Open Source Mac Data Visualization Software - Page 11
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Data Visualization Software for Mac
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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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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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gt R
Easily generate information-rich, publication-quality tables from R
With the gt package, anyone can make wonderful-looking tables using the R programming language. The gt philosophy: we can construct a wide variety of useful tables with a cohesive set of table parts. These include the table header, the stub, the column labels and spanner column labels, the table body, and the table footer. It all begins with table data (be it a tibble or a data frame). You then decide how to compose your gt table with the elements and formatting you need for the task at hand. Finally, the table is rendered by printing it at the console, including it in an R Markdown document, or exporting it to a file using gtsave(). Currently, gt supports the HTML, LaTeX, and RTF output formats. -
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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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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. -
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missingno
Missing data visualization module for Python
Messy datasets? Missing values? missingno provides a small toolset of flexible and easy-to-use missing data visualizations and utilities that allows you to get a quick visual summary of the completeness (or lack thereof) of your dataset. Just pip install missingno to get started. This quickstart uses a sample of the NYPD Motor Vehicle Collisions Dataset dataset. The msno.matrix nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion. At a glance, date, time, the distribution of injuries, and the contribution factor of the first vehicle appear to be completely populated, while geographic information seems mostly complete, but spottier. The sparkline at right summarizes the general shape of the data completeness and points out the rows with the maximum and minimum nullity in the dataset. This visualization will comfortably accommodate up to 50 labelled variables. -
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nb-clean
Clean Jupyter notebooks of outputs, metadata, and empty cells
nb-clean cleans Jupyter notebooks of cell execution counts, metadata, outputs, and (optionally) empty cells, preparing them for committing to version control. It provides both a Git filter and pre-commit hook to automatically clean notebooks before they're staged, and can also be used with other version control systems, as a command line tool, and as a Python library. It can determine if a notebook is clean or not, which can be used as a check in your continuous integration pipelines. nb-clean can also be used as a pre-commit hook. You may prefer this to the Git filter if your project already uses the pre-commit framework. Note that the Git filter and pre-commit hook work differently, with different effects on your working directory. The pre-commit hook operates on the notebook on disk, cleaning the copy in your working directory. The Git filter cleans notebooks as they are added to the index, leaving the copy in your working directory dirty. -
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pprof
pprof is a tool for visualization and analysis of profiling data
pprof is a profiling visualization and analysis tool that ingests profiles in the profile.proto format and generates human-readable and graph-based reports. It supports multiple profile types (CPU, heap, allocations, contention, etc.) and can present data as text tables, call graphs (via Graphviz/dot), flame graphs, and interactive web UIs. The tool helps developers find hot paths, quantify resource usage, and compare profiles across runs to validate performance changes. It is widely used in Go but also has bindings and exporters for other ecosystems, and the repository includes a Go package for reading and writing profiles programmatically. The pprof command can operate on local files or fetch from targets exposing profiling endpoints, supporting iterative, production-oriented workflows. Its design and proto schema make it a lingua franca for profilers that want to interoperate across languages and runtimes. -
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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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xeogl
A WebGL-based 3D engine for technical visualization
xeogl is an open source JavaScript library from xeolabs for 3D model visualization on WebGL. It gives you tools to create interactive 3D worlds in your browser. Load models from formats like glTF or OBJ, or generate them programmatically. Navigate them with the camera and script them with Javascript, to build compelling 3D presentations. Load multiple models. Isolate/move/emphasize objects. Camera navigation controls. Camera animations (flyto, follow, path etc). Emphasis effects (wireframe, ghost, highlight, outline). Annotations. Cross-section views. Scene object hierarchies. Transform hierarchies. Bounding volumes. 3D picking, raycasting. Screen capture. You can dynamically edit most things in your scene at runtime. Animate your scenes by updating the properties of their components. Load 3D models into your scene from glTF. -
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VR Juggler is a virtual platform for virtual reality application development created at the Virtual Reality Applications Center at Iowa State University. Applications developed in VR Juggler can transparently move between a wide range of VR systems.
