5 dépôts
Performing deep data analysis by executing optimized queries across warehouses.
Distinct from SQL Analysis Tools: Distinct from SQL Analysis Tools: focuses on the analytical outcome of querying data rather than auditing the query structure.
Explore 5 awesome GitHub repositories matching data & databases · Dataset Analysis. Refine with filters or upvote what's useful.
Perspective is a columnar data analytics engine and high-performance visualization component powered by WebAssembly. It provides a system for analyzing and visualizing large or streaming datasets through interactive data grids and charts, utilizing a compiled binary to achieve near-native performance within the browser. The project distinguishes itself through a WebSocket-based data streaming interface and deep Apache Arrow integration, which minimize memory overhead when synchronizing tables between servers and clients. It acts as a remote query proxy capable of translating visualization con
Enables immediate grouping, sorting, filtering, and aggregations on datasets via an interactive viewer.
This project is a plugin framework and agentic workflow library designed to connect large language models to professional toolstacks. It provides a system for integrating language models with external data warehouses, CRMs, and other enterprise software to retrieve and manipulate real-time business data. The framework enables the automation of specialized professional tasks through a file-based plugin definition system. It allows for the customization of domain expertise and plugin behavior to align with internal company processes, supported by an enterprise data connector that links models t
Executes optimized SQL queries across enterprise data warehouses to perform deep dataset analysis.
ThinkStats2 is a computational statistics course and educational library designed to teach probability and statistics through a programmatic approach. It provides a framework for studying statistical concepts by writing Python code and running simulations on real-world datasets. The project uses interactive notebooks and a collection of Python modules to deliver guided lessons. It emphasizes the verification of theoretical statistical laws through iterative computational experiments and simulation-driven testing. The resource covers broad capabilities in data analysis and data science traini
Provides a framework for studying statistical patterns using programmatic analysis of real-world datasets.
Mapshaper est un outil pour traiter, simplifier et convertir des données vectorielles géographiques, disponible sous forme d'interface en ligne de commande, d'outil de navigateur web et de bibliothèque Node.js. Il fonctionne comme un projecteur de coordonnées, un convertisseur de données vectorielles et un optimiseur d'actifs de carte web conçu pour transformer les jeux de données spatiaux entre différents systèmes de référence de coordonnées et formats de fichiers. Le projet se distingue par sa simplification de géométrie préservant la topologie, qui réduit le nombre de sommets tout en maintenant les limites partagées pour éviter les lacunes et les chevauchements. Il optimise davantage les actifs pour le web grâce à la quantification des coordonnées et au filtrage des attributs pour réduire la taille des fichiers. Le système couvre un large éventail de capacités, y compris la reprojection de coordonnées utilisant des chaînes PROJ et des codes EPSG, et la conversion de données entre des formats tels que Shapefile, GeoJSON, TopoJSON, GeoPackage et KML. Il fournit des outils de traitement de géométrie étendus pour la mise en mémoire tampon, le découpage, la dissolution et la réparation des topologies, ainsi que des utilitaires de gestion de données pour la jointure, le filtrage et la transformation d'attributs. De plus, il inclut des fonctionnalités de visualisation pour générer des exportations SVG stylisées, des graticules et des cartes à symboles proportionnels. Les capacités de traitement spatial peuvent être intégrées directement dans les applications JavaScript et les pipelines de build via sa bibliothèque Node.js.
Provides an overview of files by printing geometry types, feature counts, and coordinate systems.
This project is an edge computing development toolkit and serverless command line interface used to develop, test, and deploy serverless functions to a global edge network. It serves as an edge runtime bundler and resource orchestrator, managing the entire lifecycle of edge projects from local development to worldwide distribution. The toolkit distinguishes itself through distributed workflow management, coordinating stateful instances and the durable execution of long-running processes across the edge. It also provides specialized integrations for edge AI, including the management of vector
Allows writing execution data points to datasets for SQL-based observability and performance analysis.