Python Statistics Software

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

  • Award-winning proxy networks, AI-powered web scrapers, and business-ready datasets for download.
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    Award-winning proxy networks, AI-powered web scrapers, and business-ready datasets for download.


    How the world collects public web data

    Bright Data is a leading data collection platform, enabling businesses to collect crucial structured and unstructured data from millions of websites through our proprietary technology. Our proxy networks give you access to sophisticated target sites using precise geo-targeting. You can also use our tools to unblock tough target sites, accomplish SERP-specific data collection tasks, manage and optimize your proxy performance as well as automating all of your data collection needs.
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  • Monitoring, Securing, Optimizing 3rd party scripts Icon
    Monitoring, Securing, Optimizing 3rd party scripts

    For developers looking for a solution to monitor, script, and optimize 3rd party scripts

    c/side is crawling many sites to get ahead of new attacks. c/side is the only fully autonomous detection tool for assessing 3rd party scripts. We do not rely purely on threat feed intel or easy to circumvent detections. We also use historical context and AI to review the payload and behavior of scripts.
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  • 1
    This program generates customizable hyper-surfaces (multi-dimensional input and output) and samples data from them to be used further as benchmark for response surface modeling tasks or optimization algorithms.
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  • 2
    1. Create an object-oriented python script that can represent mathematical concepts and their properties. 2. Represent all numeric values exactly. 3. Provide a variety of formats to export or embed representations of the mathematical concepts.
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  • 3
    MCPower

    MCPower

    MCPower — simple Monte Carlo power analysis for complex models

    MCPower-GUI is a desktop application that provides a graphical interface for the MCPower Monte Carlo power analysis library. It guides users through the full workflow across three tabs: Model setup (formula input with live parsing, CSV data upload with auto-detected variable types, effect size sliders, and correlation editing), Analysis configuration (find power for a given sample size or find the minimum sample size for a target power, with multiple testing correction and scenario analysis), and Results (interactive charts, exportable tables, and auto-generated Python replication scripts). Supports both standard linear models and mixed-effects models. Additional features include analysis history, configurable scenarios, and built-in documentation.
    Downloads: 0 This Week
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  • 4
    MRA

    MRA

    A general recommender system with basic models and MRA

    Multi-categorization Recommendation Adjusting (MRA) is to optimize the results of recommendation based on traditional(basic) recommendation models, through introducing objective category information and taking use of the feature that users always get the habits of preferring certain categories. Besides this, there are two advantages of this improved model: 1) it can be easily applied to any kind of existing recommendation models. And 2) a controller is set in this improved model to provide controllable adjustment range, which thereby makes it possible to provide optional modes of recommendation aiming different kinds of users.
    Downloads: 0 This Week
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  • Create and manage the email signature you need Icon
    Create and manage the email signature you need

    For companies and organizations that need an email signature solution

    With WiseStamp it’s easy to unify your brand and turn your emails into a powerful marketing tool. Get the most out of your emails with a professionally designed custom email signature.
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  • 5

    Noisy Channel Simulator

    Demonstrate errors in transmission of a file over a noisy channel.

    This program was written to dimonstrate errors in transmission for a presentation on Claude Shannon's Noisy Channel Coding Theorem. It takes an input file, the probability of a bit being flipped, and, if specified, the size of the header of the file. The program was intended to take monochrome bitmap files as input, so that each bit refers to a pixel in the image and thus, it would be easy to see errors in the output file, as some of the pixels would be flipped; however, it will work on any input file.
    Downloads: 0 This Week
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  • 6
    PaCal
    ProbAbilistic CALculator - a package for computing with probability distributions
    Downloads: 0 This Week
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  • 7
    PGAF provides a framework tuned, user-specific genetic algorithms by handling I/O, UI, and parallelism. It is designed for optimizing functions that take a "very long time" to evaluate.
    Downloads: 0 This Week
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  • 8
    PyMC

    PyMC

    Bayesian Modeling and Probabilistic Programming in Python

    PyMC is a Python library for probabilistic programming focused on Bayesian statistical modeling and machine learning. Built on top of computational tools like Aesara and NumPy, PyMC allows users to define models using intuitive syntax and perform inference using MCMC, variational inference, and other advanced algorithms. It’s widely used in scientific research, data science, and decision modeling.
    Downloads: 0 This Week
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  • 9
    Random

