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

The video tutorial introduces the concept of static and interactive plotting libraries, focusing on Bokeh as an interactive library. It guides viewers through setting up Bokeh in a Jupyter Notebook, creating a basic plot, and troubleshooting common issues. The tutorial also highlights the interactive features of Bokeh, such as zooming and saving plots, and briefly mentions other interactive libraries like Plotly.

Which of the following libraries is known for interactive plotting?

• Matplotlib

• Pandas

• Seaborn

• Bokeh

What is the purpose of setting an output file in Bokeh?

• To display plots in a browser

• To save plots as images

• To export plots to PDF

• To print plots directly

What is the correct way to specify the width of a line in Bokeh?

• lineWidth

• width_line

• line_width

• linewidth

Which feature is NOT available in Bokeh's interactive plots?

• Zooming

• Saving images

• 3D plotting

• Resetting the view

What is a common error when using Bokeh's line function?

• Incorrect data types

• Unsupported file format

• Missing data points

• Misspelled attributes