Open Source Windows Data Visualization Software - Page 12
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Data Visualization Software for Windows
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99.99% Uptime for MySQL and PostgreSQL DatabasesCloud SQL Enterprise Plus delivers near-zero downtime with 35 days of point-in-time recovery. Supports MySQL, PostgreSQL, and SQL Server.
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Rawgraphs app
A web interface to create custom vector-based visualizations
Inspired by and built on top of open-source projects. RAWGraphs is open to the community for contributions. Almost 30 visual models to visualize quantities, hierarchies, and time series and find insights in your data. Even though RAWGraphs is a web app, the data you insert will be processed only by your web browser. Save your project, or export it as a vector or raster image. Edit it within your favorite software. RAWGraphs is an open source data visualization framework built with the goal of making the visual representation of complex data easy for everyone. Primarily conceived as a tool for designers and vis geeks, RAWGraphs aims at providing a missing link between spreadsheet applications (e.g. Microsoft Excel, Apple Numbers, OpenRefine) and vector graphics editors (e.g. Adobe Illustrator, Inkscape, Figma). The project, led and maintained by the DensityDesign Research Lab (Politecnico di Milano) was released publicly in 2013. -
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ReachabilityAnalysis.jl
Compute reachable states of dynamical systems
Reachability analysis is concerned with computing rigorous approximations of the set of states reachable by a dynamical system. In the scope of this package are systems modeled by continuous or hybrid dynamical systems, where the dynamics change with discrete events. Systems are modeled by ordinary differential equations (ODEs) or semi-discrete partial differential equations (PDEs), with uncertain initial states, uncertain parameters or non-deterministic inputs. -
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React Lifecycle Methods diagram
Interactive React Lifecycle Methods diagram
React Lifecycle Methods Diagram is an interactive educational visualization of React component lifecycle methods. It is based on a lifecycle diagram originally shared by Dan Abramov and was rebuilt as a React web application. The diagram organizes methods according to when they run during component mounting, updating, and unmounting. Clicking a method opens its corresponding official React documentation for deeper reference. Commonly used methods are visually emphasized while related lifecycle actions are distinguished separately. Accessibility was designed for keyboard users and screen readers rather than relying only on visual interaction. The project also supports localization and can accommodate alternate diagram versions as React lifecycle APIs evolve. -
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ReactiveMP.jl
High-performance reactive message-passing based Bayesian engine
ReactiveMP.jl is a Julia package that provides an efficient reactive message passing based Bayesian inference engine on a factor graph. The package is a part of the bigger and user-friendly ecosystem for automatic Bayesian inference called RxInfer. While ReactiveMP.jl exports only the inference engine, RxInfer provides convenient tools for model and inference constraints specification as well as routines for running efficient inference both for static and real-time datasets. -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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RxMarbles
Interactive diagrams of Rx Observables
RxMarbles is an open-source interactive web application that teaches reactive programming through animated marble diagrams. It visualizes how ReactiveX operators transform sequences of events over time. Each diagram displays input streams, operator behavior, and resulting output streams. Users can drag individual marbles along a timeline to observe how different event positions affect the results. The application includes examples of operators used for mapping, filtering, combining, and delaying observable sequences. Individual diagrams can be shared through direct links for demonstrations or educational discussions. Built using Cycle.js, it also serves as an example of reactive interface development. The repository is archived, but the educational website remains accessible. -
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ScottPlot
Interactive Plotting Library for .NET
ScottPlot is a free and open-source plotting library for .NET that makes it easy to interactively display large datasets. Line plots, bar charts, pie graphs, scatter plots, and more can be created with just a few lines of code. The ScottPlot Cookbook demonstrates how to create line plots, bar charts, pie graphs, scatter plots, and more with just a few lines of code. The ScottPlot Demo is a click-to-run application that demonstrates mouse-interactive versions of every cookbook recipe. ScottPlot does not require a GUI so it can be used to create plots in cloud applications. The images below are regenerated hourly using Azure Functions to update star metrics from the GitHub API and download count from the NuGet API. The data is plotted with ScottPlot and saved as an image file in blob storage. -
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Setfield.jl
Update deeply nested immutable structs
Update deeply nested immutable structs. We plan to maintain Setfield.jl for a long time. We will however not add new features. -
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Space Radar Electron
Disk And Memory Space Visualization App built with Electron & d3.js
Space Radar Electron is an application that offers an interactive and comprehensive visualization of disk space and memory usage of your computer. Built with Electron & d3.js, it currently offers visualizations in the form of Sunburst, Treemap and Flamegraph charts. As it scans the contents of your disk, it produces a preview visualization so you can already see what's been scanned. It allows for drilldown of directories, breadcrumbs and navigation. Space Radar works fast, and is cross-platform. Currently, there are many developments being planned for Space Radar, including more targets for scanning, coloring by file types, filtering hidden files and more. -
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SumOfSquares.jl
Sum of Squares Programming for Julia
SumOfSquares.jl is a JuMP extension that, when used in conjunction with MultivariatePolynomial and PolyJuMP, implements a sum of squares reformulation for polynomial optimization. -
Endpoint Management with Remote Control Built InSplashtop AEM handles patching, alerts, scripts, and inventory, and unattended remote control is included. When something needs hands-on work, you’re one click away instead of switching tools.
