drop_duplicates(self, keep='first', inplace=False) -> 'Series | None'
Method to handle dropping duplicates:
If True
, performs operation inplace and returns None.
Series with duplicates dropped or None if inplace=True
.
Return Series with duplicate values removed.
DataFrame.drop_duplicates
Equivalent method on DataFrame.
Index.drop_duplicates
Equivalent method on Index.
Series.duplicated
Related method on Series, indicating duplicate Series values.
Generate a Series with duplicated entries.
This example is valid syntax, but we were not able to check execution>>> s = pd.Series(['lama', 'cow', 'lama', 'beetle', 'lama', 'hippo'],
... name='animal')
... s 0 lama 1 cow 2 lama 3 beetle 4 lama 5 hippo Name: animal, dtype: object
With the 'keep' parameter, the selection behaviour of duplicated values can be changed. The value 'first' keeps the first occurrence for each set of duplicated entries. The default value of keep is 'first'.
This example is valid syntax, but we were not able to check execution>>> s.drop_duplicates() 0 lama 1 cow 3 beetle 5 hippo Name: animal, dtype: object
The value 'last' for parameter 'keep' keeps the last occurrence for each set of duplicated entries.
This example is valid syntax, but we were not able to check execution>>> s.drop_duplicates(keep='last') 1 cow 3 beetle 4 lama 5 hippo Name: animal, dtype: object
The value False
for parameter 'keep' discards all sets of duplicated entries. Setting the value of 'inplace' to True
performs the operation inplace and returns None
.
>>> s.drop_duplicates(keep=False, inplace=True)See :
... s 1 cow 3 beetle 5 hippo Name: animal, dtype: object
The following pages refer to to this document either explicitly or contain code examples using this.
pandas.core.series.Series.duplicated
pandas.core.series.Series.drop
pandas.core.frame.DataFrame.duplicated
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