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

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.

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

What is the purpose of the dropna method in pandas?

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