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Sweetviz
Visualize and compare datasets, target values and associations
Sweetviz is an open-source Python library that generates beautiful, high-density visualizations to kickstart EDA (Exploratory Data Analysis) with just two lines of code. Output is a fully self-contained HTML application. The system is built around quickly visualizing target values and comparing datasets. Its goal is to help quick analysis of target characteristics, training vs testing data, and other such data characterization tasks. Shows how a target value (e.g. "Survived" in the Titanic dataset) relates to other features. Sweetviz integrates associations for numerical (Pearson's correlation), categorical (uncertainty coefficient) and categorical-numerical (correlation ratio) datatypes seamlessly, to provide maximum information for all data types. Automatically detects numerical, categorical and text features, with optional manual overrides. min/max/range, quartiles, mean, mode, standard deviation, sum, median absolute deviation, coefficient of variation, kurtosis, skewness. -
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SymbolicNumericIntegration.jl
SymbolicNumericIntegration.jl: Symbolic-Numerics for Solving Integrals
SymbolicNumericIntegration.jl is a hybrid symbolic/numerical integration package that works on the Julia Symbolics expressions. -
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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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XLSX.jl
Excel file reader and writer for the Julia language
XLSX.jl is a Julia package to read and write Excel spreadsheet files. Internally, an Excel XLSX file is just a Zip file with a set of XML files inside. The formats for these XML files are described in the Standard ECMA-376. This package follows the EMCA-376 to parse and generate XLSX files. -
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classic.tplx
A more accurate representation of jupyter notebooks
A more accurate representation of Jupyter notebooks when converting to pdfs. This template was designed to make converted Jupyter notebooks look (almost) identical to the actual notebook. If something doesn't exist in the original notebook then it doesn't belong in the conversion. As of nbconvert 5.5.0, the majority of these improvements have been merged into nbconvert's default template. Version 3.x of this package will continue to support nbconvert 5.5.0 and lower, whereas in the future version 4.x will only support nbconvert 5.5.0 and newer. Versions 3.x, and 4.x will overlap support for nbconvert version 5.5.0. -
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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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esquisse
RStudio add-in to make plots interactively with ggplot2
The purpose of this add-in is to let you explore your data quickly to extract the information they hold. You can create visualization with {ggplot2}, filter data with {dplyr} and retrieve generated code. This addin allows you to interactively explore your data by visualizing it with the ggplot2 package. It allows you to draw bar plots, curves, scatter plots, histograms, boxplot and sf objects, then export the graph or retrieve the code to reproduce the graph. This addin allows you to interactively explore your data by visualizing it with the ggplot2 package. It allows you to draw bar plots, curves, scatter plots, histograms, boxplot and sf objects, then export the graph or retrieve the code to reproduce the graph. -
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flot
Attractive JavaScript charts for jQuery
Flot is a pure JavaScript plotting library for jQuery, with a focus on simple usage, attractive looks and interactive features. Works with Internet Explorer 6+, Chrome, Firefox 2+, Safari 3+ and Opera 9.5+. Additional examples are bundled with Flot. Also take a look at the Flot Usage Wiki for screenshots and stories from people and companies using Flot. Take a look at the the examples in examples/index.html; they should give a good impression of what flot can do, and the source code of the examples is probably the fastest way to learn how to use flot. Just include the JavaScript file after you've included jQuery. You need at least jQuery 1.2.6, but try at least 1.3.2 for interactive charts because of performance improvements in event handling. The plot function immediately draws the chart and then returns a plot object with a couple of methods. The placeholder is a jQuery object or DOM element or jQuery expression that the plot will be put into. -
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folium
Python data, Leaflet.js maps
