Open Source Data Analytics Tools - Page 12
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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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Novel Insight Scoring
Novel Insight Scoring is analytics software for scoring customers
Novel Insight Scoring is analytical CRM software for automatically scoring customers given example (scored) data. The user of the software can set optimization time and adjust risk level (pessimistic, neutral or optimistic scoring) and score new customers without detailed knowledge about data analysis and machine learning methods. The scoring results are stored in a CSV file for further processing and importing to databases etc. -
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Novembre
STM data analysis
A tool for visualisation and analysis of STM and STS results. Currently supports RHK, WinSPM, Nanonis and Createc file formats. Other formats can be added. Tools are made available by plugins and are currently focused on spectroscopy manipulation. -
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OME-3DR
3D cell reconstruction and quantitative analysis based on OME data
For big OME data analysis, we integrate commonly used quantitative methods, describe our novel strategies to quantify and analyze biological markers related to the cell or organelle spatial-coordinate model, and present open-source OME-3-Dimensional Reconstruction (OME-3DR), a flexible, programmable and batch-oriented tool based on OME data, for reconstructing 3-dimensional (3D) spatial conformations and conducting further analyses, such as the identification, counting, localization and tracking of bio-imaging markers, calculation of model-contour parameters for association analyses, establishing spatial-coordinate system, 3D co-localization analyses and so on. OME-3DR is well modularized (for automation, three main menus integrate hundreds of sub-functions), easy to use and ingenious; indeed, after setting the corresponding parameters, batch processing is relatively straightforward when beginning the 3D model reconstruction... -
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Open Cezeri Library
Effective Linear Algebra and Computer Vision Library with JAVA
OCL stands for Open Cezeri Library (yet another linear algebra and matrix library). This library provides rapid coding as matlab ease of use. To learn for library please try to use test examples at OpenCezeriLibrary\test\test. It is originally developed at el-cezeri laboratory of Siirt University, in order to establish generic framework of reusable components and software tools for machine vision, machine learning, AI and robotic applications. Currently, it holds following main concepts 1- Vision: It can access web cams, imaging source industrial cameras for manuel settings and advanced issues. Studies on accesing Leapmotion and Kinect is still under-development. 2- Machine learning: It uses Weka Software tool and some personel coded ML algorithms 3- CMatrix: Special matrix library called as CMatrix meaning Cezeri Maztrix Class. Actually it is regarded as the core of the OCL. CMatrix supports fluent interface and method chaining. -
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Open2Dprot is an open-source proteomics project for the development of bioinformatic tools for n-dimensional protein expression data analysis of quantified protein expression across multiple samples from research experiments.
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OpenData
Open source coronavirus 2019 sample application using open data
Open source software using open data with template code to demonstrate getting open government data such as the coronavirus 2019 (COVID-19). It takes data in feed format such as CSV, JSON, etc. to process maps, pie charts, line/bar graphs, HTML table that can be copied and pasted to spreadsheets such as Excel. The purpose is to provide template code to access open data readily available from official government websites useful for regional data analysis, latest information at a glance with data visualisation, etc. Sample includes region like Australia, Austria, Belgium, Brazil, Canada, Chile, Czechia, Denmark, Estonia, Europe, Finland, France, Germany, Greece, Hong Kong, Iceland, Indonesia, Ireland, Israel, Italy, Japan, Luxembourg, Macau, Malaysia, Netherlands, Norway, Korea, Philippines, Poland,Portugal,Qatar,Romania,Saudi Arabia,Singapore,Slovenia,Spain,Sweden,Switzerland,Taiwan,Thailand,United Kingdom,United States of America,etc. with various data such as face mask maps, and more. -
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OpenUnderwriter (Insurance Distribution)
Feature rich insurance quote & buy system for underwriters and brokers
OpenUnderwriter is an open source software house specialising in the development of IT solutions for the insurance market. Specialists in the areas of eBusiness and component based development, the team has developed technology for a number of major insurance companies. The OpenUnderwriter platform has been collaboratively developed by some of the best technical brains in the Insurance Industry and offers a viable alternative to traditional solutions. To date, OpenUnderwriter has been downloaded over 26,000 times in 30 countries. Our goal is simple, we are focused on enabling insurers and brokers to perform more effectively by providing a powerful, adaptable and robust open source insurance software toolset that removes the traditional barriers associated with insurance software adoption, including high cost of ownership, slow time to market and restrictive long term contracts. -
