Bokeh

68
102
+ 1
10
Matplotlib

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Bokeh vs Matplotlib: What are the differences?

Developers describe Bokeh as "An interactive visualization library *". It is an interactive visualization library that targets modern web browsers for presentation. Its goal is to provide elegant, concise construction of versatile graphics, and to extend this capability with high-performance interactivity over very large or streaming datasets. It can help anyone who would like to quickly and easily create interactive plots, dashboards, and data applications. On the other hand, *Matplotlib** is detailed as "A plotting library for the Python programming language". 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.

Bokeh and Matplotlib can be primarily classified as "Charting Libraries" tools.

According to the StackShare community, Matplotlib has a broader approval, being mentioned in 10 company stacks & 19 developers stacks; compared to Bokeh, which is listed in 4 company stacks and 7 developer stacks.

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    - No public GitHub repository available -

    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 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.
    What companies use Bokeh?
    What companies use Matplotlib?

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    What tools integrate with Bokeh?
    What tools integrate with Matplotlib?

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    What are some alternatives to Bokeh and Matplotlib?
    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.
    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.
    Shiny
    It is an open source R package that provides an elegant and powerful web framework for building web applications using R. It helps you turn your analyses into interactive web applications without requiring HTML, CSS, or JavaScript knowledge.
    See all alternatives
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