folium builds on the data wrangling strengths of the Python ecosystem and the mapping strengths of the leaflet.js library. Manipulate your data in Python, then visualize it in on a Leaflet map via folium. folium makes it easy to visualize data that’s been manipulated in Python on an interactive leaflet map. It enables both the binding of data to a map for choropleth visualizations as well as passing rich vector/raster/HTML visualizations as markers on the map. The library has a number of built-in tilesets from OpenStreetMap, Mapbox, and Stamen, and supports custom tilesets with Mapbox or Cloudmade API keys. folium supports both Image, Video, GeoJSON and TopoJSON overlays. To create a base map, simply pass your starting coordinates to Folium. To display it in a Jupyter notebook, simply ask for the object representation. The default tiles are set to OpenStreetMap, but Stamen Terrain, Stamen Toner, Mapbox Bright, and Mapbox Control Room, and many others tiles are built in. -
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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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ggrepel
epel overlapping text labels away from each other in your ggplot2
ggrepel is an R package that provides “smart” repulsion for text and label geoms in ggplot2. When placing text labels on a plot (e.g. labeling points), the labels can often overlap; ggrepel ensures labels don’t overlap (or overlap less) by repelling labels / pushing them away, adding connecting lines or nudges, etc. It improves the readability of plots, especially when many labels are present. Support for point and segment geoms (so labels can be connected by lines when moved). Supports both plotting of labels inside or outside plot area, with trimming/clipping etc. -
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gping
Ping, but with a graph
Graphical Ping displays a color-coded realtime graph of continuous pings to a specified host. No warranties are provided on this program, it is completely free to use. Graph the execution time for a list of commands rather than pinging hosts. Resolve ping targets to IPv4 address. Resolve ping targets to IPv6 address. Uses dot characters instead of braille. Determine the number of seconds to display in the graph. Watch interval seconds (provide partial seconds like '0.5'). -
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inMap
Rich layers, better user experience, big data geographic visualization
inMap is a big data visualization library based on Baidu Map. It focuses on the display of scatter, heat map, grid, and aggregation in the direction of big data. It is committed to making big data visualization easy to use. -
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indicators
Activity Indicators for Modern C++
Indicators is an open-source C++ library for displaying customizable progress bars, spinners, and activity indicators in terminal applications. It provides responsive visual feedback for long-running tasks such as downloads, file processing, and computational operations. The library includes basic, block-style, and indeterminate progress bars, along with animated spinners and multiple concurrent indicators. Developers can customize colors, symbols, animation behavior, percentage displays, and elapsed or remaining time estimates. Its thread-safe architecture supports progress updates from concurrent operations. Dynamic progress containers allow indicators to be added or removed during execution. Indicators is distributed as a header-only library, including a convenient single-header version. It supports Unicode output and integrates into modern C++ applications without requiring a separate compiled library. -
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just-dashboard
Dashboards using YAML or JSON files
Dashboards using YAML or JSON files. Create a public GitHub gist with a file named dashboard.yml or dashboard.json (depending on your preferred format) As your dashboard is just data, you can generate it instead of repeating yourself. You can do that by generating the YAML or JSON file yourself, or you can use jq queries in your YAML file. And one with a dashboard that contains a component that can fetch the data from other other gist and turn it into 3 different charts. Using the same principle, you can also loads parts from your dashboard from other files, or just JSON/CSV data for specific charts. Suppose you are only interested in comparing foods by how much they contain of a single macronutrient. However, you want to be able to decide which macronutrient. -
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mapcn
Beautiful map components, 100% Free, Zero config, one command setup
mapcn is a research-oriented project centered on mapping continuous control in reinforcement learning to structured policies using neural networks. It explores how high-dimensional action spaces can be decomposed into structured primitives that can be learned, composed, and reused across different tasks. The core idea is to enable agents to generalize learned behavior by representing continuous control policies in a compact, interpretable form that preserves smoothness and controllability. The project includes implementations that experiment with policy encoding, action decomposition techniques, and sample efficiency analysis in classic reinforcement learning environments. By organizing action outputs into meaningful, lower-dimensional manifolds, MapCN attempts to improve both learning convergence and transfer performance when compared to unguided continuous control baselines.