    Random

    Generation random numbers, words and elements

    The application supports Russian and English languages. An application for generating random numbers, words and selecting a random element from a list. The simple interface ensures fast and convenient user interaction. - Random numbers: generation is possible in any range. - Random words: the application's vocabulary is about 10,000 words and will increase in future versions. - Random element: the number of elements in the list is not limited, all have an equal probability of selection.
    Downloads: 0 This Week
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  • CloudZero: The Cloud Cost Optimization Platform Icon
    CloudZero: The Cloud Cost Optimization Platform

    CloudZero automates the collection, allocation, and analysis of your infrastructure and AI spend to uncover waste and improve unit economics.

    CloudZero is the leader in proactive cloud cost efficiency. We enable engineers to build cost-efficient software without slowing down innovation. CloudZero's next-generation cloud cost optimization platform automates the collection, allocation, and analysis of cloud costs to uncover savings opportunities and improve unit economics. We are the only platform that enables companies to understand 100% of their operational cloud spend and take an engineering-led approach to optimizing that spend. CloudZero is used by industry leaders worldwide, such as Coinbase, Klaviyo, Miro, Nubank, and Rapid7.
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  • 10
    SciEnPlot

    SciEnPlot

    Data Plotting and Analysis for Science and Engineering

    - Save and open a Work/Project (spf) file - Single fitting/ Batch fitting (user defined custom func) - Matrix to XYZ in Tool menu - Symbol plot: makers, curve, landscape, bar, etc. - Implemented a 3d surface plot (GLSurface) based on OpenGL (ScienPlot v1.3.2 and above) - ColorMap surface, trisurface, Pie, Polar plots, and 3D height field, 3dBar, scatter plots (under developing), and more - Column by column plotting/calculation - LaTex commands enclosed by $ symbols can be used for the labels in Graph - Accept txt(Text) and csv(Comma separated values) formatted data - Save, copy, print Graph - Use spread sheets to display data - Textboard to organize the results - Graphs in a publishable quality - Source codes based on: Python Numpy Scipy Matplotlib WxPython Visvis etc. - Special functions - Drag and drop data files - Python console is back (since v1.3.3), capable of reusing column data - Debye and Guinier models for SANS / SAX data - More apps in our Web below
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    Downloads: 0 This Week
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  • 11
    Software for speech research. It includes programs and libraries for signal processing, along with general purpose scientific libraries. Most of the code is in Python, with C/C++ supporting code. Also, contains code releases corresponding to publishe
    Downloads: 0 This Week
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  • 12
    Travel Market Simulator
    That project aims at studying and comparing typical airline IT methods, for instance RM-related algorithms. It works from a Unix/Linux/Mac command-line, and exposes basic APIs. It is being developed in C++, with Python wrappers for some components.
    Downloads: 0 This Week
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  • 13
    VAERity

    VAERity

    Uncovering truth in data

    VAERity is a free, open source tool to graphically explore the VAERS data set. It aims to eventually expand in scope to allow fast querying of arbitrary large datasets. It utilizes vaex and pandas as required to provide a balance of speed and query flexibility.
    Downloads: 0 This Week
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  • 14
    allink

    allink

    Software for data analysis, image processing, simulations, solver.

    Collection of utilities based on two basics classes: Matematica and VarData. Matematica) performs math operations on vectors and matrices for smoothing, interpolation, convolution, image processing... VarData) manipulate a structure of points connected by links. Addraw) openGL engine. ElPoly) analyze mechanical properties of polymer and membrane like structures. Addyn) perform molecular dynamics and Monte Carlo simulations and has a solver for 4th oder PDE. Avvis) perform all the operation of Matematica on different sets of data visualized on a Qt graphical interface. DrImage) image manipulation on the Matematica filters. The program is intended to use as less as possible external libs (optional: openGL, gsl, fftw, cgal, png, tiff, boost, MPI, Qt...).
    Downloads: 0 This Week
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  • 15

    dAnalytics

    dAnalytics is a software made for education in discriminant analysis.

