render responsive, interactive charts in a web browser. It functions as a lightweight utility for generating scalable vector graphics and data annotations without external dependencies. The library enables the creation of custom SVG charts with adjustable colors and animations to meet specific design requirements. It supports dynamic data updates and the addition of markers, regions, and tooltips to provide context to specific data points. The system covers broad capability areas including responsive
Supports adding markers, regions, and tooltips to specific data points for additional context and clarity.
ApexCharts is a comprehensive JavaScript charting library designed for building interactive, responsive, and data-driven visualizations within web applications. It functions as a versatile data visualization framework that supports a wide range of chart types, including categorical, statistical, and financial plots, enabling developers to construct complex dashboards and real-time monitoring interfaces. The library distinguishes itself through a deep commitment to accessibility and high-performance interactivity. It provides built-in support for keyboard navigation, screen readers, and high-c
Adds custom labels, lines, and shapes to specific chart areas to highlight trends and significant values.
PlantUML is a text-to-diagram generator that translates human-readable markup into structured graphical representations. It functions as a diagram-as-code tool, allowing users to create and maintain technical documentation, architectural models, and flowcharts by decoupling diagram content from visual layout. The project distinguishes itself through a comprehensive rendering pipeline that processes domain-specific markup into various output formats, including vector and raster graphics. It utilizes a graph-based layout engine to calculate spatial positioning, while a declarative styling layer
Adds text labels and pointers to specific chart coordinates to highlight key data points.
fl_chart is a data visualization library and UI component framework for Flutter. It provides a system of reusable graphical widgets for creating interactive, customizable quantitative data visualizations. The framework supports a variety of chart types, including line, bar, pie, donut, scatter, radar, and candlestick views. It allows for the creation of complex visualizations such as layered data segments and financial charts. The library includes capabilities for interactivity and visual refinement, such as touch event handling, data tooltips, and state animations. It also provides tools fo
Allows adding horizontal and vertical lines or range markers to highlight specific values within charts.
This project is a Python data science curriculum and programming tutorial collection. It provides a structured set of educational notebooks and scripts designed to teach data analysis, machine learning, and deep learning. The repository serves as a learning path for building and tuning predictive models, including regression, decision trees, and neural networks. It includes a data visualization guide for creating financial time-series plots and a multiprocessing reference for implementing parallel task execution and shared memory synchronization. The curriculum covers broader capability area
Includes instructions for adding labels and grid lines to enhance the readability of data charts.
charts.css is a CSS-driven framework designed to transform semantic HTML into accessible data visualizations without relying on JavaScript. It functions as a charting library that uses standard HTML structures, such as tables and lists, to render graphs while maintaining full compatibility with screen readers. The project distinguishes itself by using CSS variables to map numeric data to visual dimensions and utility classes to control chart types and layouts. It supports a wide range of visual styles, including 3D effects, reflection effects, and customized color palettes integrated via a br
Adds headings and labels to specific data points using semantic markers to provide visual context.
Rickshaw is a JavaScript library for building interactive, SVG-based time series charts in the browser. It provides a framework for rendering line, area, bar, and scatterplot visualizations from data series, with built-in support for axes, legends, color palettes, and interactive controls. The library distinguishes itself through a plugin-based architecture that allows renderers to be swapped at runtime, such as switching between stacked area and line chart views while preserving chart state. It includes an event-driven interaction layer for hover details, click behaviors, and drag-based rang
Adds toggleable text annotations at specific timestamps on the graph timeline.
billboard.js is a JavaScript charting library built on D3.js that renders interactive data visualizations from a single declarative configuration object. It supports a wide range of chart types including bar, line, pie, scatter, area, spline, step, candlestick, funnel, gauge, heatmap, radar, polar, treemap, bubble, donut, and sparkline charts, and can overlay multiple chart types within a single visualization. The library offers an opt-in Canvas rendering mode for improved performance with large datasets and high-density axis displays, alongside its standard SVG-based rendering. The library d
Displays a configurable text title above the chart for context and labeling.
Provides reference lines and shaded regions to highlight thresholds and ranges on charts.
ScrollableGraphView هي مكتبة تصور بيانات Swift وإطار عمل رسم بياني لنظام iOS تُستخدم لعرض مجموعات البيانات الرقمية المنفصلة كرسوم بيانية تفاعلية. توفر مكون واجهة مستخدم قابل للتمرير يقوم بتصور نقاط البيانات باستخدام نظام إحداثيات مع تخطيطات وأنماط قابلة للتكوين. يتميز إطار العمل بتوسيع الرسم البياني التكيفي، الذي يضبط المحور الرأسي تلقائيًا ليتناسب مع نقاط البيانات المرئية أثناء تمرير المستخدم. ويدعم عرض البيانات في الوقت الفعلي، مما يسمح لطرق عرض الرسم البياني بالتحديث فورًا مع تغير مجموعات البيانات الأساسية من خلال انتقالات متحركة. تغطي المكتبة مجموعة متنوعة من أنواع المخططات، بما في ذلك المخططات الخطية، والشريطية، والنقطية، وتدعم رسم مجموعات بيانات متعددة لعرض سلاسل بيانات متعددة على رسم بياني واحد. تشمل الإمكانيات الإضافية تسمية نقاط بيانات المحور السيني، وتصميم المخططات المخصص، واستخدام علامات الخط المرجعي لتسليط الضوء على عتبات أو قيم أساسية محددة.
Draws static horizontal or vertical markers to highlight thresholds or baseline values on the graph.
