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The tutorial focuses on a common data cleaning task: removing duplicates from a dataset, which is also a frequent interview question for data or financial analyst positions. The instructor will demonstrate three methods for identifying and removing duplicates, emphasizing the importance of understanding the advantages and disadvantages of each method, as they may yield different results. The example provided involves a table containing sales agent, region, and sales value, where the goal is to eliminate duplicate rows while retaining one instance of each unique entry. The tutorial will clarify what constitutes a duplicate by comparing rows within the dataset.
