How to Build Interactive Data Visualizations for Python with Bokeh

  • Bokeh is a powerful tool for exploring and understanding your data or creating beautiful custom charts for a project or report.
  • Bokeh provides a Python API to create visual data applications in D3.js, without necessarily writing any JavaScript code.
  • It allows the use of standard Pandas and NumPy objects for plotting, including NumPy arrays, plain lists and Pandas series.
  • In the Python visualization space, Bokeh is the most ideal candidate for building interactive and dynamic visualizations across different mediums.
  • Using Bokeh to transform your data into visualizations
  • Customizing your visualizations using Bokeh
  • Adding interactivity to your visualizations
  • NumPy arrays
  • plain lists
  • Pandas series
  • Gestures (Pan/Drag Tools, Click/Tap Tools, Scroll/Pinch Tools)
  • Actions (Reset Tool)
  • Inspectors (HoverTool, CrosshairTool.)
  • Edit Tools
  • output_file() for saving plots in the outer .html file
  • output_notebook() for rendering directly in Jupyter notebooks



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Education Ecosystem (LEDU)

Education Ecosystem (LEDU)

Education Ecosystem (LEDU) is a decentralized project-based learning platform that teaches people how to build tech products,