Python data visualization libraries

Streamlit

Framework for turning Python scripts into interactive data apps.

Dash

Framework for building data apps and dashboards in Python, built on Plotly.js and React.

Matplotlib

2D plotting library.

Bokeh

Interactive Web Plotting for Python.

Taipy

Python framework for building data and AI web applications with interactive charts and dashboards.

Plotly (Python)

Interactive web based visualization built on top of plotly.js

PyGWalker

Turns dataframes into a drag-and-drop visual analysis UI in Jupyter, based on Graphic Walker.

pyecharts

Python binding for Echarts library.

Seaborn

A library for making attractive and informative statistical graphics.

ydata-profiling

Generates statistical analytic reports with visualization for quick data analysis (formerly pandas-profiling).

Rerun

An SDK for logging computer vision and robotics data paired with a visualizer for exploring that data over time.

WordCloud

Word cloud generator for Python.

Vega-Altair

Declarative statistical visualizations, based on Vega-Lite.

SciencePlots

Matplotlib styles for scientific figures and journal publications.

folium

Builds interactive Leaflet.js maps from Python data.

Voilà

Turns Jupyter notebooks into standalone interactive web applications.

Panel

Data exploration and web app framework for Python that works with many plotting libraries.

plotnine

Grammar of graphics for Python, based on R's ggplot2.

mplfinance

Financial market data visualization (candlestick, OHLC, volume) using matplotlib.

PyQtGraph

Interactive and realtime 2D/3D/Image plotting and science/engineering widgets.

missingno

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

PyVista

3D plotting and mesh analysis through a streamlined interface for the Visualization Toolkit (VTK)

leafmap

Interactive mapping and geospatial analysis in Jupyter with multiple mapping backends.

bqplot

Plotting library for IPython/Jupyter notebooks.

ggpy

Plotting system based on R's ggplot2.

Chartify

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

VisPy

High-performance scientific visualization based on OpenGL.

Datashader

Renders very large datasets into accurate images by rasterizing them.

VTK

Open-source library for 3d Graphics, image processing and visualization.

HoloViews

Complex and declarative visualizations from annotated data.

napari

Fast, interactive viewer for multi-dimensional images in Python.

vedo

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

Plotext

Plots data directly in the terminal with a matplotlib-like syntax.

Lets-Plot

Grammar of graphics plotting library for Python and Kotlin, by JetBrains.

Shiny for Python

Python version of the Shiny reactive framework for interactive data apps.

Cartopy

Cartographic projections and geospatial data plotting with matplotlib.

Mayavi

Interactive scientific data visualization and 3D plotting in Python.

glumpy

OpenGL scientific visualizations library.

Veusz

Python multiplatform GUI plotting tool and graphing library

pptk

Visualize and work with 2D/3D pointclouds

yt

Toolkit for analysis and visualization of volumetric data.

uniplot

Lightweight plotting to the terminal. 4x resolution via Unicode.

Toyplot

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

diagram

Text mode diagrams using UTF-8 characters

Quibbler

Your data and anything you plot is effortlessly live and interactive.

ipychart

The power of Chart.js in Jupyter Notebook.

three.py

Easy to use 3D library based on PyOpenGL. Inspired by Three.js.

syd

A package for making GUIs around matplotlib figures easy, fast, and streamlined.