awesome-python-data-visualization

Declarative statistical visualizations, based on Vega-Lite.

Bokeh wrapper that makes it easy for data scientists to create charts.

Complex and declarative visualizations from annotated data.

A library for making attractive and informative statistical graphics.

Built on top of Flask, React and Plotly aimed at analytical web applications.

Streamlit turns data scripts into shareable web apps in minutes. All in pure Python. No front‑end experience required.

Interactive Web Plotting for Python.

2D plotting library.

Interactive web based visualization built on top of

Interactive Plotting Library for the Jupyter Notebook.

A grammar of graphics for Python based on ggplot2.

A Python SVG Charts Creator.

The kid-sized plotting toolkit for Python with grownup-sized goals.

A cartographic python library with matplotlib support.

Cartographic rendering and mesh analytics powered by PyVista.

Text mode diagrams using UTF-8 characters

Diagram as Code.

plotting system based on

The power of Chart.js in Jupyter Notebook.

generates statistical analytic reports with visualization for quick data analysis.

Visualize and work with 2D/3D pointclouds

OpenGL scientific visualizations library.

interactive scientific data visualization and 3D plotting in Python.

Library for scientific analysis and visualization of 3D objects based on VTK.

High-performance scientific visualization based on OpenGL.

3D computer graphics, image processing, and visualization that includes a Python interface.

provides flexible toolset of data-visualization utilities that allows quick visual summary of the completeness of your dataset, based on matplotlib.