How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.
Csvlens is a terminal-based tabular data explorer and memory-mapped browser designed for viewing and navigating large CSV files. It functions as a command-line interface for inspecting massive structured datasets while maintaining a constant memory footprint.
The main features of ys-l/csvlens are: Memory-Mapped File Access, Command-Line Viewers, Regex Row Filters, Large CSV Inspection, Streaming File Reads, Tabular Data Filtering, Command Line Data Explorers, Terminal Data Interfaces.
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This project is an educational resource and a collection of instructional materials for performing data manipulation and statistical analysis using Python. It provides a comprehensive set of guides and code examples for using the Pandas, NumPy, and Matplotlib libraries to analyze structured data. The resource includes a dedicated guide for reshaping, cleaning, and aggregating tabular data and time series via Pandas, alongside a reference for high-performance vectorized operations and linear algebra using NumPy. It also features tutorials for creating publication-quality charts, distribution p
csvkit is a composable Unix-style command-line toolkit for converting, filtering, and analyzing CSV files directly from the terminal. It provides a suite of focused single-purpose commands that can be combined via pipes to build complex data processing workflows, with a modular architecture that includes a column-type inference engine for automatically detecting data types and a streaming-pipeline design for efficient handling of tabular data. The toolkit distinguishes itself through its SQL-engine abstraction layer, which allows users to run SQL queries directly against CSV files without req
Bootstrap Table is a jQuery plugin for rendering interactive data grids with sorting, pagination, and filtering. It features a remote data integration system for fetching and synchronizing content from JSON endpoints using AJAX and server-side processing. The project includes a styling layer that adapts markup to work with various CSS frameworks, such as Bootstrap, Semantic UI, Bulma, and Material Design. It provides specialized rendering modes, including a hierarchical tree grid for parent-child row relationships and a responsive card-view table that transforms grids into mobile-friendly lay
Trippy is a network diagnostic tool and terminal user interface that combines ping and traceroute functionality to analyze network paths and performance. It provides a network packet parser and path analyzer to detect packet loss, jitter, and multipath routing through continuous network probing. The project is distinguished by its support for specialized tracing strategies, including Paris and Dublin, to ensure consistent path discovery. It identifies network address translation devices and utilizes heuristic analysis to distinguish genuine packet loss from rate-limiting. Broad capability ar