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11 repository-uri

Awesome GitHub RepositoriesBox Plots

Charts that visualize data distribution using boxes and whiskers to show quartiles and outliers.

Distinguishing note: A specific statistical visualization type not covered by the candidates.

Explore 11 awesome GitHub repositories matching data & databases · Box Plots. Refine with filters or upvote what's useful.

Awesome Box Plots GitHub Repositories

Găsește cele mai bune repo-uri cu AI.Vom căuta cele mai potrivite repository-uri folosind AI.
  • dc-js/dc.jsAvatar dc-js

    dc-js/dc.js

    7,431Vezi pe GitHub↗

    dc.js is a multi-dimensional analysis tool and visualization framework used to build interactive data dashboards. It functions as a charting library that renders diverse SVG visualizations powered by D3 and integrates natively with Crossfilter to enable coordinated filtering across large datasets. The project is distinguished by its linked-view coordination, where selecting a data range or category in one chart simultaneously updates all other connected views. This allows for dynamic data exploration through dimensional chart linking and coordinated brushing, transforming raw datasets into na

    Provides data distribution visualizations using boxes and whiskers with outlier highlighting and tooltips.

    JavaScript
    Vezi pe GitHub↗7,431
  • cxli233/friendsdontletfriendsAvatar cxli233

    cxli233/FriendsDontLetFriends

    6,994Vezi pe GitHub↗

    FriendsDontLetFriends is a scientific data visualization guide and framework designed to help users create accurate plots while avoiding common data representation mistakes. It provides a collection of scripts and guidelines for selecting distribution plots, color scales, and layouts that accurately represent complex experimental data. The project distinguishes itself through specialized toolkits for revealing hidden patterns in large datasets. It includes systems for heatmap optimization via dimension reordering and outlier management, as well as spatial layout algorithms to improve the inte

    Provides a framework for choosing between violin plots, histograms, or box plots based on sample size and data modality.

    Rdata-visualizationr
    Vezi pe GitHub↗6,994
  • scottplot/scottplotAvatar ScottPlot

    ScottPlot/ScottPlot

    6,417Vezi pe GitHub↗

    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

    Shows distribution statistics from collections of values using customizable box and whisker symbols.

    C#chartchartingcharts
    Vezi pe GitHub↗6,417
  • evidence-dev/evidenceAvatar evidence-dev

    evidence-dev/evidence

    5,919Vezi pe GitHub↗

    Summarizes data distribution using boxes and whiskers to show quartiles and outliers.

    JavaScriptanalyticsbusiness-intelligencedashboard
    Vezi pe GitHub↗5,919
  • vega/vega-liteAvatar vega

    vega/vega-lite

    5,216Vezi pe GitHub↗

    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

    Renders box plots showing median, quartiles, and outliers of quantitative distributions.

    TypeScriptchartsdeclarative-languageplot
    Vezi pe GitHub↗5,216
  • nyandwi/machine_learning_completeAvatar Nyandwi

    Nyandwi/machine_learning_complete

    4,983Vezi pe GitHub↗

    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

    Provides implementations of histograms, count plots, and bar charts for analyzing data modality and spread.

    Jupyter Notebookcomputer-visiondata-analysisdata-science
    Vezi pe GitHub↗4,983
  • alandefreitas/matplotplusplusAvatar alandefreitas

    alandefreitas/matplotplusplus

    4,894Vezi pe GitHub↗

    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

    Provides box-and-whisker plots to visualize data distribution through quartiles, medians, and outliers.

    C++charting-librarychartscontour-plots
    Vezi pe GitHub↗4,894
  • swimlane/ngx-chartsAvatar swimlane

    swimlane/ngx-charts

    4,359Vezi pe GitHub↗

    ngx-charts is an Angular charting library and SVG data visualization framework. It provides a set of declarative UI components for rendering animated and interactive charts and graphs within Angular applications. The library allows for the assembly of specialized visualizations by combining low-level internal charting components. It supports the creation of custom charts through the use of mathematical scales, shape generators, and CSS styling overrides. The framework covers a wide range of visualization types, including comparison charts such as bar and line graphs, distribution visualizati

    Includes box-and-whisker plots to visualize statistical data distributions including quartiles and outliers.

    TypeScript
    Vezi pe GitHub↗4,359
  • bloomberg/bqplotAvatar bloomberg

    bloomberg/bqplot

    3,693Vezi pe GitHub↗

    bqplot is an interactive data visualization library for Jupyter notebooks. It implements a grammar of graphics model, allowing users to build complex 2D charts by combining marks, scales, and axes. The library distinguishes itself with specialized toolkits for financial charting, such as OHLC candlesticks and time-series analysis, and geographic data visualization, including choropleths and custom map projections for TopoJSON and GeoJSON data. It enables deep interaction through tools like lasso selection, rectangular brushing, and the ability to manually manipulate plot points or line data.

    Visualizes data distributions using box-and-whisker plots to highlight quartiles and outliers.

    TypeScript
    Vezi pe GitHub↗3,693
  • mne-tools/mne-pythonAvatar mne-tools

    mne-tools/mne-python

    3,243Vezi pe GitHub↗

    MNE-Python is an open-source Python library for processing, visualizing, and analyzing human neurophysiological data, including MEG, EEG, sEEG, ECoG, and NIRS recordings. It provides a comprehensive framework for loading data from over 30 proprietary file formats into a common hierarchical FIF data structure, and represents all time-series data as NumPy arrays for seamless integration with the scientific Python ecosystem. The library is built around object-oriented data containers that encapsulate raw, epoched, evoked, and source data with built-in preprocessing and visualization methods. The

    Generates topographic maps of the scalp field distribution at specified time points, with configurable averaging durations.

    Pythonecogeegelectrocorticography
    Vezi pe GitHub↗3,243
  • gpac/gpacAvatar gpac

    gpac/gpac

    3,205Vezi pe GitHub↗

    GPAC is an open-source multimedia framework built around a pluggable filter graph pipeline, where modular processing units called filters connect into a directed graph to handle media workflows. At its core, the framework centers all media packaging and manipulation on the ISO Base Media File Format (ISOBMFF), with specialized tools for reading, writing, fragmenting, and encrypting MP4 and related containers. It also provides a declarative scene graph composition system for describing interactive multimedia scenes using MPEG-4 BIFS, X3D, SVG, or VRML syntax, alongside a hardware-accelerated re

    Enables runtime injection of custom ISOBMFF boxes during media encoding.

    Catsc3broadcastcenc
    Vezi pe GitHub↗3,205
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Explorează sub-etichetele

  • Distribution Analysis PlotsCharts used to analyze data modality and spread, including violin and box plots. **Distinct from Box Plots:** Broadens from just Box Plots to include the logic of selecting between different distribution types based on sample size.
  • Distribution Plot Selection1 sub-tagLogic for choosing the most appropriate distribution visualization based on data modality and sample size. **Distinct from Box Plots:** Focuses on the selection criteria between different plot types (violin, box, histogram) rather than a specific plot type.
  • ISOBMFF Box PatchesApplies custom box patches to ISOBMFF output during encoding, with per-PID customization. **Distinct from Box Plots:** Distinct from Box Plots: focuses on modifying ISOBMFF container structure, not statistical visualization.