Create visual representations of data that models real-world phenomena or processes : Scatter Plots

The video tutorial guides viewers through creating a scatter plot using Python's Matplotlib library. It starts with setting up a new file and importing necessary libraries. The instructor then prepares data arrays for plotting, explains the scatter function, and demonstrates how to annotate and label the plot. Finally, the video covers running the script and debugging common errors, ensuring the scatter plot displays correctly with titles and labels.

What is the purpose of importing Matplotlib's pyplot as plt?

• To generate random numbers

• To import data from Excel

• To simplify the syntax for plotting

• To create 3D plots

Which arrays are defined for creating the scatter plot?

• friends, minutes, labels

• colors, sizes, shapes

• x, y, z

• names, ages, scores

What is the function used to create a scatter plot in Matplotlib?

• line()

• bar()

• scatter()

• plot()

How are the data points labeled in the scatter plot?

• Using alphabetical order

• Using shapes

• Using colors

• Using numbers

What is the purpose of the annotate function in the scatter plot?

• To change the color of the plot

• To add labels to data points

• To adjust the size of the plot

• To create a legend

What should be corrected if the plot title is not displaying?

• Change the color scheme

• Check the data arrays

• Ensure plt.title is used

• Adjust the plot size

What is the final step after creating the scatter plot script?

• Print the plot on paper

• Save the plot as an image

• Run the script in the command prompt

• Email the plot to a friend