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DOC: Fix EX01 in DataFrame.drop_duplicates #33283

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Apr 10, 2020
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DOC: Fix EX01 in DataFrame.drop_duplicates #33283

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DOC: Fix EX01 in DataFrame.drop_duplicates
farhanreynaldo Apr 4, 2020
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DOC: Fix EX01 in DataFrame.drop_duplicates
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Merge branch 'master' of https://github.com/pandas-dev/pandas into dr…
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42 changes: 42 additions & 0 deletions pandas/core/frame.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4673,6 +4673,48 @@ def drop_duplicates(
See Also
--------
DataFrame.value_counts: Count unique combinations of columns.

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

>>> brand = ['Yum Yum', 'Yum Yum', 'Indomie', 'Indomie', 'Indomie']
>>> df = pd.DataFrame({
... 'brand': brand,
... '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, it removes duplicate rows based on all columns

>>> df.drop_duplicates()
brand style rating
0 Yum Yum cup 4.0
2 Indomie cup 3.5
3 Indomie pack 15.0
4 Indomie pack 5.0

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

>>> df.drop_duplicates(subset=['brand'])
brand style rating
0 Yum Yum cup 4.0
2 Indomie cup 3.5

To remove duplicates and keep last occurences, use ``keep``

>>> df.drop_duplicates(subset=['brand', 'style'], keep='last')
brand style rating
1 Yum Yum cup 4.0
2 Indomie cup 3.5
4 Indomie pack 5.0
"""
if self.empty:
return self.copy()
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