This project provides a framework for performing data science tasks using command-line tools and scripts. It focuses on the processing and analysis of text and structured data directly within the terminal. The approach centers on using Unix pipes to stream data between independent processes and employing shell scripting to automate repetitive data science workflows. It utilizes plain-text interchange formats, such as CSV, to move information between diverse utilities. Capability areas include text-based data processing, command-line data analysis, and terminal-based data visualization. These
This project is a collection of curricular resources and hands-on tutorials designed to teach Python programming and scientific computing. It consists of a series of interactive lessons and executable notebooks that provide a guided approach to learning Python through a combination of code and prose. The curriculum is specifically designed for experienced programmers to quickly master Python syntax, data structures, and core language semantics. It includes an introductory guide to the libraries and programming environments used for scientific computing and complex dataset analysis. The educa
:books: WebAssembly friendly programming with C/C++ -- Emscripten practice
