Open Source Python Data Visualization Software

Python Data Visualization Software

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Browse free open source Python Data Visualization Software and projects below. Use the toggles on the left to filter open source Python Data Visualization Software by OS, license, language, programming language, and project status.

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  • 1
    Avogadro

    Avogadro

    An intuitive molecular editor and visualization tool

    Avogadro is an advanced molecular editor designed for cross-platform use in computational chemistry, molecular modeling, bioinformatics, materials science and related areas. It offers a flexible rendering framework and a powerful plugin architecture.
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    Downloads: 11,011 This Week
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  • 2
    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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    Downloads: 2,187 This Week
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  • 3
    FreeImage is a library project for developers who would like to support popular graphics image formats (PNG, JPEG, TIFF, BMP and others). Some highlights are: extremely simple in use, not limited to the local PC (unique FreeImageIO) and Plugin driven!
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    Downloads: 1,613 This Week
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  • 4
    Gwyddion

    Gwyddion

    Scanning probe microscopy data visualisation and analysis

    A data visualization and processing tool for scanning probe microscopy (SPM, i.e. AFM, STM, MFM, SNOM/NSOM, ...) and profilometry data, useful also for general image and 2D data analysis.
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    Downloads: 1,367 This Week
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    GMAT

    GMAT

    General Mission Analysis Tool

    The General Mission Analysis Tool (GMAT) is an open-source tool for space mission design and navigation. GMAT is developed by a team of NASA, private industry, and public and private contributors. The GMAT development team is pleased to announce the release of GMAT version R2025a. For a complete list of new features, compatibility changes, and bug fixes, see the R2025a Release Notes in the Users Guide.
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    Downloads: 1,228 This Week
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  • 6
    Orange Data Mining

    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.
    Downloads: 78 This Week
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  • 7
    dxf2gcode

    dxf2gcode

    DXF2GCODE: converting 2D dxf drawings to CNC machine compatible G-Code

    DXF2GCODE is a tool for converting 2D (dxf, pdf, ps) drawings to CNC machine compatible GCode. Windows, Linux, and Mac support by using python scripting language.
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    Downloads: 475 This Week
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  • 8
    The Timeline Project

    The Timeline Project

    Cross-platform app for displaying and navigating events on a timeline.

    The Timeline Project aims to create a free, cross-platform application for displaying and navigating events on a timeline.
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    Downloads: 211 This Week
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  • 9
    K-3D is the free (as in freedom) 3d modeling, animation, and rendering system.
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    Downloads: 185 This Week
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  • 10
    Asymptote

    Asymptote

    2D & 3D TeX-Aware Vector Graphics Language

    Asymptote is a powerful descriptive vector graphics language for technical drawing, inspired by MetaPost but with an improved C++-like syntax. Asymptote provides for figures the same high-quality typesetting that LaTeX does for scientific text.
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    Downloads: 145 This Week
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  • 11
    PyMca
    Stand-alone application and Python tools for interactive and/or batch processing analysis of X-Ray Fluorescence Spectra. Graphical user interface (GUI) and batch processing capabilities provided.
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    Downloads: 180 This Week
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  • 12
    TexGen
    TexGen is a geometric textile modelling software package to be used for obtaining engineering properties of woven textiles and textile composites. Citing TexGen We would be grateful if you could acknowledge use of TexGen where appropriate and suggest using one of the following references: L P Brown and A C Long. "Modelling the geometry of textile reinforcements for composites: TexGen", Chapter 8 in "Composite reinforcements for optimum performance (Second Edition)", ed. P Boisse, Woodhead Publishing Ltd, 2021, ISBN: 978-0-12-819005-0. https://doi.org/10.1016/B978-0-12-819005-0.00008-3 Lin, H., Brown, L. P. & Long, A. C. 2011. Modelling and Simulating Textile Structures using TexGen. Advanced Materials Research, 331, 44-47. To reference version 3.13.0 please use: Louise Brown, mike-matveev, & georgespackman. (2023). louisepb/TexGen: TexGen v3.13.1 (v3.13.1). Zenodo. https://doi.org/10.5281/zenodo.8221491
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    Downloads: 269 This Week
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  • 13
    matplotlib
    Matplotlib is a python library for making publication quality plots using a syntax familiar to MATLAB users. Matplotlib uses numpy for numerics. Output formats include PDF, Postscript, SVG, and PNG, as well as screen display. As of matplotlib version 1.5, we are no longer making file releases available on SourceForge. Please visit http://matplotlib.org/users/installing.html for help obtaining matplotlib.
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    Downloads: 126 This Week
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  • 14
    LabPlot

    LabPlot

    Data Visualization and Analysis

    LabPlot is a FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone.
    Downloads: 140 This Week
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  • 15
    XCSoar

    XCSoar

    ... the open-source glide computer

    XCSoar is a tactical glide computer for Android, Linux, macOS, and Windows.
    Downloads: 102 This Week
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  • 16

    PLplot

    Cross-platform, scientific graphics plotting library

    PLplot is a cross-platform, scientific graphics plotting library that supports math symbols and human languages (via UTF-8 user input strings); plot capabilities for multiple non-interactive plot file formats and in multiple interactive environments; and bindings for multiple computer languages.
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    Downloads: 78 This Week
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  • 17
    HEALPix

