modin.pandas.Index.duplicated¶

Index.duplicated(keep: Literal['first', 'last', False] = 'first') → ndarray[source]¶

Indicate duplicate index values.

Duplicated values are indicated as True values in the resulting array. Either all duplicates, all except the first, or all except the last occurrence of duplicates can be indicated.

Parameters:

keep ({'first', 'last', False}, default 'first') –

The value or values in a set of duplicates to mark as missing.

• ’first’ : Mark duplicates as True except for the first occurrence.

• ’last’ : Mark duplicates as True except for the last occurrence.

• False : Mark all duplicates as True.

Returns:

An array where duplicated values are indicated as True

Return type:

np.ndarray[bool]

See also

Series.duplicated

Equivalent method on pandas.Series.

DataFrame.duplicated

Equivalent method on pandas.DataFrame.

Examples

By default, for each set of duplicated values, the first occurrence is set to False and all others to True:

>>> idx = pd.Index(['lama', 'cow', 'lama', 'beetle', 'lama'])
>>> idx.duplicated()
array([False, False,  True, False,  True])

Copy

which is equivalent to

>>> idx.duplicated(keep='first')
array([False, False,  True, False,  True])

Copy

By using ‘last’, the last occurrence of each set of duplicated values is set on False and all others on True:

>>> idx.duplicated(keep='last')
array([ True, False,  True, False, False])

Copy

By setting keep on False, all duplicates are True:

>>> idx.duplicated(keep=False)
array([ True, False,  True, False,  True])

Copy