Interactive Data Visualization in the browser, from Python

Overview
Bokeh logotype

Bokeh is an interactive visualization library for modern web browsers. It provides elegant, concise construction of versatile graphics, and affords high-performance interactivity over large or streaming datasets. Bokeh can help anyone who would like to quickly and easily make interactive plots, dashboards, and data applications.

Latest Release Latest release version npm version Conda Conda downloads per month
License Bokeh license (BSD 3-clause) PyPI PyPI downloads per month
Sponsorship Powered by NumFOCUS Live Tutorial Live Bokeh tutorial notebooks on MyBinder
Build Status Current github actions build status Support Community Support on discourse.bokeh.org
Static Analysis Language grade: Python Language grade: JavaScript Twitter Follow Bokeh on Twitter

If you like Bokeh and would like to support our mission, please consider making a donation.

colormapped image plot thumbnail anscombe plot thumbnail stocks plot thumbnail lorenz attractor plot thumbnail candlestick plot thumbnail scatter plot thumbnail SPLOM plot thumbnail
iris dataset plot thumbnail histogram plot thumbnail periodic table plot thumbnail choropleth plot thumbnail burtin antibiotic data plot thumbnail streamline plot thumbnail RGBA image plot thumbnail
stacked bars plot thumbnail quiver plot thumbnail elements data plot thumbnail boxplot thumbnail categorical plot thumbnail unemployment data plot thumbnail Les Mis co-occurrence plot thumbnail

Installation

The easiest way to install Bokeh is using the Anaconda Python distribution and its included Conda package management system. To install Bokeh and its required dependencies, enter the following command at a Bash or Windows command prompt:

conda install bokeh

To install using pip, enter the following command at a Bash or Windows command prompt:

pip install bokeh

For more information, refer to the installation documentation.

Resources

Once Bokeh is installed, check out the first steps guides.

Visit the full documentation site to view the User's Guide or launch the Bokeh tutorial to learn about Bokeh in live Jupyter Notebooks.

Community support is available on the Project Discourse.

If you would like to contribute to Bokeh, please review the Developer Guide and request an invitation to the Bokeh Dev Slack workspace.

Note: Everyone interacting in the Bokeh project's codebases, issue trackers and discussion forums is expected to follow the Code of Conduct.

Follow us

Follow us on Twitter @bokeh

Sponsors

Fiscal Sponsors

The Bokeh project is grateful for individual contributions as well as sponsorship by the organizations and companies below:

NumFocus Logo Blackstone Logo
Anaconda Logo NVidia Logo Rapids Logo
Quansight Logo Rex Logo Nom Nom Data Logo

If your company uses Bokeh and is able to sponsor the project, please contact [email protected]

Bokeh is a Sponsored Project of NumFOCUS, a 501(c)(3) nonprofit charity in the United States. NumFOCUS provides Bokeh with fiscal, legal, and administrative support to help ensure the health and sustainability of the project. Visit numfocus.org for more information.

Donations to Bokeh are managed by NumFOCUS. For donors in the United States, your gift is tax-deductible to the extent provided by law. As with any donation, you should consult with your tax adviser about your particular tax situation.

In-kind Sponsors

The Bokeh project is also grateful for the donation of services from the following companies:

Security

To report a security vulnerability, please use the Tidelift security contact. Tidelift will coordinate the fix and disclosure.

Owner
Bokeh
Interactive Data Visualization
Bokeh
Regress.me is an easy to use data visualization tool powered by Dash/Plotly.

Regress.me Regress.me is an easy to use data visualization tool powered by Dash/Plotly. Regress.me.-.Google.Chrome.2022-05-10.15-58-59.mp4 Get Started

Amar 14 Aug 14, 2022
Analytical Web Apps for Python, R, Julia, and Jupyter. No JavaScript Required.

