Open Source Windows Data Visualization Software
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Data Visualization Software for Windows
View 162 business solutionsBrowse free open source Data Visualization software and projects for Windows below. Use the toggles on the left to filter open source Data Visualization software by OS, license, language, programming language, and project status.
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SciDAVis is a user-friendly data analysis and visualization program primarily aimed at high-quality plotting of scientific data. It strives to combine an intuitive, easy-to-use graphical user interface with powerful features such as Python scriptability.
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Gephi
Gephi the open graph Viz platform
Gephi is the leading visualization and exploration software for all kinds of graphs and networks. Gephi is open-source and free. Gephi is an award-winning open-source platform for visualizing and manipulating large graphs. It runs on Windows, Mac OS X and Linux. Localization is available in English, French, Spanish, Japanese, Russian, Brazilian Portuguese, Chinese, Czech and German. Fast Powered by a built-in OpenGL engine, Gephi is able to push the envelope with very large networks. Visualize networks up to a million elements. All actions (e.g. layout, filter, drag) run in real-time. Simple Easy to install and get started. An UI that is centered around the visualization. Like Photoshop™ for graphs. Modular Extend Gephi with plug-ins. The architecture is built on top of Apache Netbeans Platform and can be extended or reused easily through well-written APIs. -
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Orange Data Mining
Orange: Interactive data analysis
Open source machine learning and data visualization. Build data analysis workflows visually, with a large, diverse toolbox. Perform simple data analysis with clever data visualization. Explore statistical distributions, box plots and scatter plots, or dive deeper with decision trees, hierarchical clustering, heatmaps, MDS and linear projections. Even your multidimensional data can become sensible in 2D, especially with clever attribute ranking and selections. Interactive data exploration for rapid qualitative analysis with clean visualizations. Graphic user interface allows you to focus on exploratory data analysis instead of coding, while clever defaults make fast prototyping of a data analysis workflow extremely easy. Place widgets on the canvas, connect them, load your datasets and harvest the insight! When teaching data mining, we like to illustrate rather than only explain. -
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NumeRe
Framework for numerical computations, data analysis and visualisation
Curve fitting | Data analysis | Plotting | Matrix operations | FFT | Extensible framework | Multiple file formats | Programmable | Open source | Free for everyone NumeRe: Framework for Numerical Computation is a numerical framework written for Microsoft Windows(R) and released under the GNU GPL v3 for solving and visualizing mathematical and physical problems numerically. Keep simple things simple: You want to plot a sine function? Just enter 'plot sin(x)'. You want to load some data? Enter 'load "path/to/your/file"' or drag the file into the terminal. You need to fit a function to the data? Enter 'fit data() -with=YOURFUNCTION(x)' Need assistance? Enter 'help topic' into the terminal or simply press [F1]. Find us on Discord: https://discord.gg/s5tSjwU Follow us on Mastodon: https://fosstodon.org/@numeredevs Visit our page: https://www.numere.org Buy us a coffee: https://ko-fi.com/numere We've moved to GitHub: https://github.com/numere-org -
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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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Datafor Visualization and Analysis
Visualization and Analysis
Datafor is a self-service agile BI tool that provides intuitive and user-friendly data visualization and analysis capabilities to help users quickly explore, analyze, and make decisions with their data. -
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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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AlphaPlot
Interactive scientific graphing and data analysis software.
Alpha Plot can generate different types of 2D and 3D plots (such as line, scatter, bar, pie, and surface plots) from data that is either imported from ASCII files, entered by hand, or calculated using formulas. The data is held in spreadsheets which are referred to as tables with column-based data (typically X and Y values for 2D plots) or matrices (for 3D plots). The spreadsheets as well as graphs and note windows are gathered in a project and can be organized using folders. The built-in analysis operations include column/row statistics, (de)convolution, FFT and FFT-based filters. Scripting Console support in-place evaluation of mathematical expressions and scrtipting interface to ECMAScript like dynamic scripting language(java script). The GUI of the application uses the Qt toolkit. Periodic test builds are available here http://alphaplot.sourceforge.net/test-build.html -
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LabPlot
Data Visualization and Analysis
LabPlot is a FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Metabase
The simplest, fastest way to share business intelligence and analytics
Metabase is the easiest way to let everyone in your company access business data and analytics, learn from it and ask questions. Even if you or your colleagues have no experience in SQL, you can easily summarize and visualize your data, share it and let your team ask questions about it. Metabase creates beautiful graphs and charts, with an easy-to-use dashboard where everyone can create, organize and share exceptionally visualized data. It supports a great number of databases, including Postgres, MySQL, Druid, MongoDB, SQLite and more. Setup literally takes 5 minutes. -
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QtiPlot is a user-friendly, platform independent data analysis and visualization application similar to the non-free Windows program Origin.
