maxframe.dataframe.Index.drop_duplicates

Index.drop_duplicates(keep='first', method='auto')

Return Index with duplicate values removed.

Parameters:

keep ({‘first’, ‘last’, False}, default ‘first’) –

• ‘first’ : Drop duplicates except for the first occurrence.

• ’last’ : Drop duplicates except for the last occurrence.

• ’any’ : Drop duplicates except for a random occurrence.

• False : Drop all duplicates.

Returns:

deduplicated

Return type:

Index

See also

Series.drop_duplicates

Equivalent method on Series.

DataFrame.drop_duplicates

Equivalent method on DataFrame.

Index.duplicated

Related method on Index, indicating duplicate Index values.

Examples

Generate a pandas.Index with duplicate values.

>>> import maxframe.dataframe as md

>>> idx = md.Index(['lame', 'cow', 'lame', 'beetle', 'lame', 'hippo'])

The keep parameter controls which duplicate values are removed. The value ‘first’ keeps the first occurrence for each set of duplicated entries. The default value of keep is ‘first’.

>>> idx.drop_duplicates(keep='first').execute()
Index(['lame', 'cow', 'beetle', 'hippo'], dtype='object')

The value ‘last’ keeps the last occurrence for each set of duplicated entries.

>>> idx.drop_duplicates(keep='last').execute()
Index(['cow', 'beetle', 'lame', 'hippo'], dtype='object')

The value False discards all sets of duplicated entries.

>>> idx.drop_duplicates(keep=False).execute()
Index(['cow', 'beetle', 'hippo'], dtype='object')