The correct option is drop_duplicates(keep='last').

The DataFrame method drop_duplicates(keep='last') removes duplicate rows and preserves only the final occurrence of each set of duplicates when you set the keep parameter to 'last'. You can return a new DataFrame or apply the operation in place and this behavior directly matches the requirement to keep only the last instance of every duplicate.

duplicated(keep='last') is incorrect because duplicated returns a boolean mask that marks which rows are duplicates and it does not itself remove rows. You would need to apply that mask with additional indexing to obtain a DataFrame without earlier duplicates.

dropdupes(retain='last') is incorrect because there is no such pandas method. The correct pandas method name is drop_duplicates and the parameter names differ from the ones shown.

drop_duplicates() is incorrect because calling drop_duplicates without arguments uses the default keep behavior which is 'first'. That default will preserve the first occurrence and drop later ones which is the opposite of keeping only the final occurrence.

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