By taking a look at our test data set, we can assume that row 11 and 12 are duplicates.To discover duplicates, we can use the duplicated() method.The duplicated() method returns a Boolean values for each row:ExampleGet your own Python Server Returns True for every row that is a ...
DataFrame.drop_duplicates(subset=None, keep=’first’, inplace=False) Subset: In this argument, we define the column list to consider for identifying duplicate rows. If it considers all columns in case, we do not specify any values Keep: Here, we can specify the following values: First...