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In this tutorial, we will learn how to replace or modify values in a pandas DataFrame. The dataset used is a list of open positions in the New York City government, obtained from New York City Open Data. It includes job IDs, titles, agencies, external/internal status, categories, and salary ranges. The tutorial focuses on handling missing values (None) in the DataFrame. To replace missing values in pandas, the method `data.fillna()` is used. If you have a specific value to replace the missing entries, you can input it directly. The instructor also mentions that there are various ways to identify missing values, with links to more detailed videos provided.