pandas for Python - A Quick Guide - Handling Missing Values and Duplicates

pandas for Python - A Quick Guide - Handling Missing Values and Duplicates

Assessment

Interactive Video

Information Technology (IT), Architecture, Social Studies

University

Hard

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The video tutorial covers data preprocessing, focusing on handling missing data and duplicates in datasets. It explains how to identify missing values and duplicates using pandas, and demonstrates methods to address these issues, such as removing or replacing missing values and eliminating duplicate rows. The tutorial uses the Titanic dataset for practical examples, highlighting the importance of data cleaning in data analysis.

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3 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

Explain how to check for missing values in a DataFrame using pandas.

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the purpose of the dropna method in pandas?

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3.

OPEN ENDED QUESTION

3 mins • 1 pt

How can you replace missing values with the average of a column in pandas?

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