Open Source Python Data Analytics Tools
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Python Data Analytics Tools
View 261 business solutionsBrowse free open source Python Data Analytics Tools and projects below. Use the toggles on the left to filter open source Python Data Analytics Tools by OS, license, language, programming language, and project status.
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Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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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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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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pandas
Fast, flexible and powerful Python data analysis toolkit
pandas is a Python data analysis library that provides high-performance, user friendly data structures and data analysis tools for the Python programming language. It enables you to carry out entire data analysis workflows in Python without having to switch to a more domain specific language. With pandas, performance, productivity and collaboration in doing data analysis in Python can significantly increase. pandas is continuously being developed to be a fundamental high-level building block for doing practical, real world data analysis in Python, as well as powerful and flexible open source data analysis/ manipulation tool for any language. -
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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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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/ -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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scikit-learn
Machine learning in Python
scikit-learn is an open source Python module for machine learning built on NumPy, SciPy and matplotlib. It offers simple and efficient tools for predictive data analysis and is reusable in various contexts. -
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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. -
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AUR Malware Check
Detection tools for the June 2026 atomic-lockfile AUR supply-chain
AUR Malware Check is a community repository for detecting exposure to the June 2026 atomic-lockfile supply-chain attack against the Arch User Repository. It collects scattered indicators, affected package lists, and detection scripts into one place for easier review and contribution. The project helps users compare installed AUR packages against known compromised package lists. It also includes checks for related package-manager cache artifacts and supports broader historical scans through pacman logs. The repository provides shell-based tooling, a Python 3.14+ implementation, consolidated indicators, source notes, and testable detection resources. It is useful for Arch users, maintainers, and incident responders who need a focused way to investigate possible local exposure. -
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Python for Data Analysis
Materials and IPython notebooks for "Python for Data Analysis"
Python for Data Analysis is the official companion repository for Python for Data Analysis, 3rd Edition by Wes McKinney. It contains the datasets, examples, and IPython notebooks used throughout the book. The repository helps readers practice Python data analysis concepts directly in Jupyter Notebook. Its chapters cover Python basics, NumPy, pandas, data loading, cleaning, wrangling, visualization, time series, modeling libraries, and full analysis examples. The project includes setup options using uv or Conda, with dependency files to reproduce the working environment. It is best suited for learners, analysts, and developers who want hands-on practice with the modern Python data stack. -
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Dash
Build beautiful web-based analytic apps, no JavaScript required
Dash is a Python framework for building beautiful analytical web applications without any JavaScript. Built on top of Plotly.js, React and Flask, Dash easily achieves what an entire team of designers and engineers normally would. It ties modern UI controls and displays such as dropdown menus, sliders and graphs directly to your analytical Python code, and creates exceptional, interactive analytics apps. Dash apps are very lightweight, requiring only a limited number of lines of Python or R code; and every aesthetic element can be customized and rendered in the web. It’s also not just for dashboards. You have full control over the look and feel of your apps, so you can style them to look any way you want. -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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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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LaueTools
open source python packages for X-ray MicroLaue Diffraction analysis
LaueTools is an open-source project for white beam Laue x-ray microdiffraction data analysis including tools in image processing, peaks searching & indexing, crystal structure solving (orientation & strain) and data & grain mapping visualisation. Python 3 Code and new features are now at: https://gitlab.esrf.fr/micha/lauetools -
