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Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.
TTK - Topological Data Analysis and Visualization - Source Code
cell detection in calcium imaging recordings
Code and data used to create the examples in "Evidence-based Software Engineering based on the publicly available data"
High-performance Bayesian Data Analysis on the GPU in Clojure
High-assurance AI data visualization IDE & analytics workbench. Natural language to charts with local ground-truth table verification.
The foundational library of the Morpheus data science framework
Umbrella package of the 'spatstat' family................
CLI utility and Python module for analyzing log files and other data.
The power of Chart.js with Python
CASSIA: A Multi-Agent LLM-Based Single-Cell Cell Type Annotation Framework
daru-view is for easy and interactive plotting in web application & IRuby notebook. daru-view is a plugin gem to the existing daru gem.
A curated list of awesome Qlik extensions and resources for Qlik Sense and QlikView
Go's answer to pandas + scikit-learn: a batteries-included data analysis library with dataframes, statistics, machine learning, quant, and GPU acceleration. Run Python with seamless two-way variable sharing, or explore data straight from the Insyra CLI.
Turn CSV, Excel, and read-only databases into verified, editable business reports.
Quanfima (Quantitative Analysis of Fibrous Materials)
R COBOL DI (Data Integration) Package : Import COBOL CopyBook data files directly into R as properly structured data frames.
Run DuckDB inside Excel VBA: pandas-style analytics via in-process SQL + native C bridge. High-speed Range/Array ingestion, Parquet/CSV/JSON I/O.
A lightweight Python package for teaching computational methods through art history. Extract and analyze artist-specific works from WikiArt with built-in visualizations. Designed for digital humanities and computational design courses. Features genre/style analysis, matplotlib integration, and pedagogical clarity over algorithmic complexity.