Open Source Data Visualization Software - Page 24
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Data Visualization Software
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Visdom
A tool for creating, organizing, and sharing data visualizations
A flexible tool for creating, organizing, and sharing visualizations of live, rich data. Supports Torch and Numpy. Visdom aims to facilitate visualization of (remote) data with an emphasis on supporting scientific experimentation. Broadcast visualizations of plots, images, and text for yourself and your collaborators. Organize your visualization space programmatically or through the UI to create dashboards for live data, inspect results of experiments, or debug experimental code. Visdom has a simple set of features that can be composed for various use-cases. The UI begins as a blank slate, you can populate it with plots, images, and text. These appear in windows that you can drag, drop, resize, and destroy. The windows live in envs and the state of envs is stored across sessions. You can download the content of windows, including your plots in svg. -
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Vulkan.jl
Using Vulkan from Julia
Vulkan.jl is a lightweight wrapper around the Vulkan graphics and compute library. It exposes abstractions over the underlying C interface, primarily geared toward developers looking for a more natural way to work with Vulkan with minimal overhead. It builds upon the core API provided by VulkanCore.jl. Because Vulkan is originally a C specification, interfacing with it requires some knowledge before correctly being used from Julia. This package acts as an abstraction layer, so that you don't need to know how to properly call a C library, while still retaining full functionality. The wrapper is generated directly from the Vulkan Specification. -
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WAV.jl
Julia package for working with WAV files
This is a Julia package to read and write the WAV audio file format. WAV provides wavread, wavwrite and wavappend functions to read, write, and append to WAV files. The function wavplay provides simple audio playback. These functions behave similarly to the former MATLAB functions of the same name. -
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Wavelets.jl
A Julia package for fast discrete wavelet transforms and utilities
A Julia package for fast wavelet transforms (1-D, 2-D, 3-D, by filtering or lifting). The package includes discrete wavelet transforms, column-wise discrete wavelet transforms, and wavelet packet transforms. 1st generation wavelets using filter banks (periodic and orthogonal). Filters are included for the following types: Haar, Daubechies, Coiflet, Symmlet, Battle-Lemarie, Beylkin, Vaidyanathan. 2nd generation wavelets by lifting (periodic and general type including orthogonal and biorthogonal). Included lifting schemes are currently only for Haar and Daubechies (under development). A new lifting scheme can be easily constructed by users. The current implementation of the lifting transforms is 2x faster than the filter transforms. Thresholding, best basis, and denoising functions, e.g. TI denoising by cycle spinning, best basis for WPT, noise estimation, and matching pursuit. -
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awesome-single-cell
Community-curated list of software packages and data resources
Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc. List of software packages (and the people developing these methods) for single-cell data analysis, including RNA-seq, ATAC-seq, etc. Rapid, accurate and memory-frugal preprocessing of single-cell and single-nucleus RNA-seq data. Find bimodal, unimodal, and multimodal features in your data. Ascend is an R package comprised of fast, streamlined analysis functions optimized to address the statistical challenges of single cell RNA-seq. The package incorporates novel and established methods to provide a flexible framework to perform filtering, quality control, normalization, dimension reduction, clustering, differential expression and a wide-range of plotting. An analytical framework for big-scale single cell data. Transform percentage-based units into a 2d space to evaluate changes in distribution with both magnitude and direction. -
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brms
brms R package for Bayesian generalized multivariate models using Stan
brms is an R package by Paul Bürkner which provides a high-level interface for fitting Bayesian multilevel (i.e. mixed effects) models, generalized linear / non-linear / multivariate models using Stan as the backend. It allows R users to specify complex Bayesian models using formula syntax similar to lme4 but with far more flexibility (distributions, link functions, hierarchical structure, nonlinear terms, etc.). It supports model diagnostics, posterior predictive checking, model comparison, custom priors, and advanced features such as distributional regression. -
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city-roads
Visualization of all roads within any city
city-roads is a data visualization and mapping project that renders street networks of cities as vector paths, offering an interactive, zoomable experience that highlights how cities are stitched together by their road infrastructure. It typically fetches open map data (such as from OpenStreetMap) and then processes that data into geometry suited for rendering in the browser, allowing users to explore intricate road layouts at various scales. The visual style often abstracts away labels and extraneous map features to focus purely on the road network, giving a unique, aesthetic view of urban form and connectivity. Because road topology reflects historical, geographic, and planning decisions, the resulting images serve as both analytical tools and generative art. Developers can integrate it into web pages or interactive dashboards where geographic structure is central, and users can pan/zoom to compare different cities or neighborhoods. -
