16 Repos
Low-level components for defining the mathematical and structural rules of a chart, distinct from the visual rendering logic itself.
Explore 16 awesome GitHub repositories matching user interface & experience · Visualization Configuration Utilities. Refine with filters or upvote what's useful.
shadcn/ui offers a collection of React UI components and a CLI-driven registry system for direct source code integration.
Applies design tokens, labels, and icons to govern the visual appearance and thematic consistency of graphical data elements.
Chart.js is a declarative data visualization framework that renders interactive, responsive charts directly onto an HTML5 canvas element. It functions as a configuration-driven engine, transforming structured datasets into complex graphical representations by merging user-defined settings with global defaults. The library utilizes a high-performance rendering pipeline that executes drawing commands during each animation frame to maintain smooth visual feedback. The project distinguishes itself through a modular, extensible architecture that allows developers to register custom scales, control
Maps complex datasets onto specific coordinate spaces by defining axis types, positions, and identifiers.
Plotly.js is a JavaScript charting library and interactive graphing framework used to create web-based visualizations. It functions as a high-performance data visualization engine that utilizes both SVG for static elements and WebGL for hardware-accelerated rendering of large datasets and complex 3D plots. The library is distinguished by specialized toolkits for financial analysis, such as candlestick and OHLC charts, and geographic mapping tools for rendering choropleth and scatter maps with custom projections. It also supports complex scientific visualizations, including Sankey diagrams, pa
Controls axis ranges, tick formatting, SI prefixes, and category ordering for various coordinate systems.
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
Provides configuration utilities for refining chart appearance, including axis labels and tick formatting.
G2 is a declarative data visualization engine that constructs complex charts and graphical representations by mapping raw data to visual elements through a systematic grammar of graphics. It functions as a modular framework for building custom analytical visualizations, allowing users to define visual encodings and coordinate systems independently of the underlying data. The library distinguishes itself through a multi-backend rendering pipeline that supports Canvas, SVG, and WebGL, ensuring consistent graphical performance across different environments. Its architecture relies on a plugin-ba
Aligns multiple axes and coordinate systems to visualize complex multi-dimensional data relationships.
react-vis is a declarative, component-based React data visualization library. It provides a framework of reusable building blocks for rendering interactive charts and graphs by mapping raw data to visual attributes such as position, color, and size. The system leverages D3 for its scaling and layout logic. The library is distinguished by its ability to handle complex data relationships, including hierarchical data via tree maps and circle packing, as well as multidimensional analysis using parallel axes and radar charts. It also supports network flow mapping to illustrate the volume and direc
Provides utilities for customizing the appearance and formatting of axis tick labels.
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
Configures time or numeric axes with formatted tick values, custom time units, and adjustable orientation.
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
Controls tick positions, label formats, density, rotation, and grid lines for any chart axis.
Flot is an interactive charting library for jQuery that renders line, bar, pie, and time-series plots with zooming and panning. It provides interactive plots for engineering and scientific data with customizable axes, scales, and series styles, and supports real-time data updates. The library is built as a jQuery plugin with a canvas-based rendering pipeline and a plugin extension system that allows third-party code to add new chart types, interactions, and data transformations. The library distinguishes itself through a broad range of specialized chart types, including candlestick, bubble, r
Controls tick label spacing, width, and positioning for chart axes.
Applies number, date, or custom string formatting to x-axis and y-axis tick labels independently.
