Useful Python tools for data visualizations Python frameworks, libraries, and software of Data Visualization
This list is a collection of tools, projects, images, and resources conforming to the Awesome Manifesto
Contributions very welcome but first see Contributing.
- Core
- High-Level Shared API
- High-Level
- Native-GUI
- Other InfoVis
- SciVis
- Geospatial
- Graphs and networks
- Other domain-specific
- Large-data rendering
- Dashboarding
- Colormapping
- Not in PyViz
- matplotlib - 2D plotting library.
- plotly - Interactive web based visualization built on top of plotly.js
- bokeh - Interactive Web Plotting for Python.
- altair - Declarative statistical visualizations, based on Vega-Lite.
- seaborn - A library for making attractive and informative statistical graphics.
- Chartify - Bokeh wrapper that makes it easy for data scientists to create charts.
- holoviews - Complex and declarative visualizations from annotated data.
- PyQtGraph - Interactive and realtime 2D/3D/Image plotting and science/engineering widgets.
- bqplot - Interactive Plotting Library for the Jupyter Notebook.
- plotnine - A grammar of graphics for Python based on ggplot2.
- pygal - A Python SVG Charts Creator.
- toyplot - The kid-sized plotting toolkit for Python with grownup-sized goals.
- glumpy - OpenGL scientific visualizations library.
- mayavi - interactive scientific data visualization and 3D plotting in Python.
- PyVista โ 3D plotting and mesh analysis through a streamlined interface for the Visualization Toolkit (VTK)
- vedo - Library for scientific analysis and visualization of 3D objects based on VTK.
- VisPy - High-performance scientific visualization based on OpenGL.
- vtk - 3D computer graphics, image processing, and visualization that includes a Python interface.
- cartopy - A cartographic python library with matplotlib support.
- GeoVista - Cartographic rendering and mesh analytics powered by PyVista.
- pygraphviz - Python interface to Graphviz.
- missingno - provides flexible toolset of data-visualization utilities that allows quick visual summary of the completeness of your dataset, based on matplotlib.
- dash - Built on top of Flask, React and Plotly aimed at analytical web applications.
- Streamlit - Streamlit turns data scripts into shareable web apps in minutes. All in pure Python. No frontโend experience required.
- diagram - Text mode diagrams using UTF-8 characters
- diagrams - Diagram as Code.
- ggplot - plotting system based on R's ggplot2.
- ipychart - The power of Chart.js in Jupyter Notebook.
- pandas-profiling - generates statistical analytic reports with visualization for quick data analysis.
- pptk - Visualize and work with 2D/3D pointclouds
- pyechars - Python binding for Echarts library.
- three.py - Easy to use 3D library based on PyOpenGL. Inspired by Three.js.
- veusz - Python multiplatform GUI plotting tool and graphing library