Search Results for "real"

Shiny is an R package from RStudio that enables users to build interactive web applications using R without requiring knowledge of JavaScript, HTML, or CSS. It allows statisticians and data scientists to turn their analyses into fully functional web dashboards with reactive elements, data inputs, visualizations, and controls, making data communication more effective and dynamic.

MetBrewer is an R package that provides color palettes inspired by artworks and collections in the Metropolitan Museum of Art (The Met). The idea is to draw on the rich visual heritage of fine art to generate palettes that are aesthetically pleasing and grounded in real-world artistic color usage. The palettes are curated, named after artworks or styles, and often include notes about colorblind-friendliness and contrast. The package supports both discrete and continuous palette types, with interpolation when more colors are requested than originally defined. It also provides ggplot2-friendly scale functions (scale_color_met_c, scale_fill_met_d, etc.) so integration into typical R plotting workflows is smooth. ...

The advanced-shiny repository is a curated collection of practical tips, design patterns, and mini Shiny apps focused on solving real-world challenges in R Shiny applications. The author (Dean Attali) collected many of the “harder” or less-documented tricks he uses or encounters frequently—things like controlling UI behavior dynamically, managing reactive logic, optimizing interactivity, and structuring large Shiny codebases. The repo’s structure includes folders of example apps each implementing a specific trick or pattern (e.g. loading spinners, dynamic UI, hiding/showing UI elements, handling file uploads, URL parameter inputs). ...

awesome-network-analysis is a curated list of resources focused on network and graph analysis, including libraries, frameworks, visualization tools, datasets, and academic papers. It covers multiple programming languages and domains like sociology, biology, and computer science. This repository serves as a central reference for researchers, analysts, and developers working with network data.

...It includes a docker-compose configuration with QuestDB, Grafana, Code-Server and Nginx. The AI Agent Host provides a seamless interface for managing and querying data, visualizing results, and coding in real-time. The AI Agent Host is built specifically for LangChain, a framework dedicated to developing applications powered by language models. LangChain recognizes that the most powerful and distinctive applications go beyond simply utilizing a language model and strive to be data-aware and agentic. Being data-aware involves connecting a language model to other sources of data, enabling a comprehensive understanding and analysis of information.

This repository is designed to provide a minimal benchmark framework comparing commonly used machine learning libraries in terms of scalability, speed, and classification accuracy. The focus is on binary classification tasks without missing data, where inputs can be numeric or categorical (after one-hot encoding). It targets large scale settings by varying the number of observations (n) up to millions and the number of features (after expansion) to about a thousand, to stress test different...