Python for Data Analysis: Step-By-Step with Projects - Relationship of Two Features (1)

Python for Data Analysis: Step-By-Step with Projects - Relationship of Two Features (1)

Assessment

Interactive Video

Created by

Quizizz Content

Computers

9th - 10th Grade

Hard

11:38

This video tutorial explores the use of the Seaborn library to visualize relationships between features in a dataset. It covers various plotting techniques such as scatter plots, pair plots, and joint plots to analyze numeric features. The tutorial also explains how to use correlation matrices and heatmaps to understand feature relationships. By the end, viewers will be able to explore relationships between numeric and categorical features using Seaborn's visualization tools.

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10 questions

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1.

MULTIPLE CHOICE

30 sec • 1 pt

What is the primary purpose of using the Seaborn library in data visualization?

2.

MULTIPLE CHOICE

30 sec • 1 pt

Which Seaborn function is used to create a simple scatter plot?

3.

MULTIPLE CHOICE

30 sec • 1 pt

What does the pairplot function in Seaborn help visualize?

4.

MULTIPLE CHOICE

30 sec • 1 pt

How does the jointplot function enhance the visualization of two numeric features?

5.

MULTIPLE CHOICE

30 sec • 1 pt

What is the purpose of a correlation matrix in data analysis?

6.

MULTIPLE CHOICE

30 sec • 1 pt

What does a heatmap represent in the context of a correlation matrix?

7.

MULTIPLE CHOICE

30 sec • 1 pt

Which color in a heatmap indicates a strong negative correlation?

8.

MULTIPLE CHOICE

30 sec • 1 pt

What does a correlation value close to zero indicate?

9.

MULTIPLE CHOICE

30 sec • 1 pt

Which Seaborn function is used to visualize the relationship between one categorical and one numeric feature?

10.

MULTIPLE CHOICE

30 sec • 1 pt

What type of plot is suitable for visualizing the relationship between two categorical features?

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