Bokeh vs Chart.js

Overview

Bokeh

Stacks95

Followers183

Votes12

GitHub Stars20.2K

Forks4.2K

Chart.js

Stacks2.0K

Followers786

Votes44

GitHub Stars66.7K

Forks12.0K

Bokeh vs Chart.js: What are the differences?

1. Data Visualization Capabilities: Bokeh is primarily used for creating interactive and browser-based visualizations, offering a wide range of options including basic plots, bar charts, scatter plots, and heat maps. On the other hand, Chart.js is a lightweight library designed specifically for creating static and responsive charts using HTML5 canvas. While Bokeh allows for more complex and interactive visualizations, Chart.js is more suitable for simple and static charts.
2. Programming Languages: Bokeh is built using Python and provides an extensive Python library for creating visualizations. On the contrary, Chart.js is based on JavaScript and allows developers to create charts by writing JavaScript code. This difference in programming languages means that Bokeh is more convenient for Python developers, while Chart.js can be used by JavaScript developers.
3. Interactivity and Animations: Bokeh enables developers to create highly interactive visualizations, offering features such as hover tooltips, zooming, panning, and interactive legends. It also supports animations and can update the visualizations in real-time. Chart.js, on the other hand, lacks many of these interactive features and is more focused on creating static charts.
4. Community and Support: Bokeh is a mature and widely adopted library, backed by a strong community of developers. It provides extensive documentation, examples, and support resources, making it easier to learn and troubleshoot. Chart.js also has a supportive community, but it is relatively newer compared to Bokeh and may have fewer resources available.
5. Integration with Other Libraries: Bokeh can be easily integrated with other Python libraries such as NumPy and pandas, which makes it convenient for data manipulation and analysis. On the contrary, Chart.js does not have direct integration with other JavaScript libraries, and developers may need to write additional code to achieve similar functionality.
6. Customizability: Bokeh offers a high level of customization, allowing developers to control various aspects of the visualizations such as colors, layouts, and styling. It also provides a wide range of predefined themes. Chart.js, while it does offer some level of customization, has more limited options compared to Bokeh.

In Summary, Bokeh and Chart.js differ in terms of their data visualization capabilities, programming languages, interactivity, community support, integration with other libraries, and customizability.

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Advice on Bokeh, Chart.js

Shaik

Feb 18, 2020

Needs advice

I have used highcharts and it is pretty awesome for my previous project. now as I am about to start my new project I want to use other charting libraries such as recharts, chart js, Nivo, d3 js.... my upcoming project might use react js as front end and laravel as a backend technology. the project would be of hotel management type. please suggest me the best charts to use

246k views246k

Comments

Sudhan

Dec 23, 2019

Needs advice

I'm developing angular 8 application, I need to create a dynamic, custom charts based on the data, Charts options will be configured with a user input form. at any time users can edit and modify the chart options. even I dont know how many charts I have to create everything is dynamic. ( based on the user configuration chart counts will vary ). I need some suggestions on which chart will give these kinds of flexible options.

42.8k views42.8k

Comments

Detailed Comparison

Bokeh	Chart.js
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.	Visualize your data in 6 different ways. Each of them animated, with a load of customisation options and interactivity extensions.
interactive visualization library ; versatile graphics ; open source; https://github.com/bokeh/bokeh	animated;HTML5 based;Responsive;Modular;Bar;Doughnut;Radar;Line;Polar Area;Interactive
Statistics
GitHub Stars 20.2K	GitHub Stars 66.7K
GitHub Forks 4.2K	GitHub Forks 12.0K
Stacks 95	Stacks 2.0K
Followers 183	Followers 786
Votes 12	Votes 44
Pros & Cons
Pros 12 Beautiful Interactive charts in seconds	Pros 19 Offers all types of charts 14 Interactive Charts 10 It's totally free Cons 12 Slow rendering 2 Bitmap quality export 1 Low quality zoom plugin 0 It's totally free
Integrations
Bootstrap Flask NGINX React Django Python Jupyter Tornado Streamlit	React AngularJS

What are some alternatives to Bokeh, Chart.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.

Underscore

A JavaScript library that provides a whole mess of useful functional programming helpers without extending any built-in objects.

Deno

It is a secure runtime for JavaScript and TypeScript built with V8, Rust, and Tokio.

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.

Plotly.js

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.

Recharts

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

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

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

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

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

Related Comparisons

Bokeh vs Chart.js: What are the differences?

1. Data Visualization Capabilities: Bokeh is primarily used for creating interactive and browser-based visualizations, offering a wide range of options including basic plots, bar charts, scatter plots, and heat maps. On the other hand, Chart.js is a lightweight library designed specifically for creating static and responsive charts using HTML5 canvas. While Bokeh allows for more complex and interactive visualizations, Chart.js is more suitable for simple and static charts.
2. Programming Languages: Bokeh is built using Python and provides an extensive Python library for creating visualizations. On the contrary, Chart.js is based on JavaScript and allows developers to create charts by writing JavaScript code. This difference in programming languages means that Bokeh is more convenient for Python developers, while Chart.js can be used by JavaScript developers.
3. Interactivity and Animations: Bokeh enables developers to create highly interactive visualizations, offering features such as hover tooltips, zooming, panning, and interactive legends. It also supports animations and can update the visualizations in real-time. Chart.js, on the other hand, lacks many of these interactive features and is more focused on creating static charts.
4. Community and Support: Bokeh is a mature and widely adopted library, backed by a strong community of developers. It provides extensive documentation, examples, and support resources, making it easier to learn and troubleshoot. Chart.js also has a supportive community, but it is relatively newer compared to Bokeh and may have fewer resources available.
5. Integration with Other Libraries: Bokeh can be easily integrated with other Python libraries such as NumPy and pandas, which makes it convenient for data manipulation and analysis. On the contrary, Chart.js does not have direct integration with other JavaScript libraries, and developers may need to write additional code to achieve similar functionality.
6. Customizability: Bokeh offers a high level of customization, allowing developers to control various aspects of the visualizations such as colors, layouts, and styling. It also provides a wide range of predefined themes. Chart.js, while it does offer some level of customization, has more limited options compared to Bokeh.

Bokeh vs Chart.js

Overview