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dc.js
Multi-Dimensional charting built to work natively with crossfilter
dc.js is a javascript charting library with native crossfilter support, allowing highly efficient exploration on large multi-dimensional datasets (inspired by crossfilter's demo). It leverages d3 to render charts in CSS-friendly SVG format. Charts rendered using dc.js are data driven and reactive and therefore provide instant feedback to user interaction. Dimensional charting built to work natively with crossfilter rendered using d3.js. In dc.js, each chart displays an aggregation of some attributes through the position, size, and color of its elements, and also presents a dimension which can be filtered. When the filter or brush changes, all other charts are updated dynamically, using animated transitions. dc.js is an easy yet powerful javascript library for data visualization and analysis in the browser and on mobile devices. -
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echarts-for-react
Apache ECharts components for React wrapper
echarts-for-react is a React wrapper for Apache ECharts that lets developers render ECharts visualizations inside React applications. It provides a simple component-based interface where users pass an ECharts option object to generate charts. The package supports common React integration needs, including themes, styles, loading states, chart-ready callbacks, event binding, and renderer options. It also exposes access to the underlying ECharts instance, which lets developers use the full ECharts API when needed. The project includes guidance for importing ECharts modules manually to reduce bundle size and for using it with Next.js. Overall, it is a practical bridge between React projects and the full charting power of Apache ECharts. -
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ggpubr
'ggplot2' Based Publication Ready Plots
ggpubr is an R package that provides easy-to-use wrapper functions around ggplot2 to create publication-ready visualizations with minimal code. It streamlines plot creation for researchers and analysts, allowing features such as statistical annotation, theme customization, and plot arrangement with fewer lines of code. -
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graphdot
Visualize Go module dependencies in Graphviz DOT format
Visualize Go module dependencies in Graphviz DOT format. Run graphdot in the directory of any project using Go modules with a go.mod file to print out a dependency graph in Graphviz DOT format. The output can be piped directly into dot to generate a PNG image file. For large graphs with many nodes of dependencies, you may want to generate an SVG file to allow you to zoom in with high fidelity and save disk space instead. If you like a more UML'ish style, you can use the provided graph properties from uml.gprops. -
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kotlin-math
Set of Kotlin APIs to make graphics math easier to write.
Set of Kotlin APIs to make graphics math easier to write. These APIs are mostly modeled after GLSL (OpenGL Shading Language) to make porting code to and from shaders easier. The various types offered by this library are only meant to be value types. Most APIs are therefore exposed as top-level functions and not as methods. -
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leafmap
A Python package for interactive mapping and geospatial analysis
A Python package for geospatial analysis and interactive mapping in a Jupyter environment. Leafmap is a Python package for interactive mapping and geospatial analysis with minimal coding in a Jupyter environment. It is a spin-off project of the geemap Python package, which was designed specifically to work with Google Earth Engine (GEE). However, not everyone in the geospatial community has access to the GEE cloud computing platform. Leafmap is designed to fill this gap for non-GEE users. It is a free and open-source Python package that enables users to analyze and visualize geospatial data with minimal coding in a Jupyter environment, such as Google Colab, Jupyter Notebook, and JupyterLab. Leafmap is built upon several open-source packages, such as folium and ipyleaflet (for creating interactive maps), WhiteboxTools and whiteboxgui (for analyzing geospatial data), and ipywidgets (for designing interactive graphical user interface [GUI]). -
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luma.gl
High-performance Toolkit for WebGL-based data visualization
luma.gl is a GPU toolkit for the Web-focused primarily on data visualization use cases. luma.gl aims to provide support for GPU programmers that need to work directly with shaders and want a low abstraction API that remains conceptually close to the WebGPU and WebGL APIs. Unlike other common WebGL APIs, the developer can choose to use the parts of luma.gl that support their use case and leave the others behind. While generic enough to be used for general 3D rendering, luma.gl's mandate is primarily to support GPU needs of data visualization frameworks in the vis.gl suite. -
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md2googleslides
Generate Google Slides from markdown
Generate Google Slides from markdown & HTML. Run from the command line or embed in another application. This project was developed as an example of how to use the Slides API. While it does not yet produce stunningly beautiful decks, you are encouraged to use this tool for quickly prototyping presentations. The first time the command is run you will be prompted for authorization. OAuth token credentials are stored locally in a file named ~/.md2googleslides/credentials.json. Each time you will run the above comment, new slide deck will be generated. In order to work on exactly the same deck, just get the ID of the already generated slides. md2googleslides does not edit or control any theme-related options. Just set a base theme you want on Google Slides directly. Even if you will use, append option for deck reuse, theme will be not changed. Images can be placed on slides using image tags. Multiple images can be included. -
