Tabular Data
Showing 36 of 58 projects
A deep learning library built on PyTorch that provides high-level components for rapid results and low-level components for research flexibility.
A deep learning library built on PyTorch that provides high-level components for rapid results and low-level components for research flexibility.
An automated machine learning library that trains and deploys high-accuracy models for tabular, text, image, and time series data with minimal code.
A GPU-accelerated DataFrame library for tabular data processing, part of the RAPIDS data science suite.
A terminal spreadsheet multitool for exploring and arranging tabular data from various formats.
A high-performance Python DataFrame library for lazy out-of-core processing and visualization of billion-row datasets at interactive speeds.
A Python library for handling tabular datasets across multiple formats like XLS, CSV, JSON, and YAML.
An open-source solution for continuous validation of machine learning models and data, from research to production.
A blazing-fast command-line toolkit for querying, slicing, analyzing, transforming, and validating tabular data (CSV, Excel, JSONL, etc.).
A Go library providing DataFrames, Series, and data wrangling operations for tabular data manipulation.
A Go library providing DataFrames, Series, and data wrangling operations for structured data manipulation.
An Automated Machine Learning Python package for tabular data with feature engineering, hyperparameter tuning, explanations, and automatic documentation.
Ajax-enabled jQuery grid plugin for displaying and manipulating tabular data in web applications.
Automatic neural architecture search and hyperparameter optimization for PyTorch, focusing on tabular data and time series forecasting.
A fast, header-only C++11 library for reading CSV files with automatic column rearrangement, threading for I/O overlap, and configurable parsing features.
A set of Backbone.js components for building semantic, easily stylable data grid widgets with a clean JavaScript API.
A flexible and fast package for in-memory tabular data manipulation and analysis in the Julia programming language.
An R package for creating, modifying, analyzing, and visualizing network graphs from tabular data.
A unified framework for implementing and training deep learning models on tabular data using PyTorch and PyTorch Lightning.
A Python package for generating synthetic tabular and time-series data using state-of-the-art generative models like GANs and Gaussian Mixtures.
A feature-rich Angular component for displaying and managing tabular data with built-in CRUD operations.
A suite of high-performance command line tools for filtering, summarizing, joining, and manipulating large tabular data files.
A modern, interactive JavaScript datatable library for displaying and editing tabular data on the web.
A fast and friendly R package for reading rectangular data from delimited files like CSV and TSV.
An automated feature generation framework for tabular data that discovers expert-level features to boost machine learning model performance.
A model-agnostic method for generating high-precision rule-based explanations for black-box classifier predictions.
A modular deep learning framework for PyTorch to build neural networks on heterogeneous tabular data.
A Python library for introductory data science education, developed for Berkeley's Data 8 course.
A high-performance, functional tabular data processing library for Clojure, similar to Python's Pandas or R's data.table.
A Go library for creating readable tabular data displays in terminal applications.
A Swift library for reading and writing CSV files with support for Decodable serialization and RFC4180 compliance.
A Neovim plugin that displays CSV/TSV files in a tabular format with virtual text, Excel-like navigation, and sticky headers.
A fast, interactive datagrid widget for Jupyter Notebook and JupyterLab with advanced features like selections, renderers, and conditional formatting.
A Clojure library for prettifying console output with ANSI fonts, formatted exceptions, binary diffs, and tables.
A Python library for generating high-quality synthetic tabular data using GANs, diffusion models, and large language models.
A customizable and easy-to-use data table component for Vue.js 3.x applications.
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