Vega-Lite is a high-level declarative language for specifying interactive, multi-view visualizations. It compiles a concise JSON specification into a full Vega visualization, automatically inferring scales, axes, and legends from encoding declarations. The grammar-of-graphics encoding maps data fields to visual channels such as position, color, size, and shape, while a multi-view composition grammar enables layered, faceted, concatenated, and repeated layouts. Reactive parameter binding links named parameters to input widgets, selections, and expressions for dynamic updates. The project suppo
Draws horizontal or vertical lines spanning the full view for annotations such as average values.
This C++ data visualization library is a scientific plotting framework used to create 2D and 3D charts, network graphs, and geographic maps. It operates as a multi-backend graphics library, decoupling high-level plotting logic from low-level rendering engines to support various output backends. The project distinguishes itself with a dual-interface API, providing both a global functional interface for rapid prototyping and an object-oriented interface for precise control. It features a component-based layout engine for managing tiled grids and subplots, alongside a layered plot state that all
Draws horizontal, vertical, or sloped reference lines to mark milestones or targets on a chart.
mplfinance هو إطار عمل لرسم السلاسل الزمنية المالية وتصور بيانات السوق مبني على Matplotlib. صُمم لعرض إطارات بيانات السوق في مخططات متخصصة، بما في ذلك الشموع اليابانية، وأشرطة OHLC، ومكعبات Renko، وأعمدة النقطة والشكل. تتميز المكتبة بإطار عمل مخصص لبيانات السوق يدير تقويمات التداول وفترات عدم التداول، مما يضمن تباعداً زمنياً دقيقاً عن طريق طي الفجوات خلال العطلات. كما توفر نظاماً لرسم مخططات التحليل الفني، مما يتيح تراكب المتوسطات المتحركة، وأشرطة الحجم، والمؤشرات الفنية الأخرى على مخططات حركة السعر. تغطي مجموعة الأدوات نطاقاً واسعاً من القدرات، بما في ذلك تنظيم المخططات الفرعية المكدسة عمودياً مع محاور مشتركة وتطبيق سمات مرئية متسقة. وهي تدعم تعليقات السوق مثل خطوط الاتجاه، والتعامل مع البيانات المفقودة، والقدرة على تحديث المخططات لتغذية البيانات في الوقت الفعلي. يمكن تصدير التصورات إلى تنسيقات مختلفة بما في ذلك PDF و SVG و PNG و JPG.
Adds horizontal, vertical, and trend lines to highlight specific market signals or boundaries.
Vizro is a low-code Python framework for building production-ready data visualization applications. It functions as a UI orchestrator that allows users to define multi-page analytical dashboards through structured configurations in Python, YAML, or JSON, reducing the need for extensive frontend engineering. The project distinguishes itself through generative AI integration, utilizing a model context protocol server to translate natural language descriptions into validated dashboard configurations, charts, and layouts. It also features a decoupled data cataloging system that separates data sou
Adds structured context to charts through customizable titles, Markdown headers, and tooltips.
Unovis is a modular SVG and Canvas data visualization library used to build interactive charts, maps, and network graphs. It provides a framework-agnostic set of primitives for creating data dashboards and specialized visualizations. The library is distinguished by its dedicated toolkits for different visualization domains, including an XY charting library for coordinated plots, a network graph framework for relational data, and a geospatial visualization toolkit for TopoJSON-based mapping. Its capability surface covers a wide range of data representations, including linear, area, and bar ch
Provides custom labels, lines, and shapes such as axes and legends to highlight chart areas.
ChartGPU is a high-performance visualization library designed to render large-scale datasets and real-time data streams using hardware acceleration. It functions as a component-based tool that integrates into declarative user interfaces, allowing developers to build responsive, themeable charts that maintain smooth interaction even when processing massive amounts of information. The library distinguishes itself through a specialized rendering engine that employs screen-space binning and zoom-aware data resampling to manage dense datasets. It provides advanced interactive capabilities, includi
Provides tools to draw custom lines, points, and text labels over specific plot areas using coordinate mapping.
هذا المشروع عبارة عن غلاف (wrapper) بلغة Python لمكتبة Lightweight Charts، صُمم لعرض تصورات مالية تفاعلية تعتمد على المتصفح. يعمل المشروع كإطار عمل لبناء لوحات تحكم وواجهات مالية مخصصة تدمج خلاصات السوق المباشرة وسلاسل البيانات التاريخية. تتيح المكتبة بناء تخطيطات معقدة من خلال دمج مخططات متعددة الأجزاء، وقوائم مراقبة، وجداول إدخال أوامر في مساحة عمل واحدة موحدة. كما تدعم مراقبة السوق في الوقت الفعلي عبر بث بيانات التيك (tick) أو الأعمدة (bar) مباشرة إلى المخططات النشطة، مما يسمح بتحديثات تدريجية دون الحاجة إلى إعادة تحميل الصفحة بالكامل. بالإضافة إلى العرض الأساسي، توفر الأداة إمكانات واسعة للتحليل الفني، بما في ذلك القدرة على رسم التعليقات التوضيحية، وخطوط الاتجاه، والعلامات مباشرة على لوحة الرسم. يمكن للمستخدمين تهيئة المظهر المرئي للشموع، وأعمدة الحجم، ووسائل الإيضاح، مع ربط تفاعلات المستخدم مثل اختيار الإطار الزمني أو اختصارات لوحة المفاتيح بمنطق Python مخصص.
Allows drawing annotations, trendlines, and markers directly onto charts for technical analysis.