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ngx-datatable
A feature-rich yet lightweight data-table crafted for Angular
ngx-datatable is an Angular component for presenting large and complex data. It has all the features you would expect from any other table but in a light package with no external dependencies. The table was designed to be extremely flexible and light; it doesn't make any assumptions about your data or how you: filter, sort or page it. It was built for modern browsers using TypeScript, CSS3 and HTML5 and Angular 8.0.0. This is the sister project of the angular-data-table that is designed for Angular 1.x. Intelligent Column Width Algorithms (Force-fill & Flex-grow). Fixed AND Fluid height. Left and Right Column Pinning. Row Detail View. Decoupled theme'ing with included Google Material theme. Light codebase / No external dependencies. AoT Compilation Support. Universal Support. Cell & Row Selection. -
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nvim-hlslens
Hlsearch Lens for Neovim
nvim-hlslens helps you better glance at matched information, and seamlessly jump between matched instances. -
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nw_wrld
nw_wrld is an event-driven sequencer for triggering visuals
nw_wrld is a procedurally generated world-building engine tailored for game developers and interactive storytellers who want to craft rich, random yet coherent environments without hand-crafting every detail. It uses noise functions and modular terrain algorithms to generate expansive maps, diverse biomes, and layered features like rivers, mountain ranges, forests, and resource nodes. The system is designed to be extensible, letting developers plug in new generation rules or tweak parameters with real-time previews so they can iterate rapidly on world design. It also includes utilities to derive metadata from worlds, such as climate distributions, strategic points of interest, and navigable paths, which can be consumed by gameplay systems or AI agents. For teams building games or simulations, nw_wrld provides a reusable foundation that reduces upfront world design costs while enabling endless variety. -
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repo2docker GitHub Action
A GitHub action to build data science environment images
Trigger repo2docker to build a Jupyter enabled Docker image from your GitHub repository and push this image to a Docker registry of your choice. This will automatically attempt to build an environment from configuration files found in your repository. Images generated by this action are automatically tagged with both latest and <SHA> corresponding to the relevant commit SHA on GitHub. Both tags are pushed to the Docker registry specified by the user. If an existing image with the latest tag already exists in your registry, this Action attempts to pull that image as a cache to reduce uncessary build steps. -
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see
Visualisation toolbox for beautiful and publication-ready figures
see is an R package that serves as the visualization component of the easystats ecosystem, providing plotting utilities to produce publication-ready visualizations of statistical model parameters, diagnostics, predictions, and performance metrics. It works in conjunction with other easystats packages (such as parameters, performance, modelbased, bayestestR, etc.) to convert model outputs or summary objects into visual forms (dot-and-whisker plots, diagnostic plots, residual plots, etc.). It includes themes, scales, geoms for ggplot2, and custom color palettes to make visual summaries more informative and attractive. -
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stats Koa
Request statistics middleware that stores response times, status code
Request statistics middleware. Request statistics middleware that stores response times, status code counts, etc. -
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tikzcd-editor
A simple visual editor for creating commutative diagrams
A simple visual editor for creating commutative diagrams. -
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visx
Visualization components
visx a collection of expressive, low-level visualization primitives for React. At Airbnb, we made it a goal to unify our visualization stack across the company and in the process, we created a new project that brings together the power of D3 with the joy of React. visx is split into multiple packages. Start small and use only what you need. Bring your own state management, animation library, or CSS-in-JS solution. Odds are good your React app already has an opinion on how animation, theming, or styling is done. visx is careful not to add another one and integrates with all of them. As you start using visualization primitives, you’ll end up building your own charting library that’s optimized for your use case. You’re in control. And most importantly, it’s just React. If you know React, you can make visualizations. It’s all the same standard APIs and familiar patterns. visx should feel at home in any React codebase. -
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Teem
Tools to process and visualize scientific data and images
Teem is a set of C libraries for manipulation, measurement, and visualization of structured scientific data. Includes N-dimensional image I/O and processing, volume rendering, diffusion tensor processing, and more. Latest code via git clone http://git.code.sf.net/p/teem/teem.git . Join us at https://discord.gg/xBBqZGXkF7 -
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