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In this tutorial, we will learn how to replace or modify values in a pandas DataFrame using a dataset from New York City's open data, which lists open government positions along with job IDs, titles, agencies, internal/external status, categories, and expected salaries. The first focus is on handling missing values (None) in the DataFrame. To replace these, you can use the method `data.fillna()`, specifying the desired fill value. The tutorial also mentions various ways to identify missing values, with a reference to a previous video for more details on the topic.