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Bokeh vs Chart.js: What are the differences?

  1. 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. 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. 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. 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. 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. 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.

Advice on Bokeh and Chart.js
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HighchartsHighchartsChart.jsChart.js
and
RechartsRecharts

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

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Replies (1)
Darren Adams
Senior Developer at Burning Glass Technologies · | 2 upvotes · 136.1K views
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HighchartsHighcharts

I've used Highcharts with both Angular Js Reactive applications (render as ReactJs) and also a bit of D3. Personally I found Highcharts to be the easiest to use but, with still quite a good level of customisability if you need it. graphs and charts then give D3 a try.

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Pros of Bokeh
Pros of Chart.js
  • 12
    Beautiful Interactive charts in seconds
  • 19
    Offers all types of charts
  • 14
    Interactive Charts
  • 10
    It's totally free

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Cons of Bokeh
Cons of Chart.js
    Be the first to leave a con
    • 12
      Slow rendering
    • 2
      Bitmap quality export
    • 1
      Low quality zoom plugin
    • 0
      It's totally free

    Sign up to add or upvote consMake informed product decisions

    What is Bokeh?

    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.

    What is Chart.js?

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

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    What companies use Bokeh?
    What companies use Chart.js?
    See which teams inside your own company are using Bokeh or Chart.js.
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    What tools integrate with Bokeh?
    What tools integrate with Chart.js?

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    What are some alternatives to Bokeh and Chart.js?
    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.
    Matplotlib
    It is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. It can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application servers, and four graphical user interface toolkits.
    Dash
    Dash is an API Documentation Browser and Code Snippet Manager. Dash stores snippets of code and instantly searches offline documentation sets for 150+ APIs. You can even generate your own docsets or request docsets to be included.
    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.
    Tableau
    Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.
    See all alternatives