    HEALPix

    Data Analysis, Simulations and Visualization on the Sphere

    Software for pixelization, hierarchical indexation, synthesis, analysis, and visualization of data on the sphere. Please acknowledge HEALPix by quoting the web page http://healpix.sourceforge.net (or https://healpix.sourceforge.io) and publication: K.M. Gorski et al., 2005, Ap.J., 622, p.759 Full software documentation available at https://healpix.sourceforge.io/documentation.php Wiki Pages: https://sourceforge.net/p/healpix/wiki/Home Exchanging Data with HEALPix (in FITS files): https://sourceforge.net/p/healpix/wiki/Exchanging%20Data%20with%20HEALPix/ GDL and FL users should read https://sourceforge.net/p/healpix/wiki/HEALPix%20and%20GDL/
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    Downloads: 318 This Week
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  • 18
    Matplotlib

    Matplotlib

    matplotlib: plotting with Python

    Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things possible. Matplotlib ships with several add-on toolkits, including 3D plotting with mplot3d, axes helpers in axes_grid1 and axis helpers in axisartist. A large number of third party packages extend and build on Matplotlib functionality, including several higher-level plotting interfaces (seaborn, HoloViews, ggplot, ...), and a projection and mapping toolkit (Cartopy). Matplotlib is the brainchild of John Hunter (1968-2012), who, along with its many contributors, have put an immeasurable amount of time and effort into producing a piece of software utilized by thousands of scientists worldwide. Matplotlib is a Sponsored Project of NumFOCUS, a 501(c)(3) nonprofit charity in the United States. Matplotlib has support for visualizing information with a wide array of colors and colormaps.
    Downloads: 10 This Week
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  • 19
    Neuroglancer

    Neuroglancer

    WebGL-based viewer for volumetric data

    Neuroglancer is a WebGL-based visualization tool designed for exploring large-scale volumetric and neuroimaging datasets directly in the browser. It allows users to interactively view arbitrary 2D and 3D cross-sections of volumetric data alongside 3D meshes and skeleton models, enabling precise examination of neural structures and biological imaging results. Its multi-pane interface synchronizes multiple orthogonal views with a central 3D viewport, making it ideal for analyzing complex brain imaging data such as connectomics datasets. Neuroglancer operates entirely client-side, fetching data over HTTP in a variety of supported formats including Neuroglancer precomputed, N5, Zarr, and NIfTI, among others. The viewer is built with a multi-threaded architecture, separating rendering and data processing to ensure smooth performance even with massive datasets. Extensively used in neuroscience research, Neuroglancer supports integration with tools.
    Downloads: 8 This Week
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  • 20
    geemap

    geemap

    A Python package for interactive geospaital analysis and visualization

    A Python package for interactive geospatial analysis and visualization with Google Earth Engine. Geemap is a Python package for geospatial analysis and visualization with Google Earth Engine (GEE), which is a cloud computing platform with a multi-petabyte catalog of satellite imagery and geospatial datasets. During the past few years, GEE has become very popular in the geospatial community and it has empowered numerous environmental applications at local, regional, and global scales. GEE provides both JavaScript and Python APIs for making computational requests to the Earth Engine servers. Compared with the comprehensive documentation and interactive IDE (i.e., GEE JavaScript Code Editor) of the GEE JavaScript API, the GEE Python API has relatively little documentation and limited functionality for visualizing results interactively. The geemap Python package was created to fill this gap.
    Downloads: 8 This Week
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  • 21
    PanelCheck is an easy-to-use software tool for visualization of sensory profiling data using different types of plots. The joint information from the implemented plots provide detailed insight into assessor and panel performance.
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    Downloads: 167 This Week
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  • 22
    PyMOL Molecular Graphics System

    PyMOL Molecular Graphics System

    PyMOL is an OpenGL based molecular visualization system

    The Open-Source PyMOL repository has been moved to github: https://github.com/schrodinger/pymol-open-source We still use the pymol-users mailing list here on sourceforge. Please subscribe for community support: https://pymol.org/maillist (Note: SourceForge email newsletter and special offers are optional and can be unchecked) The PyMOL community wiki has its own home: https://pymolwiki.org/
    Downloads: 137 This Week
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  • 23
    Mercury

    Mercury

    Convert Python notebook to web app and share with non-technical users

    Turn Python notebooks to web applications with open-source Mercury framework. Hide code and add interactive widgets. Non-technical users can tweak widgets and execute notebook with new parameters. The core of Mercury is Open Source under AGPLv3. We provide Mercury Pro with additional features, dedicated support and friendly commercial license. Mercury is a perfect tool to convert Python notebook to interactive web application and share with non-programmers. You define interactive widgets for your notebook with the YAML header. Your users can change the widgets values, execute the notebook and save result (as PDF or html file). You can hide your code to not scare your (non-coding) collaborators. Easily deploy to any server. Mercury is dual-licensed. Looking for dedicated support, a commercial-friendly license, and more features? The Mercury Pro is for you.
    Downloads: 5 This Week
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  • 24
    folium

    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.
    Downloads: 5 This Week
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  • 25
    seaborn

    seaborn

    Statistical data visualization in Python

    Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. Seaborn helps you explore and understand your data. Its plotting functions operate on dataframes and arrays containing whole datasets and internally perform the necessary semantic mapping and statistical aggregation to produce informative plots. Its dataset-oriented, declarative API lets you focus on what the different elements of your plots mean, rather than on the details of how to draw them. Behind the scenes, seaborn uses matplotlib to draw its plots. For interactive work, it’s recommended to use a Jupyter/IPython interface in matplotlib mode, or else you’ll have to call matplotlib.pyplot.show() when you want to see the plot.
    Downloads: 5 This Week
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