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In this tutorial, the focus is on a common data cleaning task: removing duplicates, a frequent topic in data and financial analyst interviews. The presenter will demonstrate three methods for achieving this, emphasizing the importance of understanding the advantages and disadvantages of each approach. The tutorial uses a table with sales data, highlighting that duplicates are identified by identical entries across relevant fields. For instance, two entries are considered duplicates if they share the same sales agent, region, and sales value. The goal is to keep only one occurrence of each duplicate row in the final dataset.
