How do you handle missing data in a DataFrame using Pandas?

Instruction: Demonstrate with an example how you would handle missing data in a dataset using Pandas.

Context: This question assesses the candidate's knowledge of data preprocessing techniques in Pandas, specifically focusing on handling missing values, which is a common issue in data analysis.

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Firstly, I assess the nature and extent of missing data within the DataFrame. It's crucial to understand whether the missingness is random or systematic, as this informs the strategy for dealing with these values. For demonstration purposes, let's assume we're working with a dataset where we have user demographics and usage patterns, and we've identified missing values in the 'age' and 'last_login_date' columns.

To begin, I use the isnull() method combined with sum() to quantify missing values per column:...

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