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Standardize the format of the names across all columns by ensuring that they are in one consistent format (e.g., first name, middle name/initial, last name).

Ensure that the names in each column are clean, consistent, and free of errors, such as misspellings or extra spaces.

Use data cleansing tools and techniques to identify and remove any duplicates or erroneous data in the names columns.

Add new columns to the dataset that specify the individual's full name, first name, middle name, and last name for easier merging in pandas.

Use fuzzy matching algorithms or string distance metrics to identify and merge similar names that may have slight variations, such as nicknames or alternate spellings.

Consider using external data sources or APIs to verify and standardize the format of the names, such as by checking them against a database of known names.

Leverage advanced pandas operations, such as join(), merge(), and concat(), to efficiently merge the names columns while avoiding any common pitfalls like losing data or generating redundant matches.