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relax
Molecular dynamics by NMR data analysis
The software package 'relax' is designed for the study of molecular dynamics through the analysis of experimental NMR data. Organic molecules, proteins, RNA, DNA, sugars, and other biomolecules are all supported. It supports exponential curve fitting for the calculation of the R1 and R2 relaxation rates, calculation of the NOE, reduced spectral density mapping, the Lipari and Szabo model-free analysis, study of domain motions via the N-state model and frame order dynamics theories using anisotropic NMR parameters such as RDCs and PCSs, the investigation of stereochemistry in dynamic ensembles, and the analysis of relaxation dispersion data. -
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FreeSEM
Free and open-source desktop application designed for SEM
FreeSEM is a free, open-source desktop application designed for researchers and students to perform Structural Equation Modeling (SEM) for statistical and research analysis. It allows users to visually build models using a drag-and-drop interface to create path diagrams and analyze relationships between observed and latent variables. The software supports methods such as exploratory factor analysis, covariance-based SEM, partial least squares SEM, and meta-SEM, and it provides model fit statistics like CFI, TLI, RMSEA, SRMR, and chi-square to evaluate models. It also enables exporting analysis results and reports to formats like Word, Excel, CSV, and PDF, making it useful for academic research and data analysis workflows. -
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GXSM
Scanning Probe Microscopy Controller and Data Visualization Software
GXSM -- Gnome X Scanning Microscopy: A multi-channel image and vector-probe data acquisition and visualization system designed for SPM techniques (STM,AFM..), but also SPA-LEED/LEED/LEEM data analysis. A plug-in interface allows any user add-on data-processing and special hardware and instrument support. Latest: NC-AFM and related explorative methods as SQDM can be configured. High-Speed external PAC-PLL hardware option with digital DSP link. Based on several hardware options it supports a commercially available DSP hardware and provided also Open Source Code for all the low level signal processing tasks and instrument controls in a most flexible and adaptable manner. All latest software is available via github.com/pyzahl/Gxsm4 (source code) or as binary for Ubuntu on https://launchpad.net/~totto/+archive/ubuntu/gxsm -
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SCaVis
Scientific Computation and Visualization Environment
SCaVis is an environment for scientific computation, data analysis and data visualization for scientists, engineers and students. The program is fully multiplatform (100% Java) and integrated with Java and a number of scripting languages: Jython (Python), Groovy, JRuby, BeanShell. SCaVis 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. Elements of symbolic computations using Octave/Matlab scripting are supported. The project was migrated to DataMelt. -
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Crystalsim - XRD hkl simulation
X-ray diffraction (XRD) analysis for hkl simulation of any crystal.
Crystalsim is a simple freeware program with a neat graphical user interface for X-ray diffraction (XRD) data analysis . It can simulates all possible {hkl} planes data for the selected crystal. Crystallographic Information File (.cif) can also be used. Analyze both powder diffraction and single crystal data . Indexed at International Union of Crystallography (IUCR). Crystalline lattice parameters such as ‘a’, ‘b’, ‘c’ as well as interfacial angles such as alpha, beta, gamma can also be entered manually. Processed data can be saved as .csv file format. Designed by M Kanagasabapathy, Associate Professor, Department of Chemistry, Rajus' College, Affiliated to Madurai Kamaraj University Rajapalayam (TN) India email: rrcmks(at)gmail.com -
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Uranie
Uranie is CEA's uncertainty analysis platform, based on ROOT
Uranie is a sensitivity and uncertainty analysis plateform based on the ROOT framework (http://root.cern.ch) . It is developed at CEA, the French Atomic Energy Commission (http://www.cea.fr). It provides various tools for: - data analysis - sampling - statistical modeling - optimisation - sensitivity analysis - uncertainty analysis - running code on high performance computers - etc. Thanks to ROOT, it is easily scriptable in CINT (c++ like syntax) and Python. Is is available both for Unix and Windows platforms (a dedicated platform archive is available on request). Note : if you have downloaded version 3.12 before the 8th of february, a patch exists for a minor bug on TOutputFileKey file, don't hesitate to ask us. -
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This is a sophisticated & integrated simulation and analysis environment for dynamical systems models of physical systems (ODEs, DAEs, maps, and hybrid systems). It supports symbolic math, optimization, continuation, data analysis, biological apps...
