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What are the common ways to handle missing data in a dataset?

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Missing data is one of the standard factors while working with data and handling. It is considered as one of the greatest challenges faced by the data analysts. There are many ways one can impute the missing values. Some of the common methods to handle missing data in datasets can be defined as deleting the rows, replacing with mean/median/mode, predicting the missing values, assigning a unique category, using algorithms that support missing values, etc.

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