Data Science and Machine Learning (Theory and Projects) A to Z - Seaborn for Data Visualization: Seaborn Relplot Kind Li

The video tutorial explores the use of line plots with the iris dataset using Seaborn. It covers how to customize plots by setting CI, hue, and style, and demonstrates advanced features like markers and dashes. The tutorial also explains how to create facets and multi-dimensional plots, highlighting the flexibility and power of Seaborn for data visualization.

What is the primary function used to create line plots in Seaborn with the Iris dataset?

• sns.scatterplot

• sns.relplot

• sns.lineplot

• sns.barplot

What does setting the CI value to 'None' achieve in a Seaborn plot?

• It adds markers to the plot.

• It adds color to the plot.

• It removes the confidence interval shading.

• It changes the plot to a bar chart.

How can you differentiate between species in a Seaborn plot?

• By setting the CI value to 'standard deviation'.

• By changing the plot type to a bar chart.

• By using the 'size' parameter.

• By using the 'hue' parameter.

What effect does setting 'dashes' to 'False' have on a Seaborn plot?

• It adds a legend to the plot.

• It removes the dashed line style.

• It changes the plot to a scatter plot.

• It changes the color of the lines.

Which parameter allows you to add markers to a Seaborn line plot?

• hue

• dashes

• style

• markers

What is one of the advanced features of Seaborn mentioned in the video?

• Creating 3D plots

• Exporting plots to Excel

• Generating multi-dimensional plots

• Adding animations to plots

What is the main advantage of using Seaborn for plotting as mentioned in the video?

• It automatically generates 3D plots.

• It is the only library that supports the Iris dataset.

• It is faster than other libraries.

• It allows for complex plots with simple commands.