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TinkerCell is a software for synthetic biology. The visual interface allows users to design networks using various biological "parts". Models can include modules and multiple cells. Users can program new functions using C or Python. www.tinkercell.
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libPGF
libPGF is an implementation of the Progressive Graphics File (PGF)
The Progressive Graphics File (PGF) is an efficient image file format, that is based on a fast, discrete wavelet transform with progressive coding features. PGF can be used for lossless and lossy compression. It's most suitable for natural images. PGF can be used as a very efficient and fast replacement of JPEG 2000. -
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42
Simulation for spacecraft attitude control system analysis and design
42 is a comprehensive general-purpose simulation of spacecraft attitude and orbit dynamics. Its primary purpose is to support design and validation of attitude control systems, from concept studies through integration and test. 42 accurately models multi-body spacecraft attitude dynamics (with rigid and/or flexible bodies), and both two-body and three-body orbital flight regimes, modelling environments from low Earth orbit to throughout the solar system. 42 simulates multiple spacecraft concurrently, facilitating studies of rendezvous, proximity operations, and precision formation flying. It also features visualization of spacecraft attitude. -
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Java Universal Network/Graph Framework
Java graph/network library
JUNG provides a common and extendible language for the modeling, analysis, and visualization of data that can be represented as a graph or network. New version now available on GitHub: https://github.com/jrtom/jung/releases/tag/jung-2.1 -
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FCOLLADA based COLLADA plugins for Maya and 3DSMax. Newer plugins with 1.5 support and support the files mentioned in "Papervision3D Essentials" by Paul Tondeur are available at http://opencollada.org . Please use this project for FCOLLADA related topi
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OVATION Prime
Seasonal model of the diffuse, monoenergetic, proton, and wave aurora.
OVATION Prime is a seasonal model of the diffuse, monoenergetic, proton, and wave aurora. The OVATION Prime model is written in IDL and was developed at the Johns Hopkins Applied Physics Laboratory (JHU-APL) by Patrick Newell and co-workers. This current version includes updates to the retrospective and real time components, several efficiency enhancements and a user configuration as implemented by Rob Redmon and Janet Machol of NOAA. This is a community model. Users are invited to suggest and provide improvements. Documentation includes a model description and instructions for running the software. The README is available here: http://sourceforge.net/p/ovation-prime/code/HEAD/tree/trunk/README.pdf?format=raw A web interface for running the model for historical periods is available here: http://sd-www.jhuapl.edu/Aurora/ovation_prime/prime_display.html Realtime versions are running here: http://www.ngdc.noaa.gov/stp/ovation_prime/ http://www.swpc.noaa.gov/ovation/ -
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Mantid Project (www.mantidproject.org)
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This site hosts the source code for C++ version of the Broker for SBW, NOM module, advanced simulation suite, analysis applications and model editors.
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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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The repository was moved to GitHub https://github.com/htrb/ngraph-gtk User's manual https://htrb.github.io/ngraph-gtk/manual/ Japanese web page https://htrb.github.io/homepage/ngraph/ngraph-gtk.html
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Panini is a visual tool for creating perspective views from panoramic and wide angle photographs. More than a pano viewer, more than a view camera, with features of both. For Linux/Unix, Win32, and Mac systems with OpenGL 2.0 + Nov. 2017: now hosted at https://github.com/lazarus-pkgs/panini
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GeomSpace
Interactive geometry software for Euclidean and non-Euclidean spaces
GeomSpace is interactive geometry software for different geometric spaces. You can build your own universe of any dimension and with any geometry. You can choose Euclidean, elliptic, hyperbolic, Galilean, Minkowskii, de Sitter among other spaces. -
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The FAKE GAME tool uses natural evolution to evolve Data Mining models. It incorporates several preprocessing, optimization and visualization methods aimed to streamline the Knowledge Discovery process. Knowledge Extraction from data is being automated!
