Python In Practice - 15 Projects to Master Python - Customizing Visualizations with Matplotlib

This video tutorial covers the installation and basic usage of Matplotlib for data visualization in Python. It begins with installing Matplotlib via Anaconda, followed by importing data using Pandas. The tutorial then demonstrates basic plotting techniques, including customizing plot lines, colors, and markers. Advanced customization options are explored, such as changing marker styles and sizes. The video concludes with adding labels and titles to plots, enhancing the overall presentation of data visualizations.

What is the first step to customize plots using Matplotlib?

• Add labels and titles to the plot

• Create a basic plot using the plot method

• Import data using pandas

• Install Matplotlib via Anaconda prompt

Which library is used to import data for plotting in this lesson?

• Seaborn

• SciPy

• Pandas

• NumPy

What function is used to read CSV data in pandas?

• load_csv()

• read_csv()

• fetch_csv()

• import_csv()

When using pyplot, what must be specified to create a plot?

• Only the Y values

• Both X and Y values

• Neither X nor Y values

• Only the X values

Why might using prices as X values disturb the plot?

• Prices are too large

• Prices are not uniform like IDs

• Prices are not supported by Matplotlib

• Prices are not numerical values

How can you change the line style to dotted in Matplotlib?

• By setting the line style to '--'

• By setting the line style to 'solid'

• By setting the line style to 'dashdot'

• By setting the line style to 'none'

What function is used to add a title to a plot in Matplotlib?

• add_title()

• title()

• plot_title()

• set_title()