bigframes.pandas.DatetimeIndex.drop_duplicates

DatetimeIndex.drop_duplicates(*, keep: __builtins__.str = 'first') → Index

Return Index with duplicate values removed.

Examples:

>>> import bigframes.pandas as bpd

Generate an pandas.Index with duplicate values.

>>> idx = bpd.Index(['lama', 'cow', 'lama', 'beetle', 'lama', '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')
Index(['lama', 'cow', 'beetle', 'hippo'], dtype='string')

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

>>> idx.drop_duplicates(keep='last')
Index(['cow', 'beetle', 'lama', 'hippo'], dtype='string')

The value False discards all sets of duplicated entries.

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

Parameters:

keep ({‘first’, ‘last’, False}, default ‘first’) – One of: ‘first’ : Drop duplicates except for the first occurrence. ‘last’ : Drop duplicates except for the last occurrence. False : Drop all duplicates.

Returns:

bigframes.pandas.Index