Data Science and Machine Learning (Theory and Projects) A to Z - Bokeh for Interactive Plotting: Bokeh Multiplots Marker

This video tutorial introduces Bokeh, a tool for creating browser-based interactive plots. It covers embedding plots in Jupyter notebooks, customizing plot dimensions, and exploring advanced features like data generation and interactive elements. The tutorial also demonstrates how to use different plot markers and legends, and concludes with a preview of grid plots for organizing multiple plots.

What is the primary purpose of using Bokeh in a notebook?

• To compile code

• To write text documents

• To create static images

• To generate interactive plots

Which function is used to ensure plots appear in the same notebook?

• save()

• output_notebook()

• output_file()

• show()

What property would you set to change the width of a plot?

• plot_height

• plot_width

• plot_size

• plot_length

Which function is used to generate a range of numbers for plotting?

• np.generate()

• np.linspace()

• np.arange()

• np.range()

What marker type is used to plot data as circles?

• square()

• circle()

• triangle()

• line()

How can you customize the color of a plot marker?

• By setting the 'color' property

• By setting the 'size' property

• By setting the 'shape' property

• By setting the 'legend' property

What feature allows you to have multiple plots in a grid layout?

• Interactive mode

• Layered plot

• Grid plot

• Single plot