Open Source Python Data Analytics Tools
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Python Data Analytics Tools
View 265 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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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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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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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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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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Astropy
Repository for the Astropy core package
The Astropy Project is a community effort to develop a common core package for Astronomy in Python and foster an ecosystem of interoperable astronomy packages. Astropy is a Python library for use in astronomy. Learn Astropy provides a portal to all of the Astropy educational material through a single dynamically searchable web page. It allows you to filter tutorials by keywords, search for filters, and make search queries in tutorials and documentation simultaneously. The Anaconda Python Distribution includes Astropy and is the recommended way to install both Python and the Astropy package. The astropy package contains key functionality and common tools needed for performing astronomy and astrophysics with Python. It is at the core of the Astropy Project, which aims to enable the community to develop a robust ecosystem of affiliated packages covering a broad range of needs for astronomical research, data processing, and data analysis. -
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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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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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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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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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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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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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Larch: Data Analysis for X-ray Spectra
Data Processing and Analysis for X-ray Spectroscopy and More
Larch is a scientific data processing language that is designed to be easy to use for novices and complete enough for advanced data processing and analysis. Larch provides a wide range of functionality for dealing with arrays of scientific data, and basic tools to make it easy to use and organize complex data. Larch has been primarily developed for dealing with x-ray spectroscopic and scattering data, especially the kind of data collected at modern synchrotrons and x-ray sources. Larch is written in Python and relies heavily on the standard tools for scientific computing with Python (numpy, scipy, matplotlib, and h5py). -
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PAIDA is pure Python scientific analysis package and supports AIDA (Abstract Interfaces for Data Analysis). PAIDA can create/plot histograms and functions etc. The parameter optimization and its error evaluation are also supported. Can use with Jython!
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ThermV
Comprehensive thermal analysis software package
ThermV thermal analysis software package aims to provide the most sophisticated automatic analysis of thermal analysis data (TG/DTG, DTA and DSC). It offers new algorithm for concurrent peak deconvolution at different heating rates and provides full kinetic analysis of these data, including isoconversional methods for Ea, determination of reaction model and full kinetic triplet, Avrami coefficients, and dimensionality of crystal growth for reactions in the solid state. The project is currently in alpha stage, where individual modules will be provided for data analysis. The modules for peak deconvolution, peak profile analysis and determination of Ea and lnA will be provided first. Full GUI will be provided in beta stage. Due to computational limitations, the code is partly programmed in Python and partly in R. Python code will eventually be fully integrated into GUI. R code might remain standalone, although it will be integrated to a highest possible degree. Distributed under GPL -
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AI learning
AiLearning, data analysis plus machine learning practice
We actively respond to the Research Open Source Initiative (DOCX) . Open source today is not just open source, but datasets, models, tutorials, and experimental records. We are also exploring other categories of open source solutions and protocols. I hope you will understand this initiative, combine this initiative with your own interests, and do what you can. Everyone's tiny contributions, together, are the entire open source ecosystem. We are iBooker, a large open-source community, we-media, and online earning community, with a QQ group of more than 10,000 people and at least 10,000 subscribers. The number of Github Stars exceeds 60k, and it ranks in the top 100 of all Github organizations. The daily up of all its websites exceeds 4k, and the peak of Alexa ranking is 20k. Our core members are certified as CSDN blog experts and short-book programmers as excellent authors. We have established ApacheCN, a non-profit document, and tutorial translation project. -
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A collection of tools for working with the comparative data analysis ontology including import/export facilities for common phylogenetic file formats, and also a triple-store framework.
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CalPyLab is an open source data acquisition and (light) analysis software suite for scientific laboratories. The goal of this project is to provide a lightweight replacement for lab-view, to provide a quick and easy way to connect to your equipment.
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Collaborative Computing Project for NMR
Collaborative Computing Project for NMR (CCPN)
The Collaborative Computational Project for NMR (CCPN) provides tools and knowledge to maximise the impact of the biological NMR studies. The CCPN software facilitates data analysis and software integration. The project actively promotes the exchange of knowledge and provides training and best practices for the NMR community. CCPN also has a leading role in the development of a NMR data-sharing standard and coordination of NMR instrumentation proposals for RCUK and BIS. The 28 partners of CCPN jointly cover all aspects of biomolecular NMR and together they promote excellence in science in their respective fields. -
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Cookiecutter Data Science
Project structure for doing and sharing data science work
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work. When we think about data analysis, we often think just about the resulting reports, insights, or visualizations. While these end products are generally the main event, it's easy to focus on making the products look nice and ignore the quality of the code that generates them. Because these end products are created programmatically, code quality is still important! And we're not talking about bikeshedding the indentation aesthetics or pedantic formatting standards, ultimately, data science code quality is about correctness and reproducibility. It's no secret that good analyses are often the result of very scattershot and serendipitous explorations. Tentative experiments and rapidly testing approaches that might not work out are all part of the process for getting to the good stuff, and there is no magic bullet to turn data exploration into a simple, linear progression. -
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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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Data analysis for ADEXL
Create Excel reports from results of Cadence ADE-XL simulations
*** Required files from "Excel COM API for Python" project *** The scripts allows post processing of data saved in CSV format from "Detail - Transposed" view of ADE-XL -
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DataPrep
Python-based data preprocessing tool
DataPrep v0.2 is a Tkinter-based GUI application/tool designed to assist users in data preprocessing, multicollinearity removal, and feature selection for a wide range of applications in Cheminformatics, Bioinformatics, Data Analysis, Feature Selection, Molecular Modeling, Machine Learning, and Quantitative-structure-property relationship (QSPR) studies. It includes functionality to load, process, and save datasets with support for different preprocessing & multicollinearity removal strategies with customizable parameter setting options. -
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Electrophysiology & circular stats tools
Data analysis and circular statistics with OpenElectrophy and R
Set of tools for basic analysis of electrophysiological data. The Python classes show how to call OpenElectrophy functions and save data. The R library applies circular statistics to spike phase data and saves the best von Mises fit and the Rayleigh statistics on the disk. The wavelet coherence analysis is done in R by the package "sowas". Check the module R_coherence to see how we solved that problem. This packages may be useful for people who start using OpenElectrophy and circular statistics in R. If you find errors, please report them. The project is still in development, so in the future you'll get updates. -
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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. -
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MoDAVE aims at providing data analysis and visualization extensions to Mosaic datasets, including cubed sphere data, to the Climate Data Analysis Tools (CDATA) in particular.
