How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.
pyecharts is a Python visualization library and wrapper for the Echarts JavaScript engine. It translates Python data and configurations into JSON specifications to generate interactive web-based charts and graphs. The library provides specialized capabilities for geographic data mapping using a comprehensive library of map assets to visualize spatial information. It also includes utilities to capture rasterized snapshots of rendered web visualizations for export as static image files. The tool supports rendering interactive plots directly within data science notebook environments and exporti
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
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
Python+Numpy+OpenGL: fast, scalable and beautiful scientific visualization
Python library that makes it easy for data scientists to create charts.
The main features of spotify/chartify are: Data Visualization, Python Visualization, Python Visualization Libraries.
Projects with overlapping indexed features include: pyecharts/pyecharts — pyecharts is a Python visualization library and wrapper for the Echarts JavaScript engine. It translates Python data… bokeh/bokeh — Bokeh is a Python data visualization library and interactive plotting framework used to create high-performance… matplotlib/matplotlib — Matplotlib is a Python data visualization library and 2D plotting engine used to generate publication-quality figures… nicohlr/ipychart — The power of Chart.js with Python. glumpy/glumpy — Python+Numpy+OpenGL: fast, scalable and beautiful scientific visualization. residentmario/missingno — missingno is a Python library for the visualization and analysis of missing data patterns. It provides a set of tools…