tui.chart ist eine JavaScript-Datenvisualisierungsbibliothek und eine Multi-Typ-Charting-Engine, die zum Rendern interaktiver statistischer Diagramme verwendet wird. Sie fungiert als responsives Charting-Framework und Echtzeit-Datenvisualisierer und nutzt HTML5 Canvas für hochperformantes Rendering diverser Datensätze. Die Bibliothek bietet eine breite Palette an visuellen Formaten, einschließlich linearer, zirkulärer, rasterbasierter, hierarchischer und statistischer Diagrammtypen. Dies deckt alles ab, von Standard-Balken-, Linien- und Tortendiagrammen bis hin zu spezialisierteren Visualisierungen wie Radar-Diagrammen, Treemaps, Blasendiagrammen und Box-Plots. Die Engine enthält umfassende Funktionen für Echtzeit-Datenüberwachung mit Live-Updates und die Entwicklung interaktiver Dashboards. Sie unterstützt fortschrittliche Interaktionsmodelle wie Zoomen, Reihenauswahl und synchronisierte Tooltips über mehrere Diagramme hinweg, während sie Datenexport-Dienstprogramme für CSV-, XLS-, PNG- und JPEG-Formate bietet. Das Framework verwaltet adaptive Layouts durch einen Resize-Observer, der Diagrammoptionen und Animationen automatisch basierend auf Container-Dimensionen anpasst.
Provides customizable formatting for date and time labels displayed on chart axes.
Diese C++-Datenvisualisierungsbibliothek ist ein wissenschaftliches Plotting-Framework, das zum Erstellen von 2D- und 3D-Diagrammen, Netzwerk-Graphen und geografischen Karten verwendet wird. Sie arbeitet als Multi-Backend-Grafikbibliothek, die High-Level-Plotting-Logik von Low-Level-Rendering-Engines entkoppelt, um verschiedene Ausgabe-Backends zu unterstützen. Das Projekt zeichnet sich durch eine Dual-Interface-API aus, die sowohl ein globales funktionales Interface für schnelles Prototyping als auch ein objektorientiertes Interface für präzise Kontrolle bietet. Es verfügt über eine Komponenten-basierte Layout-Engine zur Verwaltung gekachelter Grids und Subplots, neben einem Layered-Plot-State, der es ermöglicht, mehrere Datenserien zu überlagern, ohne Achsen zu löschen. Die Bibliothek deckt ein breites Spektrum an Visualisierungsfunktionen ab, einschließlich mathematischem Funktionsplotten, Vektorfeldern und multidimensionaler Datenanalyse durch Heatmaps und parallele Koordinaten. Sie enthält spezialisierte Tools für die Visualisierung geografischer Daten, wie Geobubble- und Geodensity-Plots, sowie Tools zum Rendern gerichteter und ungerichteter Graphennetzwerke. Zu den allgemeinen Funktionen gehören Achsenverwaltung, ästhetisches Styling mit Colormaps und der Export hochwertiger Grafiken. Das Projekt nutzt CMake für Build-Automatisierung und Dependency-Retrieval, um die Installation über verschiedene Betriebssysteme hinweg zu erleichtern.
Provides utilities to format X-axis tick labels using custom strings or currency styles.
bqplot is an interactive data visualization library for IPython and Jupyter notebooks that utilizes a grammar of graphics. It functions as a tool for creating 2D charts and maps with real-time updates and bidirectional communication between the kernel and frontend. The library is distinguished by its ability to act as a geographic data visualization tool, rendering choropleth maps and spatial data via GeoJSON and custom projections. It also serves as a financial charting tool for producing OHLC and candle bar charts, and as an interactive dashboard framework for combining plotting widgets wit
Creates visual line axes for numerical or date scales with custom tick formatting.
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
Determines the numerical values of ticks and converts them into labels using strings or functions.
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
Configures independent vertical axes, tick labels, and grid layouts for diverse data types like currency or time.
This project is a cross-platform mobile graphing library designed for rendering high-performance animated line charts and data visualizations. It functions as a canvas-based data visualization system and interactive charting component for mobile applications. The library focuses on animated data visualization, using interpolation to create smooth visual transitions between different data sets. It utilizes a GPU-accelerated graphics engine to maintain high frame rates and fluid transitions during data updates. The capability surface includes interaction systems for tracking pan gestures and d
Implements dynamic formatting and rendering of labels for the graph's minimum and maximum axes.