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DOC: Fix EX01 in DataFrame.duplicated #33416

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Apr 9, 2020
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DOC: Fix EX01 in DataFrame.duplicated #33416

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DOC: Fix EX01 in pandas.DataFrame.duplicated
farhanreynaldo Apr 9, 2020
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DOC: Fix EX01 in DataFrame.duplicated
farhanreynaldo Apr 9, 2020
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67 changes: 67 additions & 0 deletions pandas/core/frame.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4740,6 +4740,73 @@ def duplicated(
Returns
-------
Series
Boolean series for each duplicated rows.

See Also
--------
Index.duplicated : Equivalent method on index.
Series.duplicated : Equivalent method on Series.
Series.drop_duplicates : Remove duplicate values from Series.
DataFrame.drop_duplicates : Remove duplicate values from DataFrame.

Examples
--------
Consider dataset containing ramen rating.

>>> df = pd.DataFrame({
... 'brand': ['Yum Yum', 'Yum Yum', 'Indomie', 'Indomie', 'Indomie'],
... 'style': ['cup', 'cup', 'cup', 'pack', 'pack'],
... 'rating': [4, 4, 3.5, 15, 5]
... })
>>> df
brand style rating
0 Yum Yum cup 4.0
1 Yum Yum cup 4.0
2 Indomie cup 3.5
3 Indomie pack 15.0
4 Indomie pack 5.0

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

>>> df.duplicated()
0 False
1 True
2 False
3 False
4 False
dtype: bool

By using 'last', the last occurrence of each set of duplicated values
is set on False and all others on True.

>>> df.duplicated(keep='last')
0 True
1 False
2 False
3 False
4 False
dtype: bool

By setting ``keep`` on False, all duplicates are True.

>>> df.duplicated(keep=False)
0 True
1 True
2 False
3 False
4 False
dtype: bool

To find duplicates on specific column(s), use ``subset``.

>>> df.duplicated(subset=['brand'])
0 False
1 True
2 False
3 True
4 True
dtype: bool
"""
from pandas.core.sorting import get_group_index
from pandas._libs.hashtable import duplicated_int64, _SIZE_HINT_LIMIT
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