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  1. Stackups
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  5. Bokeh vs Plotly

Bokeh vs Plotly

OverviewComparisonAlternatives

Overview

Plotly.js
Plotly.js
Stacks399
Followers694
Votes69
GitHub Stars17.9K
Forks1.9K
Bokeh
Bokeh
Stacks95
Followers183
Votes12
GitHub Stars20.2K
Forks4.2K

Bokeh vs Plotly: What are the differences?

Introduction

Bokeh and Plotly are both interactive data visualization libraries that are commonly used in web applications. While they share some similarities, there are several key differences between the two.

  1. Backend Infrastructure: The major difference between Bokeh and Plotly lies in their backend infrastructure. Bokeh is a server-based library that generates JavaScript in the client-side browser to create interactive visualizations. On the other hand, Plotly is API-based and can be used with different programming languages to generate visualizations.

  2. Ease of Use: Bokeh provides a simplified and concise API that allows users to create visualizations with minimal code. It emphasizes ease of use and offers a wide range of pre-built plot types. Plotly, on the other hand, has a slightly steeper learning curve and requires a deeper understanding of the API and its different components.

  3. Interactivity: Bokeh is primarily designed for creating interactive visualizations, with support for interactivity such as hover tooltips, zooming, panning, and selection tools. Plotly, on the other hand, offers a more extensive set of interactivity options, including linked brushing, animations, and even 3D plotting capabilities.

  4. Offline vs. Online Usage: Bokeh supports both offline and online usage, meaning that you can generate visualizations without internet connectivity. Plotly, on the other hand, is built to work primarily in an online environment and requires an internet connection to retrieve data and create visualizations.

  5. Community and Documentation: Bokeh has a growing community of users and developers, and it provides comprehensive documentation and examples to help users get started. Plotly, on the other hand, has a larger and more active community, with extensive documentation and a wide range of user-contributed examples and tutorials.

  6. Cost and Licensing: Bokeh is an open-source library released under the BSD-3-Clause license, making it free to use and distribute. Plotly offers both open-source and commercial versions, with additional features available in the commercial version for enterprise users.

In Summary, Bokeh and Plotly are both powerful tools for creating interactive visualizations, but they differ in terms of their backend infrastructure, ease of use, interactivity options, offline/online usage, community support, and licensing.

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Detailed Comparison

Plotly.js
Plotly.js
Bokeh
Bokeh

It is a standalone Javascript data visualization library, and it also powers the Python and R modules named plotly in those respective ecosystems (referred to as Plotly.py and Plotly.R). It can be used to produce dozens of chart types and visualizations, including statistical charts, 3D graphs, scientific charts, SVG and tile maps, financial charts and more.

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.

Feature parity with MATLAB/matplotlib graphing; Online chart editor; Fully interactive (hover, zoom, pan); SVG and WebGL backends; Publication-quality image export
interactive visualization library ; versatile graphics ; open source; https://github.com/bokeh/bokeh
Statistics
GitHub Stars
17.9K
GitHub Stars
20.2K
GitHub Forks
1.9K
GitHub Forks
4.2K
Stacks
399
Stacks
95
Followers
694
Followers
183
Votes
69
Votes
12
Pros & Cons
Pros
  • 16
    Bindings to popular languages like Python, Node, R, etc
  • 10
    Integrated zoom and filter-out tools in charts and maps
  • 9
    Great support for complex and multiple axes
  • 8
    Powerful out-of-the-box featureset
  • 6
    Beautiful visualizations
Cons
  • 18
    Terrible document
Pros
  • 12
    Beautiful Interactive charts in seconds
Integrations
Python
Python
React
React
MATLAB
MATLAB
Jupyter
Jupyter
Julia
Julia
Bootstrap
Bootstrap
Flask
Flask
NGINX
NGINX
React
React
Django
Django
Python
Python
Jupyter
Jupyter
Tornado
Tornado
Streamlit
Streamlit

What are some alternatives to Plotly.js, Bokeh?

D3.js

D3.js

It is a JavaScript library for manipulating documents based on data. Emphasises on web standards gives you the full capabilities of modern browsers without tying yourself to a proprietary framework.

Highcharts

Highcharts

Highcharts currently supports line, spline, area, areaspline, column, bar, pie, scatter, angular gauges, arearange, areasplinerange, columnrange, bubble, box plot, error bars, funnel, waterfall and polar chart types.

Chart.js

Chart.js

Visualize your data in 6 different ways. Each of them animated, with a load of customisation options and interactivity extensions.

Recharts

Recharts

Quickly build your charts with decoupled, reusable React components. Built on top of SVG elements with a lightweight dependency on D3 submodules.

ECharts

ECharts

It is an open source visualization library implemented in JavaScript, runs smoothly on PCs and mobile devices, and is compatible with most current browsers.

ZingChart

ZingChart

The most feature-rich, fully customizable JavaScript charting library available used by start-ups and the Fortune 100 alike.

amCharts

amCharts

amCharts is an advanced charting library that will suit any data visualization need. Our charting solution include Column, Bar, Line, Area, Step, Step without risers, Smoothed line, Candlestick, OHLC, Pie/Donut, Radar/ Polar, XY/Scatter/Bubble, Bullet, Funnel/Pyramid charts as well as Gauges.

CanvasJS

CanvasJS

Lightweight, Beautiful & Responsive Charts that make your dashboards fly even with millions of data points! Self-Hosted, Secure & Scalable charts that render across devices.

AnyChart

AnyChart

AnyChart is a flexible JavaScript (HTML5) based solution that allows you to create interactive and great looking charts. It is a cross-browser and cross-platform charting solution intended for everybody who deals with creation of dashboard, reporting, analytics, statistical, financial or any other data visualization solutions.

ApexCharts

ApexCharts

A modern JavaScript charting library to build interactive charts and visualizations with simple API.

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