Data Analytics using Python Visualizations - Creating Scatter Plots

This video tutorial explains how to create and customize scatter plots using the Matplotlib library. It covers two methods: using the plot method and the scatter method. The tutorial also discusses how to customize marker styles, sizes, and colors, and compares scatter plots with line plots. By the end, viewers will understand how to create scatter plots and customize them using different attributes.

What is the main difference between scatter plots and line plots?

• Scatter plots connect data points with lines.

• Line plots display data points without connecting them.

• Scatter plots display data points without connecting them.

• Line plots use bars to represent data.

How can you create a scatter plot using the plot method?

• By using a different library.

• By using only the X-axis data.

• By adjusting the third argument for marker type and color.

• By connecting all data points with lines.

Which marker type is represented by the 'o' character in the plot method?

• Triangle

• Circle

• Square

• Pentagon

What attribute can be changed to increase the size of markers in a plot?

• Marker shape

• Marker size

• Marker edge color

• Marker face color

Which attribute controls the transparency level of markers in a scatter plot?

• Gamma

• Alpha

• Beta

• Delta

What method is used to create scatter plots with more customization options?

• Bar method

• Line method

• Histogram method

• Scatter method

Which of the following is NOT a customizable attribute for markers?

• Marker size

• Marker face color

• Marker edge weight

• Marker transparency