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DuckDB is an analytical in-process SQL database management system. It is a high-performance analytical database system designed to be fast, reliable, portable and easy to use, with a rich SQL dialect supporting nested correlated subqueries, window functions, collations and complex types. It is available as a standalone CLI application with clients for Python, R, Java and Wasm.
Framework to create ChatGPT like bots over your dataset.
The Python ensemble sampling toolkit for affine-invariant MCMC.
Gadfly is a Julia package for creating statistical graphics. Developed by GiovineItalia, it provides a grammar of graphics for generating visualizations in Julia. The repository includes documentation, examples, and installation instructions, and is open source.
A Clojure dataframe library that runs on Apache Spark.
Unified interface to ggplot2 popular R packages.
Globe is a Go library for wireframe globe visualizations, backed by pinhole. It can draw graticules, land and country boundaries, dots, lines along great circles, and rectangles, and save output as PNG. Users install it with go get, and the project is available under the ISC License.
Glot is a plotting library for Golang built on top of gnuplot.
Graph layout algorithms in pure Julia.
Grid studio is a web-based spreadsheet application with full integration of the Python programming language.
HDBSCAN is a high performance implementation of hierarchical density-based clustering. It performs DBSCAN over varying epsilon values and integrates results to find a clustering with the best stability over epsilon, allowing clusters of varying densities. The package inherits from sklearn classes and supports arrays, pandas dataframes, sparse matrices or distance matrices as input.
A dataset format for creating, storing, and collaborating on AI datasets of any size.
ipychart is a Python library that brings the power of Chart.js to Python. It is hosted on GitHub at https://github.com/nicohlr/ipychart. The repository includes installation instructions, documentation, usage examples, and development information.
Distributed POSIX file system built on top of Redis and S3.
Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts.
Kartograph.py is a Python library for rendering beautiful SVG maps. The project is currently unmaintained, but its source code remains available on GitHub. It allows users to create map visualizations programmatically.
Koalas, from Databricks, implements the pandas DataFrame API on top of Apache Spark. The repository is marked deprecated and in maintenance mode; Koalas supports Apache Spark 3.1 and below, and PySpark is recommended directly for Spark 3.2 and above. It is available under the Apache-2.0 license.
LightlyTrain is an open-source GitHub repository offering all-in-one training capabilities for vision models, including YOLO, ViTs, RT-DETR, and DINOv3. It supports pretraining, fine-tuning, and distillation workflows for these model types.
Unified metadata exploration API service for Hive, RDS, Teradata, Redshift, S3 and Cassandra.
notespace is an open source project hosted as a public repository on GitHub under the scicloj/notespace project. It is designed to enable users to use their namespace as a notebook. The project invites contributions from developers.
MinerU is a tool that transforms complex documents such as PDFs and Office documents into LLM-ready markdown or JSON for agentic workflows. It supports multiple input formats including PDF, images, DOC/DOCX, PPT/PPTX, XLS/XLSX, RTF, ODT/ODS/ODP, EPUB, OFD, HTML/MHTML and CSV/TSV. Version 4.0 offers four parsing tiers and a document library with search and citation locators, and documents are not automatically uploaded to the official service; remote parsing requires explicit configuration.
Orkas is an open-source, local-first AI desktop app. A commander LLM directs specialist sub-agents and runs installed coding CLIs including Claude Code, Codex, OpenCode, OpenClaw, and Hermes as local sessions. Its agents self-evolve via reflection and skill crystallization, supports bring-your-own keys, and is compatible with macOS, Windows, and Linux.
Create HTML profiling reports from pandas DataFrame objects.
ParaMonte is a serial and parallel library of Monte Carlo routines for sampling mathematical density functions of arbitrary dimensions and machine learning algorithms for scientific inference. It is designed for interoperability with C, C++, Fortran, MATLAB and Python, and supports shared-memory OpenMP threads and MPI distributed communications.