Dash Dash is the most downloaded, trusted Python framework for building ML & data science web apps. Built on top of Plotly.js, React and Flask, Dash t

Plotly 17.9k Dec 31, 2022
Simple CLI python app to show a stocks graph performance. Made with Matplotlib and Tiingo.

stock-graph-python Simple CLI python app to show a stocks graph performance. Made with Matplotlib and Tiingo. Tiingo API Key You will need to add your

Toby 3 May 14, 2022
Interactive Data Visualization in the browser, from Python

Bokeh is an interactive visualization library for modern web browsers. It provides elegant, concise construction of versatile graphics, and affords hi

Bokeh 17.1k Dec 31, 2022
2D maze path solver visualizer implemented with python

2D maze path solver visualizer implemented with python

SS 14 Dec 21, 2022
nvitop, an interactive NVIDIA-GPU process viewer, the one-stop solution for GPU process management

An interactive NVIDIA-GPU process viewer, the one-stop solution for GPU process management.

Xuehai Pan 1.3k Jan 02, 2023
Flexitext is a Python library that makes it easier to draw text with multiple styles in Matplotlib

Flexitext is a Python library that makes it easier to draw text with multiple styles in Matplotlib

Tomás Capretto 93 Dec 28, 2022
A curated list of awesome Dash (plotly) resources

Awesome Dash A curated list of awesome Dash (plotly) resources Dash is a productive Python framework for building web applications. Written on top of

Luke Singham 1.7k Jan 07, 2023
Easily convert matplotlib plots from Python into interactive Leaflet web maps.

mplleaflet mplleaflet is a Python library that converts a matplotlib plot into a webpage containing a pannable, zoomable Leaflet map. It can also embe

Jacob Wasserman 502 Dec 28, 2022
Render tokei's output to interactive sunburst chart.

Render tokei's output to interactive sunburst chart.

134 Dec 15, 2022
Fast visualization of radar_scenes based on oleschum/radar_scenes

RadarScenes Tools About This python package provides fast visualization for the RadarScenes dataset. The Open GL based visualizer is smoother than ole

Henrik Söderlund 2 Dec 09, 2021
Python ts2vg package provides high-performance algorithm implementations to build visibility graphs from time series data.

ts2vg: Time series to visibility graphs The Python ts2vg package provides high-performance algorithm implementations to build visibility graphs from t

Carlos Bergillos 26 Dec 17, 2022
Shaded 😎 quantile plots

shadyquant 😎 This python package allows you to quantile and plot lines where you have multiple samples, typically for visualizing uncertainty. Your d

Mehrad Ansari 13 Sep 29, 2022
nptsne is a numpy compatible python binary package that offers a number of APIs for fast tSNE calculation.

nptsne nptsne is a numpy compatible python binary package that offers a number of APIs for fast tSNE calculation and HSNE modelling. For more detail s

Biomedical Visual Analytics Unit LUMC - TU Delft 29 Jul 05, 2022
Fast data visualization and GUI tools for scientific / engineering applications

PyQtGraph A pure-Python graphics library for PyQt5/PyQt6/PySide2/PySide6 Copyright 2020 Luke Campagnola, University of North Carolina at Chapel Hill h

pyqtgraph 3.1k Jan 08, 2023
Implementation of SOMs (Self-Organizing Maps) with neighborhood-based map topologies.

py-self-organizing-maps Simple implementation of self-organizing maps (SOMs) A SOM is an unsupervised method for learning a mapping from a discrete ne

Jonas Grebe 6 Nov 22, 2022
Function Plotter: a simple application with GUI to plot mathematical functions

Function-Plotter Function Plotter is a simple application with GUI to plot mathe

Mohamed Nabawe 4 Jan 03, 2022
A Python package that provides evaluation and visualization tools for the DexYCB dataset

DexYCB Toolkit DexYCB Toolkit is a Python package that provides evaluation and visualization tools for the DexYCB dataset. The dataset and results wer

NVIDIA Research Projects 107 Dec 26, 2022
A Python package for caclulations and visualizations in geological sciences.

geo_calcs A Python package for caclulations and visualizations in geological sciences. Free software: MIT license Documentation: https://geo-calcs.rea

Drew Heasman 1 Jul 12, 2022
Focus on Algorithm Design, Not on Data Wrangling

The dataTap Python library is the primary interface for using dataTap's rich data management tools. Create datasets, stream annotations, and analyze model performance all with one library.

Zensors 37 Nov 25, 2022