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59 search results found

Miller ⭐ 8,397

Miller is like awk, sed, cut, join, and sort for name-indexed data such as CSV, TSV, and tabular JSON

Git Quick Stats ⭐ 6,012

▁▅▆▃▅ Git quick statistics is a simple and efficient way to access various statistics in git repository.

Tablesaw ⭐ 3,328

Java dataframe and visualization library

Gitinspector ⭐ 2,295

📊 The statistical analysis tool for git repositories

Multi-class confusion matrix library in Python

Scikit Posthocs ⭐ 307

Multiple Pairwise Comparisons (Post Hoc) Tests in Python

Morpheus Core ⭐ 239

The foundational library of the Morpheus data science framework

Open-source Python library for statistical analysis of randomised control trials (A/B tests)

Ee Outliers ⭐ 204

Open-source framework to detect outliers in Elasticsearch events

Data Science Toolkit ⭐ 185

Collection of stats, modeling, and data science tools in Python and R.

A package for statistically rigorous scientific discovery using machine learning. Implements prediction-powered inference.

A collection of statistical analysis tools for your Swift programs.

Ciencia De Dados Projetos ⭐ 55

Repositório para meus projetos de ciência de dados (Web scraping e automação + análise exploratória de dados + machine learning + sistema de recomendação)

Pyautofit ⭐ 54

PyAutoFit: Classy Probabilistic Programming

Mplus.subcreation.net ⭐ 51

source code for the Mythic+ statistics website mplus.subcreation.net

Metanumerics ⭐ 50

Meta.Numerics is library for advanced numerical computing on the .NET platform. It offers an object-oriented API for statistical analysis, advanced functions, Fourier transforms, numerical integration and optimization, and matrix algebra.

Kernel Density Estimation and (re)sampling

Survey.jl ⭐ 47

Analysis of complex surveys

A Toolkit for Interactive Statistical Data Visualization

Official ID2T repository. ID2T creates labeled IT network datasets that contain user defined synthetic attacks.

Instant stats for any fantasy football league.

An introductory statistics course for social scientists, using Stata

Powershell Statistics ⭐ 33

Statistical analysis of data on the command line

Introductiontostats ⭐ 32

Refresher training course on the foundations of statistical analysis. http://tinyurl.com/cruk-stats

Complete Data Science Roadmap ⭐ 29

Complete Roadmap For Data Science

Wink Statistics ⭐ 27

Fast & numerically stable statistical analysis

Kalmanpy ⭐ 27

Implementation of Kalman Filter in Python

Kitsu Season Trends ⭐ 21

🦊 Kitsu seasonal anime trends

Experimentaldesign.jl ⭐ 20

Design of Experiments in Julia

Mean Median Mode Calculator ⭐ 19

Free WordPress Plugin: Calculator for mean, median, and mode in statistics. Use this calculator to get the mean, median, mode, range, and the average for any data set. www.calculator.io/mean-median-mode-calculator/

Mcmcdiagnostictools.jl ⭐ 19

Binninganalysis.jl ⭐ 18

Statistical standard error estimation tools for correlated data

This Chrome Extension automatically performs SRM checks and flags potential data quality issues on supported experimentation platforms.

Conjugate ⭐ 15

Bayesian Conjugate Models in Python

Data Scientist In Python ⭐ 15

This repository contains notes and projects of Data scientist track from dataquest course work.

R - Fetch, build and deploy.

Analysis With Programming ⭐ 13

Repository of My Old Blog

Correlationmatrix ⭐ 13

correlationMatrix is a Python powered library for the statistical analysis and visualization of correlations

Spotifystatistics ⭐ 12

Personalized stats for your Spotify profile.

Statlysis ⭐ 12

Statistical & Analysis in Ruby DSL

Multiple linear regression with statistical inference, residual analysis, direct CSV loading, and other features

Whatscloud ⭐ 10

WhatsCloud is an android app which allows you to analyze your WhatsApp chat history on the fly with only one click

Est Computacional 2019 ⭐ 10

Class notes for the computational statistics class (Spanish), master in Data Science ITAM

Statistics ⭐ 10

A Crystal shard to perform descriptive statistics and sampling on popular distributions

Python Stats Dataviz ⭐ 9

Course materials for UMBC DATA 690 - Statistical Analysis and Data Visualization with Python.

Statistics For Data Science ⭐ 8

Learning Statistics is one of the most Important step to get into the World of Data Science and Machine Learning. Statistics helps us to know data in a much better way and explains the behavior of the data based upon certain factors. It has many Elements which help us to understand the data better that includes Probability, Distributions, Descriptive Analysis, Inferential Analysis, Comparative Analysis, Chi-Square Test, T Test, Z test, AB Testing etc.

Wilson Interval ⭐ 8

A comprehensive module used to calculate the high bound, low bound, and center of a Wilson score interval.

Shinybrms ⭐ 7

An R package providing a GUI ('shiny' app) for the R package 'brms'.

Taylor moment expansion in Python (JaX and SymPy) and Matlab

Sparklyr.flint ⭐ 7

Sparklyr extension making Flint time series library functionalities (https://github.com/twosigma/flint) easily accessible through R

Pykelihood ⭐ 7

package useful for likelihood-based inference

Risk_calculation_using_backward_elimination_algorithm_in_life_insurance ⭐ 6

Implementation of backward elimination algorithm used for dimensionality reduction for improving the performance of risk calculation in life insurance industry.

A JavaScript module for generating random seeded distributions and its statistical analysis.

Community Atmospheric Model Post-Processing System

Specification language for generating Generalized Linear Models (with or without mixed effects) from conceptual models

Ratpmetro ⭐ 5

Statistical analysis of incident probability and causes on RATP metro/RER lines

Hyperbolicfitdll ⭐ 5

This is an open source library that can be used to autofocus telescopes. It uses a novel algorithm based on robust statistics. For a preprint, see https://arxiv.org/abs/2201.12466 .The library is currently used in Astro Photography tool (APT) https://www.astrophotography.app/

Statistics For Data Science Using Python ⭐ 5

Using Python, learn statistical and probabilistic approaches to understand and gain insights from data. Learn statistical concepts that are very important to Data science domain and its application using Python. Learn about Numpy, Pandas Data Frame.

Spatstat.data ⭐ 5

Sub-package of spatstat containing all datasets

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