Set axis limits with Matplotlib in Python

The video tutorial covers creating and customizing plots using Python libraries. It begins with plotting points and squares, then moves on to customizing plots with markers, labels, and legends. The tutorial explains how to adjust axis limits and introduces axis objects. Finally, it discusses enhancing plots with subplots and improving scatter visibility.

What is the primary purpose of importing NumPy and Matplotlib in the context of this tutorial?

• To manage large datasets

• To enhance the performance of Python scripts

• To create and customize plots

• To perform complex mathematical operations

Which command is used to import Matplotlib's Pyplot module?

• import matplotlib.pyplot as plt

• import matplotlib.chart as plt

• import matplotlib.plot as plt

• import matplotlib.graph as plt

Which of the following is NOT a customization option discussed for data points in the plot?

• Changing marker size

• Adding labels

• Creating legends

• Adjusting line thickness

How can you set the Y-axis limits to range from -300 to 300?

• By using the command plt.set_ylim(-300, 300)

• By using the command plt.axis([-300, 300])

• By using the command plt.set_yaxis(-300, 300)

• By using the command plt.ylim(-300, 300)

What is the purpose of setting axis limits in a plot?

• To change the color of the plot

• To define the range of data displayed

• To add labels to the plot

• To increase the plot's resolution

What is a potential issue with using large marker sizes in scatter plots?

• They make the plot less colorful

• They can cause data points to overlap

• They reduce the plot's resolution

• They increase the plot's complexity

What is the benefit of using subplots in data visualization?

• To increase the number of data points

• To reduce the file size of the plot

• To separate different data sets for clarity

• To enhance the color scheme of the plot