Data Science and Machine Learning (Theory and Projects) A to Z - Pandas for Data Manipulation: Pandas Missing Values

The video tutorial covers handling missing values in pandas, including the use of NaN and None. It explains how to fill missing values using the fillna function and how to drop them with dropna. The tutorial also touches on advanced techniques like using averages or regression for imputation, and previews the next video on implicit and explicit indices in pandas.

Describe the dropna function and when it should be used.

What are some alternative methods to handle missing values in data?

Discuss the confusion between implicit and explicit indices in Pandas.