    dAnalytics is a software made for educational purposes to work with discriminant analysis. It's a very simple calculator over bi-dimensional populations. You input a file with two columns (one for each variable) and tryout different separations of populations (blue and red) and analyze it's efficiency by observing the eigen value result for the attempted separation. It also gives many information about the statistics both of the input and the separated populations. There's a documentation folder in the software which brings a quick start guide for this software.
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  • 16

    fpyprog

    Program for statistic and visual analysis

    Example of program for statistic and visual analysis on Python
    Downloads: 0 This Week
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  • 17
    Python module to track the overall median of a stream of values "on-line" in reasonably efficient fashion.
    Downloads: 0 This Week
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  • 18

    minepy

    Maximal Information-based Nonparametric Exploration

    The minepy homepage has moved to http://minepy.readthedocs.io. The download page is now at https://github.com/minepy/minepy/releases.
    Downloads: 0 This Week
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  • 19
    mlpy

    mlpy

    Machine Learning Python

    mlpy is a Python module for Machine Learning built on top of NumPy/SciPy and of GSL. mlpy provides high-level functions and classes allowing, with few lines of code, the design of rich workflows for classification, regression, clustering and feature selection. mlpy is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License version 3. mlpy is available both for Python >=2.6 and Python 3.X.
    Downloads: 0 This Week
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  • 20
    Classic Texas Hold'Em Poker game in python.
    Downloads: 0 This Week
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  • 21

    portas

    Pequeno script em Python para provar o problema de Monty Hall

    O jogo consiste no seguinte: Monty Hall (o apresentador) apresentava 3 portas aos concorrentes, sabendo que atrás de uma delas está um carro (prémio bom) e que as outras têm prêmios de pouco valor. Na 1ª etapa o concorrente escolhe uma porta (que ainda não é aberta); De seguida Monty abre uma das outras duas portas que o concorrente não escolheu, sabendo à partida que o carro não se encontra aí; Agora com duas portas apenas para escolher — pois uma delas já se viu, na 2ª etapa, que não tinha o prêmio — e sabendo que o carro está atrás de uma delas, o concorrente tem que se decidir se permanece com a porta que escolheu no início do jogo e abre-a ou se muda para a outra porta que ainda está fechada para então a abrir. Qual é a estratégia mais lógica? Ficar com a porta escolhida inicialmente ou mudar de porta? Com qual das duas portas ainda fechadas o concorrente tem mais probabilidades de ganhar? Por quê?
    Downloads: 0 This Week
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  • 22
    PYthon RELiabilitY A python package implementing state-of-the-art numerical methods arising in the field of uncertainty quantification : from statistical inference to uncertainty propagation for various purposes.
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  • 23
    Implementation in Python of some of the statistical methods provided by "asurv", the survival analysis software.
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  • 24

    sequoia-dap

    SEQUOIA ocean data assimilation platform (a SIROCCO suite tool)

    ***** THIS PROJECT HAS MOVED TO https://gitlab.in2p3.fr/sirocco/sdap/sdap-dev ***** ***** THIS PROJECT HAS MOVED TO https://gitlab.in2p3.fr/sirocco/sdap/sdap-dev ***** ***** THIS PROJECT HAS MOVED TO https://gitlab.in2p3.fr/sirocco/sdap/sdap-dev ***** Within the SIROCCO suite of numerical tools, the purpose of SDAP is to provide a flexible platform to carry out multivariate assimilation of geophysical data in a numerical model. The program is multi-grid (finite differences or finite elements), multi-algebra (plug-in analysis kernels), multi-model (simple standardized interface). The program supports reduced-order data assimilation methods, as well as Ensemble assimilation approaches such as the Ensemble Kalman Filter. Recent additions include extensions towards simultaneous assimilation and downscaling (AMICO project), and a toolbox for ensemble assessment (SCRUM project).
    Downloads: 0 This Week
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  • 25

    slycat

    Web-based data science analysis and visualization platform.

    This is Slycat - a web-based data science analysis and visualization platform, created at Sandia National Laboratories. The goal of the Slycat project is to develop processes, tools and techniques to support data science, particularly analysis of large, high-dimensional data.
    Downloads: 0 This Week
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