Awesome GitHub RepositoriesPlot Styling Configurators

jupyter-themes is a Jupyter Notebook theme manager and CSS interface customizer. It provides a command line tool to apply custom color schemes, fonts, and layout styles to notebook environments. The project includes a data visualization styling tool that synchronizes the aesthetic properties and color schemes of plotting libraries with the active interface theme. This ensures that data charts and figures remain visually consistent with the overall workspace theme.

SciencePlots is a Matplotlib style library and scientific plotting framework designed to automate the formatting of figures for academic journals and professional scientific publications. It provides a collection of visual presets and configuration rules for academic typography, layout, and resolution. The project features curated color-blind accessible palettes and figure formatters specifically designed to meet the strict submission standards of academic publishers. It includes specialized tools for professional figure styling and the rendering of non-Latin scripts for multilingual support.

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

ScrollableGraphView este o bibliotecă de vizualizare a datelor Swift și un framework de plotting pentru iOS utilizat pentru a randa seturi de date numerice discrete sub formă de grafice interactive. Oferă o componentă de interfață cu utilizatorul scrollabilă care vizualizează punctele de date folosind un sistem de coordonate cu layout-uri și stiluri configurabile. Framework-ul se caracterizează prin scalarea adaptivă a graficului, care ajustează automat axa verticală pentru a se potrivi punctelor de date vizibile pe măsură ce utilizatorul face scroll. Suportă randarea datelor în timp real, permițând vizualizărilor grafice să se actualizeze instantaneu pe măsură ce seturile de date subiacente se modifică prin tranziții animate. Biblioteca acoperă o varietate de tipuri de grafice, inclusiv grafice liniare, cu bare și cu puncte, și suportă plotting-ul multi-dataset pentru a afișa mai multe serii de date pe un singur grafic. Capabilitățile suplimentare includ etichetarea punctelor de date pe axa X, stilizarea personalizată a graficelor și utilizarea markerelor de linie de referință pentru a evidenția praguri sau valori de bază specifice.

Vega-Lite is a high-level declarative language for specifying interactive, multi-view visualizations. It compiles a concise JSON specification into a full Vega visualization, automatically inferring scales, axes, and legends from encoding declarations. The grammar-of-graphics encoding maps data fields to visual channels such as position, color, size, and shape, while a multi-view composition grammar enables layered, faceted, concatenated, and repeated layouts. Reactive parameter binding links named parameters to input widgets, selections, and expressions for dynamic updates. The project suppo

This is an interactive notebook-based course that teaches machine learning from Python fundamentals through deep learning and natural language processing. It uses real datasets and multiple frameworks within a structured, hands-on curriculum that combines concise explanations with executable code cells, built-in datasets, and embedded exercise checkpoints. Learning progresses through data preparation and exploration, classical machine learning workflows, computer vision with convolutional neural networks, and natural language processing with deep learning, all delivered as a cohesive progressi

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

mplfinance este un framework de vizualizare a datelor financiare și a seriilor temporale, construit pe baza Matplotlib. Este conceput pentru a randa cadre de date de piață în grafice specializate, inclusiv lumânări japoneze (candlesticks), bare OHLC, cărămizi Renko și grafice point-and-figure. Biblioteca se distinge printr-un framework dedicat datelor de piață care gestionează calendarele de tranzacționare și perioadele non-tranzacționabile, asigurând o spațiere temporală precisă prin eliminarea golurilor din timpul sărbătorilor. De asemenea, oferă un sistem pentru grafice de analiză tehnică, permițând suprapunerea mediilor mobile, a barelor de volum și a altor indicatori tehnici peste evoluția prețurilor. Toolkit-ul acoperă o gamă largă de capabilități, inclusiv organizarea de subplot-uri stivuite vertical cu axe partajate și aplicarea unor teme vizuale consistente. Suportă adnotări de piață precum liniile de trend, gestionarea datelor lipsă și capacitatea de a reîmprospăta graficele pentru fluxuri de date în timp real. Vizualizările pot fi exportate în diverse formate, inclusiv PDF, SVG, PNG și JPG.

Makie.jl is a high-performance Julia data visualization library and hardware-accelerated plotting engine used to create interactive 2D and 3D visualizations. It functions as a reactive visualization framework where plots update automatically via observables and compute graphs, and as a vector graphics generator for high-resolution academic output. The system is distinguished by its backend-agnostic rendering pipeline, which supports OpenGL, WebGL, and ray-traced scenes. It employs a grammar-of-graphics approach to map variables to aesthetic attributes and utilizes a hierarchical scene graph t

Patchwork is a layout manager for combining multiple ggplot2 graphics into a single complex arrangement. It functions as a multi-plot composition tool and data visualization orchestrator, allowing independent graphics to be arranged into grids and nested layouts using additive and functional syntax. The system differentiates itself through a broadcast-based style application that propagates themes and scales across all subplots to maintain visual consistency. It also features guide-merging reconciliation to identify and collapse redundant legends into a single shared global guide. The framew