Bokeh

Bokeh is an interactive visualization library for Python that enables the creation of scalable, sophisticated graphics for web browsers. It allows developers to build dynamic visualizations with high-performance interactivity and can handle large datasets efficiently. Bokeh provides tools to create plots, dashboards, and data applications with ease, offering flexibility through its ability to integrate with other libraries and frameworks.

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About Bokeh

Bokeh was created in 2013 by the developers at Continuum Analytics, now known as Anaconda, Inc. It was developed to address the need for interactive and scalable data visualizations within web browsers, specifically targeting Python users who required a way to present large datasets effectively. The library aimed to bridge the gap between modern web technologies and data science needs, providing a tool that could generate complex visualizations without extensive JavaScript knowledge.

Bokeh's strengths include its ability to create interactive and visually appealing plots, its integration with Python, and support for handling large datasets. Weaknesses involve a steeper learning curve compared to some other libraries and occasional performance issues with very complex visualizations. Competitors include Plotly, which offers similar interactive capabilities, Matplotlib for static plots, and Seaborn for statistical data visualization.

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How to hire a Bokeh expert

A Bokeh expert must have strong proficiency in Python programming, including understanding data manipulation libraries like Pandas and NumPy. They should be skilled in creating and customizing visualizations using Bokeh's APIs, including plots, layouts, and widgets. Knowledge of HTML, CSS, and JavaScript is beneficial for integrating Bokeh plots into web applications. Familiarity with data visualization principles and experience in handling large datasets are also essential for effectively using Bokeh's capabilities.

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