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OptiMIClass
Automatic n-dimensional data clustering tool powered by five advanced
This software is an automatic n-dimensional quantitative data clustering tool based on five optimization heuristics (GA, PSO, ACO, SA, and TS). It enables performance comparisons across heuristics and parameter testing within each method, analyzing solution quality, runtime, and convergence; it also includes a repository of benchmark test tables and an intuitive interface for research and operational use. It was developed by M.Sc. Jeffry Chavarría-Molina and M.Sc. Juan José Fallas-Monge at the Instituto Tecnológico de Costa Rica (TEC), School of Mathematics, with support from the Vice-Rectory for Research and Extension (VIE). The software was a direct outcome of “Combinatorial optimization heuristics for data classification” (Code: 5402-1440-3901), and its development continued within the related project “Disease propagation: heuristics applied to optimizing control measures” (Code: 540114404201). -
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PBEN_code
codes for data analysis in python
Collection of python codes for data analysis -
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PINCIS
PINCIS.pl is a Perl bioinf. script to analyze PICS data
PINCIS.pl (PIcs N-/C-terminal Inferred Substrates perl script) is a small, command line tool to designate and analyze PICS (Schilling et al., Nat. Protocols, 2011) data to gain the prime and non-prime site specificity of proteases. Thus, the script filters given peptide lists for library peptides (generated by the digestion protease in the proteomics workflow rather then the protease of interest) and prints out lists of inferred N- and C-terminal cleavage window extensions which can be concurrently used to generate cleavage specificity visualizations like the iceLogo (https://iomics.ugent.be/icelogoserver/create). -
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PL-DAS
Port Logistics Data Analysis System using Process Mining
This project is for analyzing operational data from container terminal, applying process mining and port logistics domain knowledge. This project is found by Total Soft Bank, Ltd. and Busan National University, based on ProM framework (http://www.promtools.org) which is also an open source project. This project is sponsored by NIPA (National IT Industry Promotion Agency), Korea. -
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Pandas Profiling
Create HTML profiling reports from pandas DataFrame objects
pandas-profiling generates profile reports from a pandas DataFrame. The pandas df.describe() function is handy yet a little basic for exploratory data analysis. pandas-profiling extends pandas DataFrame with df.profile_report(), which automatically generates a standardized univariate and multivariate report for data understanding. High correlation warnings, based on different correlation metrics (Spearman, Pearson, Kendall, Cramér’s V, Phik). Most common categories (uppercase, lowercase, separator), scripts (Latin, Cyrillic) and blocks (ASCII, Cyrilic). File sizes, creation dates, dimensions, indication of truncated images and existance of EXIF metadata. Mostly global details about the dataset (number of records, number of variables, overall missigness and duplicates, memory footprint). Comprehensive and automatic list of potential data quality issues (high correlation, skewness, uniformity, zeros, missing values, constant values, between others). -
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Parallel Colt is a multithreaded version of Colt - a library for high performance scientific computing in Java. It contains efficient algorithms for data analysis, linear algebra, multi-dimensional arrays, Fourier transforms, statistics and histogramming
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PivotTable.js
Open-source Javascript Pivot Table
PivotTable.js is a powerful JS library (originally CoffeeScript) that brings Excel-style pivot tables to the browser. Built atop jQuery and jQueryUI, it allows users to drag and drop fields into rows, columns, and aggregators to slice and summarize datasets. It also integrates with Python and R via modules like pivottablejs, making it versatile for data analysis across platforms. -
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Poli
An easy-to-use BI server built for SQL lovers. Power data analysis
An easy-to-use BI server built for SQL lovers. Power data analysis in SQL and gain faster business insights. Platform independent web application. Single JAR file + Single SQLite DB file. Get up and running in 5 minutes. PostgreSQL, Oracle, SQL Server, MySQL, Elasticsearch... You name it. No ETLs, no generated SQL, polish your own SQL query to transform data. Pixel-perfect positioning + Drag'n'Drop support to customize the reports and charts in your own way. Utilize the power of dynamic SQL with query variables to connect Filters and Charts. Capture the snapshot of historical data. Free up space in your own database. Three system level role configurations + Group based report access control. Custom the language pack and translations just for your audience. Auto refresh, drill through, fullscreen, embeds, color themes + more features in development. -
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PsiLAB is an environment for scientific research, numerical calculations and generic data analysis. It's written in the functional language O'CaML.
