Data Analytics using Python Visualizations - Using the ColumnDataSource Object

This video tutorial explains how to use the column data source object in Bokeh, a key data structure for managing data in Bokeh plots. It covers the conversion of Numpy and Pandas data structures into column data source objects and demonstrates how to create and use these objects directly. The tutorial includes a practical example of plotting a circle plot using a column data source, with years on the X-axis and sales volumes on the Y-axis. The video concludes with a summary and a preview of the next topic in the series.

What is the primary role of the column data source object in Bokeh?

• To create animations

• To handle user inputs

• To replace Numpy and Pandas

• To manage data for Bokeh plots

How can you create a column data source object in Bokeh?

• By using a list

• By using a dictionary or data frame

• By using a string

• By using a tuple

In the example provided, what data is plotted along the X axis?

• Sales volumes

• Customer IDs

• Product names

• Years

What function is used to display the plot in Bokeh?

• plot()

• show()

• render()

• display()

Which of the following is NOT a component of the circle plot example?

• Y axis parameter

• Data source

• Animation speed

• X axis parameter