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A curated list of awesome R packages, frameworks, and software for data science and statistical computing.
A curated list of awesome R packages, frameworks, and software for data science and statistical computing.
A fast, powerful, and intuitive desktop application for visualizing and analyzing time series data from files, streams, and robotics systems.
Voilà converts Jupyter notebooks into secure, standalone web applications with interactive widgets.
A curated collection of Python tutorials and resources for data science, machine learning, and natural language processing.
A CLI tool and dataflow engine that lets you query and join data from multiple databases and file formats using SQL.
A curated list of open-source geospatial analysis tools, libraries, and resources across multiple programming languages and domains.
A grammar of data manipulation for R, providing a consistent set of verbs to solve common data manipulation challenges.
An integrated development environment (IDE) for the R programming language with a comprehensive workbench and server capabilities.
A C++ graphics library for data visualization with interactive plotting, high-quality export, and dozens of plot categories.
A Python library for easy database interaction with automatic table creation, bulk loading, and transaction support.
An open platform for deploying and using language agents for data analysis, plugin automation, and web browsing.
A Rails engine for business intelligence that lets you explore data with SQL, create charts and dashboards, and share insights with your team.
A Python implementation of a grammar of graphics for creating complex and beautiful statistical plots.
An open-source augmented analytics platform that automates exploratory data analysis and visualization with AI-powered insights.
A curated collection of Python libraries, tutorials, and tools for data science, from data wrangling to machine learning and visualization.
An open-source intelligence (OSINT) tool for crawling and analyzing websites on the dark web and beyond.
A modular quantitative finance framework for data collection, analysis, strategy backtesting, and machine learning across multiple markets.
A Python library for visualizing missing data in pandas DataFrames using matrix, bar, heatmap, and dendrogram plots.
A Python package for working with labeled multi-dimensional arrays, inspired by pandas and tailored for scientific data.
Course materials for the Johns Hopkins Data Science Specialization on Coursera.
Course materials for the Johns Hopkins Data Science Specialization on Coursera.
A high-performance R package for fast data manipulation of large datasets, extending data.frame with concise syntax and memory efficiency.
A command-line tool for running SQL queries against JSON, CSV, Excel, Parquet, and other structured data files.
A Java dataframe and visualization library for data loading, cleaning, transformation, and analysis.
An open-source numerical library for .NET and Mono providing algorithms for scientific computing, linear algebra, statistics, and more.
A blazing-fast command-line toolkit for querying, slicing, analyzing, transforming, and validating tabular data (CSV, Excel, JSONL, etc.).
A lightweight, dependency-free JavaScript library for descriptive, regression, and inference statistics.
A curated list of Python software for data science, covering machine learning, deep learning, visualization, and data manipulation.
A Python framework for developing and backtesting algorithmic trading strategies with machine learning.
A numerical processing library for Scala, providing generic, clean, and powerful linear algebra and scientific computing capabilities.
A central hub for sharing, refining, and reusing code for analyzing the MIMIC family of critical care and hospital databases.
A Go library providing DataFrames, Series, and data wrangling operations for structured data manipulation.
A Go library providing DataFrames, Series, and data wrangling operations for tabular data manipulation.
A WebGPU-accelerated TypeScript charting library for rendering millions of data points at 60 FPS with interactive dashboards.
A Python library for automated exploratory data analysis (EDA) with high-density visualizations and target analysis in two lines of code.
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