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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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PyNanoLab
data analysis and Visualization with matplotlib
PyNanoLab contains a variety of tools to complete the data analysis, statistics, curve fitting, and basic machine learning application. Visualization in pynanolab is based on matplotlib. The setup tools is desinged to control and set-up all the details of the figure with a GUI. -
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Pyclamp
A Python package used to extract and analyse electrophysiological data
Pyclamp is Python package used to extract and analyse electrophysiological data. A graphical user interface has been developed to allow a user to run the pack- age without requiring any knowledge of Python code. Presently, Pyclamp is designed to perform very specific forms of analysis on evoked synaptic responses: Data analysis (under development) : This is a highly user-interactive en-vironment that can be used to discriminate synaptic events, obtain various measures of their kinetics and size, and output the results. Quantal analysis : This part of the package performs simple variance-mean analysis and Bayesian quantal analysis to estimate the quantal sizea dn number of release sites among other measures. -
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Pyphant is a framework for scientific data analysis. It features a flexible plugin architecture allowing for the application in many different fields. For the analysis a graph of processing steps is constructed, that can be applied via the cli as well.
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Python Laboratory Operations Toolkit
many useful snippets for using python in a laboratory
A toolkit of Python software useful in a laboratory data acquisition and analysis environment. Includes support for such protocols as VXI-11 (and its extension, LXI), Vernier LabPro (now very old), and National Instruments DSTP (now very old). Also includes data analysis and modelling tidbits. Python3 updates are on the way in the very near future for the biggest packages. the vxi11 package is fully up-to-date, although see the blog post about python 3.13 -
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PythonStatsLab
A collection of useful statistical functions written in Python
There are functions for numerical integration of the standard normal probability distribution. They can be used to find probabilities, find z-alpha values, calculate confidence interval, etc. New functionality I wish to add are hypothesis testing and calculation of p-value, type I & II errors, etc. These functions would come in handy to anyone taking introductory or intermediate-level courses in probability, statistics and data analysis. There are several numerical integration techniques (Riemann sum, Simpson's method, Taylor expansion, etc.) that can be employed in this task, which I hope to add soon. Projected Future Improvements: -Estimation with 2 means -Student's t-distribution -Hart's algorithm for integrating CDF -
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QME-DEV Workbench (wxScipy) is a data analysis workbench based on Python, SciPy, Numpy and MatPlotLib(PyLab) and uses wxPython for the GUI. It can be used for non-linear analysis with a large set of experimental or generated data. Load/Acquire / Save/ Gr
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QSAS plug-ins
Plug-ins for the space physics data analysis software QSAS.
The project is concerned with developing new plug-ins for the space plasma analysis software QSAS. The plug-ins are developed mainly for the Cluster II mission, Champ and Swarm. QSAS can be downloaded from: http://www.sp.ph.ic.ac.uk/csc-web/QSAS/
