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Main repository for Vispy
The main features of vispy/vispy are: Data Visualization.
Projects with overlapping indexed features include: man-group/dtale — dtale is a web-based interactive grid and visualizer for pandas dataframes, designed as an exploratory data analysis… mwaskom/seaborn — Seaborn is a Python library designed for statistical data visualization. It functions as a high-level interface built… bokeh/bokeh — Bokeh is a Python data visualization library and interactive plotting framework used to create high-performance… has2k1/plotnine — Plotnine is a data visualization library for Python based on the Grammar of Graphics. It serves as a declarative… matplotlib/matplotlib — Matplotlib is a Python data visualization library and 2D plotting engine used to generate publication-quality figures… plotly/dash — Dash is a Python-based framework for building analytical web applications and reactive data dashboards. It allows…
Plotnine is a data visualization library for Python based on the Grammar of Graphics. It serves as a declarative statistical plotting framework and multi-panel plotting engine, allowing users to create complex charts by mapping data variables to visual properties such as position, color, and size. The project is distinguished by its use of a layered composition model and a statistical transformation engine that performs aggregations and computations before rendering visuals. It features a comprehensive system for multi-panel faceting, which enables the splitting of a single visualization into
dtale is a web-based interactive grid and visualizer for pandas dataframes, designed as an exploratory data analysis tool. It provides a browser-based interface for analyzing tabular data structures, allowing users to calculate statistics, detect outliers, and compute correlations without writing manual code. The project functions as an embedded data viewer that can be integrated into web applications via iframes or custom routes, with specific support for Django, Flask, and Streamlit. It enables the exploration of datasets through a combination of an interactive data grid and a data visualiz
Bokeh is a Python data visualization library and interactive plotting framework used to create high-performance graphics and data dashboards that render in web browsers. It serves as a tool for generating standalone HTML documents, embedded components for digital notebooks, and full-stack web applications powered by a Python backend. The project distinguishes itself through its ability to handle large or streaming datasets while maintaining smooth interactivity. It enables linked brushing across multiple views, allowing data selected in one plot to automatically highlight corresponding data i
Matplotlib is a Python data visualization library and 2D plotting engine used to generate publication-quality figures and charts from numerical data. It serves as a numerical graphics library and data visualization toolkit for mapping data to visual elements. The library provides capabilities for producing static, animated, and interactive visualizations. This includes creating high-resolution figures for professional documents, generating moving graphics to illustrate data evolution over time, and building dynamic plots for interactive data exploration. The toolkit supports scientific plott