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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

ScottPlot is a cross-platform, high-performance charting library for .NET that renders interactive plots across desktop and web GUI frameworks including Windows Forms, WPF, MAUI, Avalonia, Blazor, and WinUI. It provides an optimized rendering engine capable of displaying millions of data points with interactive pan, zoom, and live data streaming, while also supporting image export to formats like PNG and SVG for file output, cloud applications, and notebooks. The library distinguishes itself through a comprehensive set of chart types including scatter, line, bar, pie, heatmap, financial, rada

This C++ data visualization library is a scientific plotting framework used to create 2D and 3D charts, network graphs, and geographic maps. It operates as a multi-backend graphics library, decoupling high-level plotting logic from low-level rendering engines to support various output backends. The project distinguishes itself with a dual-interface API, providing both a global functional interface for rapid prototyping and an object-oriented interface for precise control. It features a component-based layout engine for managing tiled grids and subplots, alongside a layered plot state that all