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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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DSTK - DataScience ToolKit
DSTK - DataScience ToolKit for All of Us
DSTK - DataScience ToolKit is an opensource free software for statistical analysis, data visualization, text analysis, and predictive analytics. Newer version and smaller file size can be found at: https://sourceforge.net/projects/dstk3/ It is designed to be straight forward and easy to use, and familar to SPSS user. While JASP offers more statistical features, DSTK tends to be a broad solution workbench, including text analysis and predictive analytics features. Of course you may specify JASP for advanced data editing and RapidMiner for advanced prediction modeling. DSTK is written in C#, Java and Python to interface with R, NLTK, and Weka. It can be expanded with plugins using R Scripts. We have also created plugins for more statistical functions, and Big Data Analytics with Microsoft Azure HDInsights (Spark Server) with Livy. License: R, RStudio, NLTK, SciPy, SKLearn, MatPlotLib, Weka, ... each has their own licenses. -
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Pathomx
Workflow-based data analysis built on IPython
Pathomx is a workflow-based tool for the analysis and visualisation of experimental data. Initially created as a tool for metabolomic data analysis is has been extended and can now be used for any scientific and non-scientific data analysis. -
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xrayutilities
a package with useful scripts for X-ray diffraction physicists
xrayutilities is a python package used to analyze x-ray diffraction data. It can support with performing diffraction experiments and used for common steps in the data analysis. It can read experimental data from several data formats (spec, edf, xrdml, ...); convert them to reciprocal space for arbitrary goniometer geometries and different detector systems (point, linear as well as area detectors); for further processing the data can be gridded (transformed to a regular grid). More detailed description as well as documentation can be found at webpage http://xrayutilities.sourceforge.io/. Downloads for windows can be found on http://pypi.python.org/pypi/xrayutilities Development is performed on github: https://github.com/dkriegner/xrayutilities -
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CorNetMap
A tool for Gene Expression Correlation Network
Capabilities of CorNetMap: 1. Read data as tab-delimited text file. Can be used for analysis of any data set beyond gene expression. 2. Capable of both two-dimensional and multidimensional data analysis. 3. Calculate Pearson correlation and cross-correlation for analysis data with phase difference. 4. Generate correlation Heat-map and draws network map. 5. Save correlation data as text file. How to use and doccumentation: https://sourceforge.net/projects/cornetmap/files/Documentation_corNetMap.pdf Sample data for testing: https://sourceforge.net/projects/cornetmap/files/Test%20Data/ Citation: Cite CornetMap as " Khaund, A. Bose, B. CorNetMap. https://sourceforge.net/projects/cornetmap " Credit: Abhigyan Khaund, Biplab Bose, IIT Guwahati -
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ExAM-Exome_Analysis_And_Mining
A whole exome sequencing analysis package and its graphical interface
During the past few years, whole exome sequencing has imposed itself for genetic research, largely due to its use for detection of causative mutations responsible for Mendelian disorders. As a consequence of their power and of the rapidly decreasing cost of these technologies, massive amount of exome sequencing data are generated and becoming available to a broadening community of scientists. However, these data remain difficult to analyze and interpret by the general scientific community, due to the limited bioinformatics resources that are currently freely available for their analysis and the partial information that they provide. Here, we present an interactive and free analysis package, ExAM, dedicated to whole exome sequencing data analysis. It is accessible to non-computer scientists and provides a complete set of information, as well as decision support to prioritize candidate disease causing variants. -
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GUI for DEDA
GUI for DEmography Data Analysis
<This project has been completely rewrote and transformed into a new one: https://sourceforge.net/projects/deday/. 2013/06/26> The graphic user interface for DEDA (DEmography Data Analysis), a scientific software package fitting survivalship data to a number of distributions using maximum likelihood (ML) method. Currently, Weibull (2p), Gompertz and Gompertz-Makeham are supported. IMPORTANT NOTICE: Only the GUI is provided here. In order to perform the analysis, one also need the DEDA computation core program. Please email a request to me, entitled: 'Request for DEDA computation core', if you wish to have a copy.
