Data Analytics using Python Visualizations - Customizing Your Plots

This video tutorial covers how to customize various parameters in bouquet plots. It begins with an introduction to the topic, followed by a practical example using the figure function to create a plot. The tutorial explains how to use the sizing mode to adjust the plot's width in a browser or Jupyter notebook. It also demonstrates how to customize the X and Y axes, including changing line colors and orientations. The video concludes with a summary and a preview of upcoming topics in bouquet.

What function is used to create the figure object in bouquet plots?

• figure()

• drawPlot()

• plot()

• createFigure()

What does the 'stretch width' sizing mode do to a plot?

• It centers the plot in the browser.

• It makes the plot take up the entire width of the browser.

• It stretches the plot vertically.

• It reduces the plot size to fit the content.

In the context of bouquet plots, what can be customized using the figure.xaxis property?

• Line color of the X axis

• Plot title

• Data points shape

• Plot background color

How can the orientation of major level text on the Y axis be customized?

• By changing the plot height

• By using the 'vertical' orientation setting

• By modifying the plot title

• By adjusting the plot width

What color was used for the Y axis major level text in the example?

• Red

• Green

• Blue

• Orange