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ECharts
A powerful, interactive charting and visualization library for browser
ECharts is a free and open source charting and visualization library that gives you an easy way to add interactive, intuitive, custom charts to your commercial products, projects, presentations and more. It offers a rich set of features that includes rendering ability for ten-million-level data, Wechart and Powerpoint support, multi-dimension data analysis, and more. It also has a number of extensions for various applications. ECharts is written in pure JavaScript, and is based on zrender, a new and lightweight canvas library. -
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Kst is the fastest real-time large-dataset viewing and plotting tool available and has basic data analysis functionality. Kst contains many powerful built-in features and is expandable with plugins and extensions.
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DataMelt
Computation and Visualization environment
DataMelt (or "DMelt") is an environment for numeric computation, data analysis, computational statistics, and data visualization. This Java multiplatform program is integrated with several scripting languages such as Jython (Python), Groovy, JRuby, BeanShell. DMelt can be used to plot functions and data in 2D and 3D, perform statistical tests, data mining, numeric computations, function minimization, linear algebra, solving systems of linear and differential equations. Linear, non-linear and symbolic regression are also available. Neural networks and various data-manipulation methods are integrated using powerful Java API. Elements of symbolic computations using Octave/Matlab scripting are supported. -
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qvge
Qt Visual Graph Editor
qvge is a multiplatform graph editor written in C++/Qt. Its main goal is to make possible visually edit two-dimensional graphs in a simple and intuitive way. Please note that qvge is not a replacement for such a software like Gephi, Graphvis, Dot, yEd, Dia and so on. It is neither a tool for "big data analysis" nor a math application. It is really just a simple graph editor :) -
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The repository has been moved to: https://github.com/wojdyr/fityk. Fityk is nonlinear curve-fitting and data analysis software. It is specialized in fitting peaks (bell-shaped functions like Gaussian, Loretzian, Pearson7, Voigt) to experimental data.
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sadsa
SADSA (Software Application for Data Science and Analytics)
SADSA (Software Application for Data Science and Analytics) is a Python-based desktop application designed to simplify statistical analysis, machine learning, and data visualization for students, researchers, and data professionals. Built using Python for the GUI, SADSA provides a menu-driven interface for handling datasets, applying transformations, running advanced statistical tests, machine learning algorithms, and generating insightful plots — all without writing code. -
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Graph Plotter
GP is a tool to analyse numerical data
GP is aimed to be simple and fast tool to analyse numerical data. It does not claim to replace all other plotters. -
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PANDA
A comprehensive and flexible quantification tool for proteomics data
PANDA is a comprehensive and flexib tool for quantitative proteomics data analysis, which is developed based on our solid foundations in quantitative proteomics for years. Several novelties have been implemented in it. First, we implement the advantage algorithms of LFQuant (Proteomics 2012, 12, (23-24), 3475-84) and SILVER (Bioinformatics 2014, 30, (4), 586-7) into PANDA. Second, we consider the state-of-art concept of quantification reliability in this quantitative workflow. On the levels of spectra, peptides and proteins, PANDA works out a few quantitative filters and new scores for quantification confidence. Third, PANDA is designed for processing proteomics big data in parallel. -
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3Depict
atom probe software : visualisation and data analysis
This software is designed to help users visualize and analyze 3D point clouds with an associated real value, in a fast and flexible fashion. The primary use is in Atom Probe Tomography, which is an atomic imaging technique. However the program may also be useful in other areas, such as geospatial data, lidar, etc. -
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Canvas-2DGC
A user-extensible Freemat based 1DGC and GCxGC data analysis software.
Canvas-2DGC is a user-extensible, Freemat based 1DGC and comprehensive 2DGC (GCxGC) data visualization and processing software. GCxGC-MS data analysis is supported for Agilent GCMS data format. The first goal of this project is to provide a highly intelligent analytical tool for reducing a complex chromatographic data analysis, either 1D or 2D, to just a few simple and intuitive steps. The second goal is to provide a fast and practical way of customizing or extending functionalities by ordinary users through high-level Freemat scripting. Freemat, one of open source Matlab clones, is chosen for this very purpose, because its syntax is most compatible with Matlab and it is lightweight - very suited for ordinary users. Contact xguan@jnxtec.com for support. -
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DbViz produces plots of data contained in MySQL databases. Data can be viewed by looking at line graphs, xy scatter plots, and bar graphs. This greatly simplifies data analysis.
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FRIDA (flexible rapid interactive data analysis) is a generic program for manipulating, fitting, and plotting x,z,y data. It is primarily aimed at spectral analysis, especially in neutron scattering. Note: project has moved away from sf.net.
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IVuPy is a set of Python bindings for the Coin3D C++ class libraries which serve to create software for 3D visualization in science and engineering. IVuPy aims to be a solid basis for large Python programs for 3D visualization and data analysis.
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JARI (Just Another R Interface) is a comprehensive data science desktop suite engineered to guide researchers, students, and analysts through the entire data analysis lifecycle. By pairing a structured workflow with automated R code generation, JARI allows users to conduct rigorous statistical analysis without struggling with syntax—while keeping the full power of custom R scripting accessible for advanced users
