Bokeh Interactive Visualizations

 

Bokeh is an open-source Python library for creating interactive web-based visualizations. It provides high-level constructs for declaratively creating graphics, and an intuitive, high-level Python interface. Bokeh can be used to create a wide variety of interactive visualizations, including:

  • Line plots
  • Scatter plots
  • Bar charts
  • Pie charts
  • Heatmaps
  • Choropleth maps
  • And more

Bokeh is a powerful tool for data visualization, and it is easy to learn. Here are some of the key features of Bokeh:

  • High-level constructs: Bokeh provides high-level constructs for declaratively creating graphics. This means that you can specify the appearance of your graphics without having to worry about the underlying JavaScript code.
  • Intuitive, high-level Python interface: Bokeh provides an intuitive, high-level Python interface for creating and interacting with visualizations. This makes it easy to create and customize your visualizations.
  • Wide range of features: Bokeh supports a wide range of features, including:
    • Interactive panning and zooming
    • Data-driven styling
    • Customization of legends, axes, and other elements
    • Exporting to HTML, PNG, and SVG
  • Flexibility: Bokeh is a flexible library that can be used to create a wide variety of visualizations. It can also be used to create custom visualizations that are not supported by other libraries.

If you are looking for a powerful, easy-to-use data visualization library, Bokeh is a great option. It is a popular choice for data scientists, analysts, and developers who need to create interactive visualizations.

Here are some of the functions of Bokeh:

  • plot(): This function is used to create a new plot. The plot can be customized using a variety of arguments, such as the type of plot, the data, and the style.
  • show(): This function is used to show the plot. The plot can be shown in a Jupyter notebook or in a web browser.
  • save(): This function is used to save the plot to a file. The file can be saved in a variety of formats, such as HTML, PNG, and SVG.
  • interact(): This function is used to create an interactive plot. The plot can be interacted with using a variety of controls, such as sliders, buttons, and text boxes.
  • layout(): This function is used to create a layout for a group of plots. The layout can be customized using a variety of arguments, such as the position of the plots and the spacing between the plots.

These are just a few of the many functions that are available in Bokeh. For more information, please refer to the Bokeh documentation.

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